Study Programme for Exchange Students

Study Programme for Exchange Students

Programme in English*

for Exchange Students

in the fields of Mechanical Engineering, Engineering and Management, Electrical

Engineering and Computer Science

WS 2021/ 22 *(subject to minor modifications)


Please note, that classes with less than eight participants could be cancelled.

Semester schedule is:

Winter semester (WS): beginning of October – middle of February

Summer semester (SS): middle of March – end of July

Here in this table is a brief overview of all the classes separated in only winter-term and only summer term classes in alphabetical order with information on credit points, weekly hours. Some of them are offered on a Master´s level (+).

Below you can search for the module descriptions by clicking on the selected module in the table of contents. Please note, should you find a module that is not mentioned in this table, it will not be on offer for this term!

Winter term classes:

Subject Language

Hours Credits Winter/ Summer

Master

Note Faculty

Advanced Manufacturing Technologies

E 4 5 W + Adv_Man_Tech_M-EGM

Engineering and Management

AI Technologies for Knowledge Representation and Reasoning

E 4 5 W AI_TechKnRepRea_FW


Audio/Video Processing and 3D-Animation +Practical Training

E 3 + 2 8 W + UXDM_AVP Computer Science

Augmented and Virtual Reality Applications +Practical Training

E 3 + 2 7 W + UXDM_AVR Computer Science

Automation Technologies

E 4 5 W AUT_EGM Engineering and Management

Automotive Control Engineering

E 4 5 W + IAE_ACE Electrical Engineering and Information Technology

Automotive Electronics

E 4 5 W + IAE_AES Electrical Engineering and Information Technology

Basics of Mechanical Design

E 4 5 W BMDesign_ESYS

Mechanical Engineering

Business Administration

E 4 5 W BA_EGM_E Engineering and Management

Computer Science E 4 5 W CS_EGM_E Engineering and Management

Context and Conceptualisation in UX

E 4 5 W/S + UXDM_FW_CCUX

Computer Science


Subject Language


Master

Note Faculty

Design Strategy and Management

E 4 5 W + UXDM_DS Computer Science

Electrical Engineering E 4 5 W ETE_ESYS Mechanical Engineering

Engineering Mechanics

E 5 5 W EngMECH_EGM


Financing and Company valuation

E 4 5 W FinancCompValu_FW


Foundations of Engineering Sciences

E 7 8 W AVE_EngSci Electrical Engineering and Information Technology

International Management

E 4 5 W + Int_Mgt_M-EGM


Intelligent Decision Systems

E 4 5 W IntDecSys_FW


Introduction to Computer Science 1 +Exercise Course

E 4 + 2 7 W CAI_CS1

CAI_CS1Ex

Computer Science

Introduction to Statistical Learning

E 4 5 W IntroStatLearn_FW


Innovation Management Methods

E 4 5 W + InnoMaMeth_M-GFT


Java based Cloud Architectures

E 4 5 W IB_JBCA Computer Science

Mobile App Development

E 4 5 W + UXDM_FWMAD

Computer Science

Management Accounting & International Taxation

E 4 5 W + MgtAcc_IntTax_M-EGM


Mathematical Modelling and Simulation

E 4 5 W/S + IAE_MMS Electrical Engineering and Information Technology

Mathematics 1 (Faculty CS) +Exercise Course

E 4 + 2 7 W CAI_Math1

CAI_Math1Ex

Computer Science

Mathematics 1 (Faculty E)

E 7 8 W AVE_Math1 Electrical Engineering and Information Technology

Mathematics 1 (Faculty EGM)

E 5 5 W MA1_EGM_E


Mechanical Design 1 E 4 5 W MD1_EGM_E



Subject Language


Master

Note Faculty

Power Train E 4 5 W + IAE_PT Electrical Engineering and Information Technology

Power Supply and Energy Distribution

E 4 5 W + IAE_PSED Electrical Engineering and Information Technology

Programming 1 +Practical Course (CAI)

E 4 + 2 7 W CAI_Prog1

CAI_Prog1Pr

Computer Science

Programming 1 (AVE)

E 6 7 W/S AVE_Progr_1

Electrical Engineering and Information Technology

Programming 2 E 6 6 W/S AVE-Programming 2


Probability and Statistics +Exercise Course

E 4 + 2 7 W CAI_PrSt

CAI_PrStEx

Computer Science

Qualitative UX Design Research & Methods

E 4 5 W UXD_DRM_FW

Computer Science

Selected Topics in Digitalization

E 4 5 W + SelTop_Digi_M-EGM


Sensor Technology and Signal Processing

E 4 5 W + IAE_ST&SP Electrical Engineering and Information Technology

Smart Mobility: Trends in Intelligent and Sustainable Mobility Systems

E 4 5 W + SmartMobility_M-EGM


Software Development

E 4 5 W SWD_EGM Engineering and Management

Special Topics in Financial Modelling

E 4 5 W + SpecTopFinMod_M-EGM


Statics E 4 5 W ST_ESYS Mechanical Engineering

Strategic Foresight and Trend Analysis

E 4 5 W + StratFor_M-GFT


System Analysis and Control 1

E 4 5 W + SysAnaCon_M-RES

Mechanical Engineering

Technology Design and Evaluation

E 4 5 W + TechDesEva_M-GFT


1 Difficult subject; max. 4 students


Subject Language


Master

Note Faculty

Vehicle Crash Mechanics and Biomechanics

E 4 5 W + IAE_VCM Electrical Engineering and Information Technology

Wissensmodellierung und Maschinelles Lernen (Knowledge Modelling and Machine Learning)

E 4 5 W + AUF_WissMod



Summer term classes: not on offer at the moment!

Subject Language Hours Credits Winter Summer

Master

Note Faculty

Advanced Methods of Software Engineering

E 4 5 S INF-B Computer Science

Agile Project Management

E 4 3 S + UXD-M Computer Science

Algorithms and Data Structures

E 4 5 S/W AVE Electrical Engineering and Information Technology

Automotive Communication Systems

E 4 5 S + IAE Electrical Engineering and Information Technology

Autonomous Vehicles by Machine Learning Algorithms


CAx-Techniques in Automotive Engineering


Controlling E 4 5 S EGM Engineering and Management

Cost Engineering and Risk Management

E 4 5 S APE Engineering and Management

Cryptology E 4 5 S IB_CRYL

Computer Science

Design to Create a Sustainable Strategic Vision: At the Crossroads between Business and Design

E 4 5 S UXD-B Computer Science

Development Methodologies for Automotive Systems


Digital Procurement Engineering

E 4 5 S + EGM Engineering and Management

Electrical Engineering E 5 5 S EGM Engineering and Management

Electronics, Signals and Measurement

E 6 5 S/W AVE Electrical Engineering and Information Technology

Engineering Processes in Automotive Industry

E 4 5 S + APE Engineering and Management

Exercises in Programming for Multimodal, Interactive Systems


Financial Accounting E 5 5 S EGM Engineering and Management

Foundations of Computer Science

E 6 7 S AVE Electrical Engineering and Information Technology

Interaction Design E 4 5 S + UXD-M Computer Science

International Negotiation Training




Master

Note Faculty

Introduction to AI and Neural Networks


Java Based Cloud Architectures


Machine Learning E 4 5 S INF-B Computer Sciences

Maintenance and Certification

E 4 5 S LT Mechanical Engineering

Marketing E 5 5 S EGM Engineering and Management

Material Science E 5 5 S EGM Engineering and Management

Mathematical Modelling and Simulation

E 4 5 S/W + IAE Electrical Engineering and Information Technology

Mathematics 2 (Faculty E)

E 7 8 S AVE Electrical Engineering and Information Technology

Mathematics 2 (Faculty EGM)

E 5 5 S EGM Engineering and Management

Mobility Future Programm

E 4 5 S/W WI-FW Engineering and Management

Numerical Methods and Computation Simulation

E 4 5 S + RES Mechanical Engineering

Off-Grid Energy System 2

E 8 10 S + RES Mechanical Engineering

Power Engineering E 4 5 S EGM Engineering and Management

Production and Logistics Networks

E 4 5 S + APE Engineering and Management

Programming 1 (AVE) E 6 7 S/W AVE Electrical Engineering and Information Technology

Programming 2 E 6 6 S/W AVE Electrical Engineering and Information Technology

Production Planning and Logistics


Production Systems – two parts with different lecturers


Programming for Multimodal, Interactive Systems


Project: Implementation and deployment of a ROS software environment for autono-mous model car 3


Research Methods in HCI


2 Only with the lecturer's permission; max. 3 students 3 Only with the lecturer's permission



Master

Note Faculty

Selected Topics in International Management


Selected Topics in Physics


Statistics E 4 5 S AVE Electrical Engineering and Information Technology

Symbolic AI: Knowledge Representation and Reasoning

E 2 2,5 S WI-FW Engineering and Management

Systems Engineering E 4 5 S WI-FW Engineering and Management

Testing and Simulation Methods for Vehicle Safety Systems


User Experience Design Strategy

E 4 5 S UXD-FW

Computer Science

User Experience Participatory Design

E 4 5 S + UXD-M Computer Sciences

Vehicle Dynamics E 4 5 S + IAE Electrical Engineering and Information Technology


…………

Table of Contents: 1. Advanced Manufacturing Technologies - Master´s level (APE) ......................................... 13

2. Advanced Methods of Software Engineering ......................................................................... 14

3. Agile Project Management (Master´s level) ........................................................................... 15

4. Aircraft Repair ............................................................................................................................. 16

5. AI Technologies for Knowledge Representation an Reasoning ......................................... 17

6. Algorithms and Data Structures ............................................................................................... 18

7. Artificial Intelligence and Machine Learning ........................................................................... 19

8. Audio/Video Processing and 3D-Animation - Master´s level ............................................... 20

9. Augmented and Virtual Reality Applications - Master´s level .............................................. 21

10. Ausgewählte Kapitel der Digitalisierung - Master´s level (APE) ....................................... 22

11. Automation and Equipment Technologies – Master´s level (APE) .................................. 23

12. Automation Technologies ....................................................................................................... 24

13. Automotive Communication Systems (Master´s level)....................................................... 25

14. Automotive Control Engineering – Master´s level (IAE) ..................................................... 26

15. Automotive Electronics – Master´s level .............................................................................. 27

16. Automotive Radar Systems – Master´s level (IAE)............................................................. 28

17. Autonomous Vehicles by Machine Learning Algorithms (Master’s Level) ...................... 29

18. Basics of Mechanical Design ................................................................................................. 30

19. Business Administration .......................................................................................................... 31

20. Business Information Systems ............................................................................................... 32

21. CAx Techniques in Automotive Engineering (Master´s level) ........................................... 33

22. Computer Science ................................................................................................................... 34

23. Context and Conceptualisation in UX ................................................................................... 35

24. Controlling ................................................................................................................................. 36

25. Cost Accounting ....................................................................................................................... 37

26. Cost Engineering and Risk Management ............................................................................. 38

27. Cryptology ................................................................................................................................. 39

28. Designing Interactive Products .............................................................................................. 40

29. Designing Minimum Loveable Digital Products ................................................................... 41

30. Design Strategy and Management - Master´s level ........................................................... 42


31. Design Thinking Digital ........................................................................................................... 43

32. Design to Create a Sustainable Strategic Vision: At the Crossroads between Business and Design ....................................................................................................................................... 44

33. Design von Mensch-Maschine-Schnittstellen (in English!) ................................................ 45

34. Development Methodologies for Automotive Systems (Master´s level) .......................... 46

35. Digital Factory ........................................................................................................................... 47

36. Digital Procurement Engineering - Master´s level............................................................... 48

37. Digital Technologies in Engineering – Master´s level (APE) ............................................. 49

38. Electrical Engineering .............................................................................................................. 50

39. Electronics, Signals and Measurement ................................................................................ 51

40. Energy Policies and Economies – Master´s level (RES) ................................................... 52

41. Engineering Mechanics ........................................................................................................... 53

42. Engineering Processes in Automotive Industry – Master´s level (APE) .......................... 54

43. Exercises in Programming for Multimodal and Interactive Systems (Master´s level) ... 55

44. Financial Accounting ............................................................................................................... 56

45. Financing and Company valuation ........................................................................................ 57

46. Foundations of Computer Science ........................................................................................ 58

47. Foundations of Engineering Sciences .................................................................................. 59

48. Industrial Energy System – Master´s level (RES) ............................................................... 60

49. Integrated Safety and Assistance Systems (Master´s level) ............................................. 61

50. International Management ...................................................................................................... 62

51. Intelligent Decision Systems .................................................................................................. 63

52. Interaction Design (Master´s level)........................................................................................ 64

53. Interface Design (Master´s level) ........................................................................................... 65

54. International Negotiation Training - Master´s level ............................................................. 66

55. Introduction to AI and Neural Networks - Master´s level ................................................... 67

56. Introduction to Computer Science 1 ...................................................................................... 68

57. Introduction to Statistical Learning ........................................................................................ 69

58. Innovation Management Methods ......................................................................................... 70

59. Java Based Cloud Architectures............................................................................................ 71

60. Machine Learning..................................................................................................................... 72

61. Maintenance and Certification ............................................................................................... 73

62. Mobile App Development - Master´s level ........................................................................... 74

63. Kommunikationsnetze (in English!) ....................................................................................... 75

64. Marketing ................................................................................................................................... 76


65. Material Science ....................................................................................................................... 77

66. Management Accounting & International Taxation ............................................................. 78

67. Mathematical Modelling and Simulation – Master´s level (IAE) ....................................... 79

68. Mathematics 1 (CAI) ................................................................................................................ 80

69. Mathematics 1 (AVE) ............................................................................................................... 81

70. Mathematics 2 (AVE) ............................................................................................................... 82

71. Mathematics 1 (EGM) ............................................................................................................. 83

72. Mathematics 2 (EGM) ............................................................................................................. 84

73. Mechanical Design 1 ............................................................................................................... 85

74. Mobility Future Programme .................................................................................................... 86

75. Natural User Interfaces (Master´s level) ............................................................................... 88

76. Numerical Methods and Computation Simulation ............................................................... 89

77. Off-Grid Energy System – Master´s level (RES) ................................................................. 90

78. Power Engineering................................................................................................................... 91

79. Power Train – Master´s level (IAE) ....................................................................................... 92

80. Power Supply and Energy Distribution ................................................................................. 93

81. Practical Training in Interaction Design (Master´s level) ................................................... 94

82. Production and Logistics Networks – Master´s level (APE) .............................................. 95

83. Programming 1 (CAI) ............................................................................................................... 96

84. Programming 1 (AVE) ............................................................................................................. 97

85. Programming 2 ......................................................................................................................... 98

86. Production Management and Optimisation – Master´s level (APE) ................................. 99

87. Production System and Plant Design – Master´s level (APE) ........................................ 100

88. Production Planning and Logistics ...................................................................................... 102

89. Production Systems: two parts with two different lecturers ............................................. 103

90. Programming for Multimodal and Interactive Systems (Master´s level) ........................ 104

91. Project: ..................................................................................................................................... 105

92. Project: Implementation and deployment of a ROS software environment for autonomous model car ................................................................................................................ 106

93. Project: If the user can’t use it, it doesn’t work: Development of an Interactive System using the Human-Centered Design Approach - Master´s level ............................................. 108

94. Project: User-Centered Design of Autonomous Shuttle Buses for Use in Public Transport - Master´s level ........................................................................................................... 109

95. Probability and Statistics ....................................................................................................... 110

96. Qualitative UX Design Research & Methods ..................................................................... 111


97. Rechnernetze (Computer Networks) .................................................................................. 113

98. Selected Topics in Digitalization .......................................................................................... 114

9. Research Methods in HCI (Master´s level) .......................................................................... 115

100. Selected Topics in Physics ................................................................................................. 116

101. Selected Topics in International Management ................................................................ 117

102. Sensor Technology and Signal Processing – Master´s level ........................................ 118

103. Smart Mobility: Trends in Intelligent and Sustainable Mobility Systems ..................... 119

104. Software Development ........................................................................................................ 120

105. Special Topics in Financial Modelling ............................................................................... 121

106. Statics .................................................................................................................................... 122

107. Statistics ................................................................................................................................ 123

108. Strategic Management ........................................................................................................ 124

109. Strategic Foresight and Trend Analysis ........................................................................... 125

110. Studiendesign und Durchführung von UX-Tests ............................................................ 126

111. Symbolic AI: Knowledge Representation and Reasoning ............................................. 127

112. System Analysis and Control – Master´s level (RES) .................................................... 128

113. Systems Engineering .......................................................................................................... 129

114. Technology Design and Evaluation .................................................................................. 130

115. Technology Development & Innovation Management ................................................... 131

116. Testing and Simulation Methodes for Vehicle Safety Systems (Master´s level) ........ 132

117. User Experience Design Strategy ..................................................................................... 133

118. User Experience Participatory Design - Master´s level ................................................. 135

119. Vehicle Crash Mechanics and Biomechanics – Master´s level (IAE) .......................... 137

120. Vehicle Dynamics – Master´s level (IAE) ......................................................................... 138

121. Wind Power........................................................................................................................... 139

122. Wissensmodellierung und maschinelles Lernen ............................................................. 140


1. Advanced Manufacturing Technologies - Master´s level (APE)

Language English Content Advanced Manufacturing Technologies e.g.:

• Additive Manufacturing • Laser Technologies • Technologies for Battery production • Manufacturing Technologies to support light weight design with

the focus in carbon fibre plastics

Objectives The students get to: • Typical industry application • Advantages and disadvantages • Process know how und physical functioning • Trends in the industry

Teaching methods

tbd

Recommended prerequesite for attendance

none

Type of examination

tbd

Media Students: Lecture notes Lecturer(s): Blackboard or whiteboard, LCD-projector, Tablet-PC, OHP

Recommended literature

tbd


2. Advanced Methods of Software Engineering

Language English Content • Foundations: Propositional logic, predicate logic (first-order logic),

second-order logic, Hoare logic, temporal logics (e.g. LTL, CTL), selected topics of graph theory, Kripke structure, Davis-Putnam-Logemann-Loveland algorithm, Nelson-Oppen algorithm

• Artifact traceability throughout the development process • Architecture specification, composition, and refinement • Design-by-contract: E.g. Java Modelling Language (JML) • Software test (e.g. test cases, test coverage) and test tools (e.g.

JUnit) • Software verification (e.g. software model checking) and software

model checking tools (e.g. nuSMV)

Objectives The objective of this course is to provide students with a deeper understanding of the different phases of software development and how they are seamlessly linked. In addition, the course focuses on understanding and applying advanced software engineering methods in general and formal methods in particular throughout the development process.

On successful completion of the course, students will be able to:

• understand the role of formal methods during software development,

• understand and apply formal methods at different stages of software development,

• create formal software models and property specifications, • apply state-of-the-art tools for software test and software

verification.

Teaching methods

tbd.


3. Agile Project Management (Master´s level) Language English Content • Foundations: agile mindset, project stages, breaking down

complex tasks, prioritization, building project teams, avoiding common mistakes.

• Scrum: getting started, team structure, sprints, metrices for tracking progress, anti-patterns, daily stand-ups, retro perspectives, scrum masters.

• Kanban: getting started, cross-functional teams, kanban boards, differences to scrum, time management, leadership, practical examples, typical pitfalls.

• Agility & UX: Target customers, customer needs, product strategy, MVP prototype, testing MVPs, rapid iterations, product-market fit.

• Application: running self-organizing teams, managing stakeholders, feedback culture, continuous improvement, team collaboration, multi-team projects, cross location projects.

Objectives On successful completion of the course, students will be able to

- understand and explain the most important methods currently use for agile project management,

- apply agile project management methods in corporate, start-up and scientific environments,

- manage complex projects by the consistently focusing on generating customer value

- use kanban and scrum methodologies in order to catalyze cultural change and deliver better business agility.

- The teaching concept of this course closely connects theoretical foundations and practical applications. Thus, this course is designed workshop-like: The learning contents are presented in relation to concrete areas of application and are deepened by concrete group and single tasks. An active participation of the students is explicitly desired.

- Teaching methods

tbd


4. Aircraft Repair

Language English Content • Basic principles of aircraft repair

• Typical kinds of damage of different aircraft components • Methods of repair for different aircraft components • Documentation from manufacturers and users (AMM, CMM, SRM) • Legal rules and requirements • Mandatory documentation for repair of aircraft (components)

Objectives The students… • know and understand specific technical wording • know relevant legal rules and procedures • know standard inspection and diagnose techniques • are able to examine damage • know standard procedures for repair and their application • are able to develop working instructions for repair and plan their

execution • understand basic requirements for safety and economics

Teaching methods

Seminaristic instruction

Recommended prerequesite

Type of examination

Written exam (90 minutes)

Media students: lecture notes, moodle lecturer: LCD-projector, blackboard, moodle; tablet


• ARMSTRONG, Keith B., Richard T. BARRETT and William F. COLE, 2005. Care and repair of advanced composites. S. edition. Warrendale, Pa.: SAE International. ISBN 0-7680-1062-4, 978-0-7680-1062-6

• FEDERAL AVIATION ADMINISTRATION (FAA, 2009. Aircraft Inspection and Repair: Acceptable Methods, Techniques and Practices.

• Current technical publications.


5. AI Technologies for Knowledge Representation an Reasoning

Language English Content • Basic classification of AI technologies and differentiation between

symbolic AI and numeric approaches • such as Machine Learning • Graph‐based knowledge representation using the Resource

Description Framework (RDF) • Querying and modifying RDF graphs using the SPARQL query

language • Axiomatic knowledge representation using the Web Ontology

Language (OWL) • Practical knowledge modelling using Ontology Design Patterns • Ontology reuse and integration • Utilization of automatic reasoning to infer implicit knowledge,

including efficiency considerations

Objectives • Application areas and limitations of symbolic AI

• Overview of technologies and formalisms for knowledge representation and reasoning

• Proper use of graph‐based and axiomatic knowledge representation formalisms

• Understanding and proper use of automated reasoning, its computational issues, and its relation to human intuition

• Hands‐on experience in knowledge modelling and querying, including the use of modelling patterns,knowledge base reuse and integration

Teaching methods

tbd.


6. Algorithms and Data Structures

Language English Content • Complexity and efficiency

• Lists and sequences • Graphs and relations • Trees and hierarchies • Hash maps • Sorting algorithms • Selected applications

Objectives After successfully completing the module, students shall be able to

• analyze given algorithms concerning their timing behaviour and memory consumption.

• name the most important data structures and characterize their dominant advantages and disadvantages.

• choose suited data structures for practical problems. • distinguish aspects relevant for implementation of algorithms and

data structures and describe their impact.

Teaching methods

tbd.


7. Artificial Intelligence and Machine Learning

Language English Content • Introduction to Artificial Intelligence

• Basic of algorithms: sorting, tree searching, dynamic programming. Pros and cons at scale

• Supervised neural computation • Biological neurons vs. artificial neurons. Learning in artificial

neurons. From single neurons to neural networks. Learning in neural networks

• Unsupervised neural computation • Introduction to unsupervised learning. Radial Basis Functions.

Vector Quantization. Kohonen’s Self-Organizing-Maps. Hopfield Networks

• Deep Neural Learning • Fundamentals of Deep Networks. Common Architectural Principals

of Deep Networks. Building Blocks of Deep Networks. Major Architectures of Deep Networks

• Technical implementations of neural computation • Focus on models of: Recurrent networks, Time-series prediction,

Support Vector Machines, Liquid State Machines • Reinforcement Learning • Introduction to Reinforcement Learning. Q-Learning Algorithms. • Evolutionary programming • Introduction to evolutionary computing. Genetic Algorithms • Fuzzy Inference Systems • Introduction to Fuzzy Logic. Fuzzy control systems. • Online distributed streaming machine learning • Machine Learning in Real-Time Big Data Analytics. Vertical

Hoeffding Tree Classifiers. Adaptive Model Rules. Regressors. Bagging and Boosting. Distributed Stream Clustering

• For the practical part, the focus will be on designing intelligent software modules for big data analytics, sensory information processing and real-time control of engineered systems

Objectives At the end of the module, students will be able to apply modern methods of artificial intelligence in general and to analyze specifically applications in the area of big data analytics and real-time control for technical systems.

Teaching methods

tbd


none

Type of examination



8. Audio/Video Processing and 3D-Animation - Master´s level

Language English Content

Rendering: Rendering pipeline, Texture analysis, Shader (CPU & GPU), image based and procedural textures. Video processing: Digital image recording, (digital) cameras, RAW workflow, HDR, Lightfield, Highspeed cameras, image processing, color science, standards. Audio processing: Audio recording, audio reproduction, microphones, digital audio recorders, binaural technologies, media formats, codecs, audio broadcast, standards. 3D animation: Lighting, animation, motion graphics, rule-based animation, dynamics, photo-realistic visualization, camera matchmoving, image compositing, stereoscopic visualization.

Objectives On successful completion of the course, students will be able to understand the basic principles of different audio-visual media technologies, apply appropriate audio-visual media solutions for solving concrete practical problems, design and develop 3D-animations and integrate them in interactive systems, develop and evaluate new combinations of audio-visual media solutions, evaluate techniques for image recording, image recognition, audio recording and audio reproduction in a qualitative and quantitative manner.

Teaching methods

tbd

Type of examination



9. Augmented and Virtual Reality Applications - Master´s level

Language English Content This course covers fundamentals and state-of-the-art in virtual and

augmented reality, as well as related areas of 3D computer vision and graphics. Theoretical background as well as practical solutions and applications will be presented in the lectures. AR/VR topics covered in the course range from applications to Gaming, Entertainment, Education, Healthcare, Architecture, Engineering and Construction, Shopping, or Telepresence. In the accompanied practical and based on the principle of problem-based learning, students will be asked to design an own project (individual or groups) from idea, via implementation, testing, evaluation, demonstration, to documentation. In this way they will experience the full lifecycle of a practical project in AR/VR, as they will face it once they leave the university in either industry or research. A default project will be suggested as fall back, still covering the full lifecycle except the idea.

Objectives In this module, students will be equipped with the theoretical and practical knowledge to enable them to participate in the design and development of AR/VR technology as well as providing transferable skills relevant in the wider area of interactive entertainment. This is an interdisciplinary course combining technical skills with an understanding of the psychology of VR/AR and the creativity need to develop novel experiences. On successful completion of this module, students will have the ability to review and asses the state-of-the-art in AR and VR technologies and use this knowledge to select appropriate technologies for a project, the skills to critically evaluate current research and practice in virtual and mixed reality, an interdisciplinary understanding of VR and AR encompassing psychology, technology and creative practice, technical development skills that enable a personal VR and AR creation practice, the expertise to critically assess AR/VR experiences in different creative contexts (e.g., gaming, education, healthcare, shopping or telepresence), developed an AR/VR solution including implementation, testing, evaluation, demonstration, and documentation based on own ideas (in the practical).

Teaching methods

tbd


10. Ausgewählte Kapitel der Digitalisierung - Master´s level (APE)

Language English Content Industrie 4.0 (Bernhard Axmann)

Motivation zur Digitalisierung und Einordnung von Industrie 4.0 in den historischen Kontext Übersicht zu Software-Anwendungen und deren Vernetzung im Industriebetrieb (Entwicklungs- und Produktionsbetrieb) Herausforderungen (warum sind viele Softwareprojekte im Industriebetrieb nicht erfolgreich) Lösungsansätze Digitale Transformation (Cornelia Zehbold) Disruptive Technologien Treiber der Digitalisierung Dimensionen der Digitalisierung im Überblick: Geschäftsmodelle, Prozesse, Produkte, Vernetzung von Produkten mit der Umwelt, Mensch-Maschine-Schnittstelle Digitale Geschäftsmodelle und Wertschöpfungsnetzwerke Digitale Geschäftsprozesse

Objectives • Die Studierenden • verstehen die Aufgaben der Digitalisierungen der Fabrik, die sich

ergebenen Herausforderungen und möglichen Lösungsansätze bei Industrie 4.,

• vertiefen dabei Kenntnisse im Datenmanagement, Softwareschnittstellen und der Optimierung der Organisation,

• lernen die Treiber der Digitalisierung ebenso wie die typischen Phasen der Digitalisierung, von der Digitalisierung bestehender Prozesse bis hin zu neuen digitalen Geschäftsmodellen und Ökosystemen (Wertschöpfungsnetzwerken) an Beispielen kennen,

• erhalten Einblicke in mögliche Auswirkungen der Digitalisierung in der Gesellschaft

• arbeiten in Übungsteilen mit aktueller Software • sind in der Lage, sich selbstständig unter Anwendung einer

systematischen Herangehensweise in konkrete Problemstellungen aus dem Bereich Digitalisierung einzuarbeiten, diese zu analysieren und Lösungsalternativen aufzuzeigen.

• üben das zielgerichtete Arbeiten und die digitale Kollaboration in Teams

•


11. Automation and Equipment Technologies – Master´s level (APE)

Language English Content • robotics, automation and control technology in automotive

manufacturing • equipment manufacturing: system manufacturing, tool and mould

making, tool machines Objectives The students …

• get to know the fields of application of automation technologies in automotive production including suppliers. They can determine suitable application-oriented levels of automation (economic and technological)

• know the structure and individual components of automation systems and their interaction in automotive production (amongst others, steerings, software, clamping systems, robots, transport technology, systems, factory …)

• can derive and assess interactions between automation technology and manufacturing technology/processes, product design, production design, productivity/availability etc.

• can interpret robot systems in particular (single robot, robotic cells and gardens) mathematically and with planning (possibly do it themselves and programme using exercises/practical exercises in the lab)

• know the planning and development processes of automation systems and equipment in automotive production (e.g. robot offline programming, accessibility simulations, virtual commissioning, tooling methods planning, forming simulation etc.) and their involvement in product/production development processes

• know the involvement, processes and technology of equipment manu-facture for the development, construction and production of tools and systems

• learn the methods for the construction, commissioning and quality optimisation of systems and tools in conjunction with the production start-up processes

• get to know the tool machines used in automotive production and can assess these both technologically and economically (e.g. for procure-ment processes)

Teaching methods

lecture


12. Automation Technologies

Language English Content • basics of industrial process and control

• sensors and actuators • automation controller • programming of automation controllers (with exercise) • operation and monitoring • industrial communication • development of automation systems

Objectives The students ... • have a basic understanding of automation technology • recognise automation potential and the demand for automation • have a basic understanding of information and communication

technology in automation systems Teaching methods

Lecture and practical exercises

Prerequesite for attendance

none

Type of examination



• Karl-Heinz John: IEC 61131-3: Programming Industrial Automation Systems: Concepts and Programming Languages, Requirements for Pro-gramming Systems, Decision-Making Aids

• Terry L.M. Bartelt: Industrial Automated Systems: Instrumentation and Motion Control

• Frank Lamb: Industrial Automation: Hands On


13. Automotive Communication Systems (Master´s level)

Language English Content • Introduction to

• OSI layer model, Communication Interfaces to Embedded Operating Systems

• network descriptive structures, network functionality, network technologies

• protocols • Characteristics and discussion of current bus systems • LIN, CAN, Flexray, MOST • Ethernet • Wireless Networks WLAN • Methods to analyze the bus communication • Mechanisms to secure the data connection • High Level network protocols for diagnostics KWP2000 and

ISO14229

Objectives After successfully completing the module, the students

know systems and procedures to distribute information in between the vehicle systems. know wired and wireless bus systems and their characteristics. are able to analyze requirements for the vehicle onbord and offboard communication and to specify a communication concept fulfilling the requirements. are able to understand complex communication problems and to solve those problems choosing the most critical information, logical reasoning and raising the appropriate questions. are able to develop own ideas and are able to apply scientific concepts to solve applied development tasks.

- Teaching methods

tbd


none

Type of examination

tbd

Media Lab demonstration and practical demonstration of diagnostics

whiteboard, projector, demonstrations


14. Automotive Control Engineering – Master´s level (IAE)

Language English Content • Repetition of classical control engineering methods

• State space representation of linear time invariant systems • Analysis of system properties (dynamics, stability, controllability,

observability) in state space • Design of state feedback and feedforward control (pole placement,

modal control, optimal control) • Design of state observers • Representation and analysis of non-linear control systems • Lab work: Design and test of different types of control systems by

use of Matlab-Simulink Objectives After successfully completing the module students are able to …

• analyze and describe systems in time and frequency domain • select and design controllers based on classical control engineering

methods (root locus, bode diagram) • model and analyze LTI-systems in state space • design state space controllers for SISO and MIMO-systems using

different methods • design observers for LTI-systems • solve simple control tasks for non-linear systems

Teaching methods lecture and lab work Prerequesite for attendance

Good knowledge of control engineering methods.

Type of examination written exam (90 minutes) Media blackboard, overhead projector, LCD projector, PC Recommended literature

• BOLTON, William, 2010. Control engineering. 2. edition. Harlow u.a.: Prentice Hall. ISBN 978-0-582-32773-3

• BURNS, Roland S., 2001. Advanced control engineering. Oxford: Butterworth-Heinemann. ISBN 978-0-7506-5100-4, 0-7506-5100-8

• FRANKLIN, Gene F., J. David POWELL and Abbas EMAMI-NAEINI, 2015. Feedback control of dynamic systems. 7. edition. Upper Saddle River, NJ [u.a.]: Pearson. ISBN 978-1-29-206890-9, 1-29-206890-6

• DORF, Richard C. and Robert H. BISHOP, 2014. Modern control systems. 12. edition. Harlow [u.a.]: Pearson. ISBN 978-1-29202-405-9, 1-292-02405-4

• OGATA, Katsuhiko, 2010. Modern control engineering. 5. edition. Boston [u.a.]: Pearson. ISBN 978-0-13-713337-6, 0-13-713337-5


15. Automotive Electronics – Master´s level


basics of electrical and electronic engineering recapitulation of microcontroller technology control unit circuits for input and sensor signal conditioning, output drivers and controlling actuators, power supply physical layer of automotive communication networks and onboard communication introduction to automotive electric standards basics of automotive sensors and actuators basics of automotive software engineering

Objectives After successfully completing the module, the students have a knowledge of automotive electronics architectures knowledge of the architecture of automotive control units and applied integrated circuits knowledge of automotive sensor technologies kowledge of automotive actuator technologies comprehension of the functional dependencies ability to apply the knowledge to specify and design control units

Teaching methods


Type of examination

Media


•


16. Automotive Radar Systems – Master´s level (IAE)

Language English Content • Introduction

• Radar wave propagation • Radar signals and signal processing techniques, information

from radar • Detection of signals in noise • Radar clutter: sea, land and weather clutter • Radar system design considerations • Automotive radar examples

Objectives After successfully completing the module the students are able to

• describe and explain fundamentals, system aspects, digital signal processing techniques as well as hardware components of radar;

• evaluate practical design issues to assess radar parameters; • evaluate requirements for automotive radar systems; • design mini radars with the help of MATLAB scripts considering

the design boundaries; • describe vehicle applications that use radar sensors.

Teaching methods

tbd


none

Type of examination

tbd



tbd


17. Autonomous Vehicles by Machine Learning Algorithms (Master’s Level)

Language English Content Introduction

• Overview on Python, Git and Latex • State of the art and Framework of intelligent vehicles • Overview on Deep Learning

• Environment Perception and Modeling

1. Road detection and tracking 2. Vehicle detection and tracking

• Vehicle Localization and Navigation

1. An Integrated DGPS/IMU Positioning Approach 2. Vehicle Navigation Using Global Views 3. Advanced Vehicle Motion Control

Objectives After successfully completing the module the students are able to

• understand the main state-of-the-art signal processing and machine learning algorithms applied to autonomous vehicles

• to implement these algorithms in Python • to suggest simply modifications in these algorithms.

Teaching methods

tbd.


18. Basics of Mechanical Design

Language English Content • basic steps of product development

• Specifications • Abstraction • Functional structures • Solution finding and solution approaches (morphological matrix) • Draft design (also in CATIA) • Detailed design (also in CATIA) • Basic machine part

Objectives The students

• have fundamental knowledge about systematic approaches for product developments

• have an overview over relations between development and design and other functions in companies

• are enabled to do challenging product developments by making use of systematic approaches and ade-

• quate processes • have a fundamental understanding of the need for communication in

product development • are enabled to be a member of a product development team • know to make use of CATIA V5 (part design, assembly design,

drawings)


19. Business Administration

Language English Content • The subject of business administration and differentiation from

economics • Overview of the economics subject • Setup of a company: factors of production (management, labour,

means of production, raw material), further differentiation of management activities (leadership, planning, decision making, organization, monitoring)

• Setup of a company: legal form, alliances & partnering, choice of industrial location

• Human resource management: planning, recruiting, personnel layoff, personnel deployment, development, leadership

• Production: production processes, costing theory, procurement (overview)

• Marketing: market research, marketing mix (overview) • Investment calculus: static and dynamic methods • Financing (overview)

Objectives The students … • understand (on a high level) the various disciplines of business

administration including the respective decision needs • learn how to judge situations using a “business logic” and specifically

how to evaluate projects or investments • develop a basis for subsequent management subjects included in the

curriculum (accunting, controlling, marketing) • learn about selected practical business topics, which are not covered

in subsequent subjects of the curriculum, including the setup of a company and human resource management

Format lecture Prerequesite for attendance

none

Type of examination



20. Business Information Systems


The importance of information systems IT infrastructures and web technologies Databases and information management Operational information processing (ERP, SCM, CRM, etc.) E-procurement and e-commerce Business process management IT-enabled knowledge management Software engineering IT-enabled decision making E-Society and political/legal aspects of information systems Applications and case studies: information systems in business practice Digitization of the economy and society

Objectives Note: A detailed breakdown of the workload (total 125 h) will be given in the first exercise. The exercises include web-based training. The module “Business Information Systems” provides students with contents and challenges of Business Informatics and gives insights into current developments in business practice. Students can assess contents, objectives, and challenges of information systems in the business world (focus is on the design, implementation, management, and control of information and communication technology [ICT] as well as on the management of interfaces between systems and companies) are able to distinguish between different types of information and communication systems, earn in-depth knowledge about requirements for the effective and efficient use of ICT as well as about the importance of information systems for company success in the context of the increasing digitalization of the economy and society, are able to solve business problems in the field of information systems by applying systematic approaches and by identifying alternative solutions in teams.

Teaching methods

exercises


21. CAx Techniques in Automotive Engineering (Master´s level)

Language English Content • Overview of CAx workflow in context of modern PLM (Product

lifecycle management) in the automotive industry • Simulation driven design and CAD integrated simulation:

approach, workflow, advantage, challenges • Basics of associative and parametric CAD design • Outline of the basic concept of FEM

o Differential equation and boundary conditions o Introduction in FEM, FDM,FVM, o The principle of virtual work; Typical Finite Elements o Steps of a Finite Element Analysis (FEA), classification

of FE solver • Finite Element formulation for structural analysis

o Stiffness matrix o Linear and nonlinear analysis, modal analysis, dynamic

analysis, crash test • Thermal analysis: heat transfer and thermal boundary condition • Basics of computational fluid dynamics

Objectives After successfully completing the module students have the following

expertise: Understanding of simulation driven design and virtual prototyping in the context of Computer Aided X (X=Design, Engineering, Manufacturing, Quality, ...) Ability to realize hands-on basic parametric CAD design and configuration management to be able to run CAD integrated FEA (finite element analysis) Ability to apply FEA to engineering problems, especially to stress, modal, thermo-mechanical and thermal analysis Ability to solve problems in this field, e.g. verification, validation and calibration of FE models Ability to formulate simulation tasks, run FE simulation, document and report results

Teaching methods

tbd


22. Computer Science

Language English Content • Binary Numbers and Logic

• Computer Architecture • Operating Systems • Programs and Programming Languages • Algorithms, Data Structures, and Programming • Computer Networking • Security • Digital Media: text, images, audio, video, compression

Objectives The students develop a practical understanding of the broad and dy-namic computer science field. They are familiar with the basic principles of data processing and master the safe handling of basic terms and key concepts of computing and computer systems.


none

Type of examination


Media Students: Lecture notes, moodle Lecturer(s): Blackboard, Beamer projections, PC demonstrations, Lecture script, moodle


To be determined


23. Context and Conceptualisation in UX

Language English Content Objectives


24. Controlling

Language English Content • Definition of most important terms

• Concepts and functions of controlling as well as institutional organization of controlling

• Process of planning, control and provision of information • Strategic controlling: tools and methods for analysis and planning • Budgeting: Different methods of budgeting, evaluation of classical

and modern approaches to budgeting • Case study: budgeting • Ratios: Different ratios and ratio systems, value based ratios • Transfer pricing: meaning and calculation based on market prices,

cost or bargaining processes • Creation and presentation rules for controlling reports, visual

presenta-tion of key ratios • Responsibility accounting for selected functions

Objectives The students … • can define the term controlling and describe most important

functions • understand advantages and disadvantage of different types of

institu-tional organisation of controlling • understand the tools of strategic controlling, their differences and

simi-larities and can apply them to cases accordingly • know the different budgeting methods and can apply them to cases • understand the meaning of different ratios and can apply them, • understand the difference between value based and profitability

ratios and can explain them based on the example of the ratio EVA • can explain the advantages and disadvantages of different

methods for the determination of transfer prices and can apply these methods

• understand the rules for preparing controlling reports and can prepare visualisation of key ratios

• understand the functions of responsibility accounting in selected areas and can apply the respective specific key ratio

Teaching methods

lecture


25. Cost Accounting

Language English Content • Full cost accounting: cost unit period accounting, standard cost

accounting • Direct costing: cost unit period accounting, standard direct cost

accounting • 2 case studies: Full cost and direct cost accounting • Investment appraisal, static and dynamic investment appraisal • Financing: internal and external financing sources, liquidity

planning • Cost management: background, current cost drivers and required

actions • Product costing: profitability, product life cycle, influences on

product costs • Product development: importance and calculation of development

cost, target costing, value analysis • Analysis of fixed cost, activity-based costing, complexity costs

Objectives The students … • understand the concepts of cost unit accounting and operating

statement calculations as well as the difference between cost-of-sales and total expenditure accounting and can apply these methods

• understand the methods of direct cost accounting and can apply them

• can explain advantages and disadvantage of full costing and direct costing and make judgements in applying both approaches to cases

• can evaluate cases by using different methods of direct and marginal costing as well as break even analysis

• understand phases of the investment process • understand advantages and disadvantages of static and dynamic

invest-ment appraisal methods and can apply them to cases Module Handbook B.Eng. Engineering and Management as of 01.10.2015 page 29

• are aware of the different methods for internal and external financing as well as the targets and methods of liquidity planning

• understand targets and importance of cost management • know methods on how to influence product, project, fixed and

complexity costs • can apply the most common method to cost controlling in cases


Business administration, Financial accounting

Type of examination



26. Cost Engineering and Risk Management

Language English Content • Grundkenntnisse E-Technik

• Passive Bauelemente (R,L,C), Aktive Bauelemente (Dioden, Transitoren, Operationsverstärker)

• Aufbau Leiterplatten, Workshops zu technischen und kommerziellen Fragestellungen

• Aufbau und Kostentreiber von Displays, SMT Technologie • Value Engineering (Konzeptwertanalysen bis zu Produktkalkulation

Zero Base, Best Practice, Optimierung) Objectives Die Studenten …

• verstehen den Aufbau und Funktion ele. Bauelemente • können das Zusammenspiel der Bauelemente auf

Schaltungsträgern nachvollziehen. Können Aussagen zu Kostentreiben machen.

• lernen einfache Schaltungen kennen/Grundzüge Schaltpläne • lernen Methoden und Aufgaben des Value Engineering kennen • fokussieren auf die Fertigungstechnologie von ele. Baugruppen

(Schwerpunkt SMT, Leiterplatten, Displays) Teaching methods

tbd


27. Cryptology

Language English Content • basic knowledge from computational number theory such as

implementing the Euclidean algorithm or the square and multiply algorithm

• algebraic structures related to cryptographic methods (finite fields, elliptic curves) and related mathematical questions (such as the discrete logarithm problem)

• public-key encryption and digital signatures • zero-knowledge protocols • symmetric-key encryption methods (such as shift registers,

pseudo random numbers, DES, IDEA, AES, etc.)

Objectives After successfully completing this course, the student will be able to • state the goals of cryptography. • describe common encryption methods und illustrate these

methods using concrete examples. • discuss strengths and weaknesses of the different encryption

methods. • identify methods that are suitable for a given situation. • explain the mathematical background of specific coding and

decoding procedures. • describe and illustrate algorithms (for example for generating

prime numbers or solving the discrete logarithm problem) using specific numerical examples

Teaching methods

tbd


none

Type of examination

tbd


28. Designing Interactive Products

Language English Content • Die Projekt-Arbeiten kreisen dabei primär um die Themen

"Intelligente Produkte“, „Internet of Things", "Emotionalisierung", "Interaktion", "Veränderung", usw.

• Im Projekt wird dabei die Prozesskette „Analyse - Ideation - Observation - Prototyping & Optimierung in Iterationsschleifen („Rapid Prototyping“) so abgebildet, dass der Ablauf stark an den „Designthinking“-Prozess erinnert.

• Das Experimentieren und das Lernen aus Fehlern („fail early - fail often“) und das iterative Optimieren von Lösungen stehen hier also im Vordergrund.

• Hilfsmittel zur Umsetzung der Ideen und Konzepte sind Arduino (mit den entsprechenden Sensoren und Aktuatoren) und aktuelle „Rapid Prototyping“- Verfahren. Die Studierenden bekommen die Möglichkeit die Kenntnisse in diesen Bereichen zu vertiefen und eigene Ideen umzusetzen.

• Der Schwerpunkt des Moduls ist, aufbauend auf dem Produktdesign, das Arbeiten an dreidimensionalen Objekten und Produkten. Der Fokus liegt hier auf Objekten, die agieren und interagieren können, und deshalb mit einem Arduino-Mikrocontrollerboard, Sensoren und Aktuatoren ausgestattet sind. Die konkreten Projektthemen werden zu Beginn des Semester in einem vom Design-Thinking abgeleiteten Prozess entwickelt.

• Im Rahmen des Moduls besteht im SS 2019 u.a. die Möglichkeit, an der "In-Car Gaming Challenge" initiiert von "Pioneering. by Daimler" teilzunehmen. Hier ist es das Ziel, neue Ideen & Prototypen aus dem Bereich "Gaming Experience" für das Auto der Zukunft zu entwerfen.

Objectives Die Schwerpunkte dieses Faches liegen in der Entwicklung von

Kenntnissen und Kompetenzen in den Bereichen:

• CAD (Autodesk Fusion 360), Physical-Computing (Arduino), Rapid Prototyping

• Recherche/Analyse, Anwendung von Designprozessabläufen und von Gestaltungsmethoden, „User centered design“-Prozess

• Präsentation, Teamfähigkeit und soziale und interkulturelle Kompetenz

Ziele sind die Vertiefung und Zusammenführung der bisherigen Erkenntnisse und Erfahrungen aus dem Pflichtmodul "Produktdesign" mit den Bereichen rund um das Thema "Physical-Computing" und die Optimierung dieses Zusammenspiels und die Erweiterung mit dem Thema "Rapid Prototyping".

- Teaching methods

tbd


29. Designing Minimum Loveable Digital Products

Language English Content • Warum braucht man das? Was ist das? Definition?

• Definition: Design Minimum Loveable Products / Digtiales Produkt Design

• Grundlagen Product Discovery & Delivery: • Product Thinking: Building the right things, Building the things

right • Aufgaben, Methoden & Prozess Product Discovery • Aufgaben, Methoden & Prozess Agile Product Delivery • Wie macht man es? • Research: Erkennen von Anfroderungen/Bedürfnissen pro

Industry aus User, Tech, Business Perspektive (Quantitativ & Qualitativ)

• Synthesis & Definition: Ableitung der relevanten Informationen, Kern-Hypothesen bis hin zum Product-Solution Fit

• Feature Scoping & Concept Development: Überführen von Theorie in die Praxis

• Rapid Prototyping: Gestaltung greifbarer, validierbarer Lösungsideen erschaffen mit Tools wie inVision, Sketch oder Figma

• Guerilla User Testing: Validieren der Lösungen • Iteration & Finalisierung & Growth: Ergebnisse Rückfließen

lassen, das Produkt veröffentlichen und erweitern • Wie präsentiert man es? • Grundlagen zu Storytelling (Warum ist das so wichtig?) • Pitching der Ideen


30. Design Strategy and Management - Master´s level


Company forms and organizational principles. The role of design in terms of business success. Business-related planning of design processes. Importance of invention and innovation in an entrepreneurial context. Social-structural aspects of user groups, in particular milieu-specific forms of use-relevant interests. Coevolution of media and society. Modern public in the epoch of digitization.

Objectives On successful completion of the course, students will be able to: analyze the function-related role of the design in the overall entrepreneurial context, evaluate basic business goals, strategies and actions, develop creative problem solving considering the basic knowledge content of design management, recognize interactions between social and technical development and reflect creative innovations from a specific technical-sociological perspective,

Teaching methods

tbd

Type of examination

oral exam, 15 minutes


31. Design Thinking Digital

Language Content Design Thinking is a creative method to solve complex problems and

develop new ideas (e.g. in the context of product development, development of new business models or even in case of process changes). It is from Stanford University in Palo Alto, California. The module covers: Theory Use Cases Phases: Scoping Research Synthesis Ideation Prototyping Validation

Objectives Students learn how to better solve problems by applying design thinking and by asking for the needs of (potential) users go through all phases of this innovation method in several online workshops and they take part in group work. in doing so, they are empowered to use selected instruments for real-world tasks. are able to select and apply tools suitable for a practical problem. Special topics in the field of design thinking are given to the students as a presentation. The results are presented and the acquired understanding is questioned.

Teaching methods Script and exercises, online materials (e.g. videos), case studies, PC/Laptop/Tablet/Smartphone and software, Moodle


32. Design to Create a Sustainable Strategic Vision: At the Crossroads between Business and Design

Language English Content • Overview Design Thinking & Design Thinking Methods also

looking at related Methodologies e.g. integrative thinking, disruptive thinking, systems thinking etc.

• High level understanding about business strategy • Understanding the differences between the Business & Design

mindset • Applying design thinking to a strategic challenge on the

example of a chosen company (Patagonia/Starbucks/Uber/or your own choice

Objectives Motto of the course: "There is no Design Thinking without Design Doing!" What:

• Overview about Design Thinking (after having evaluated what the knowledge basis is) and Strategy

• The challenges & boundaries of Design Thinking implementation

• The differences between Design strategy in a corporate & a start-up environment

• Understanding about the crossroads of Design, Strategy and Design Strategy

• Digitalization and the meaning for Design Why:

• To be able to create meaningful and lasting UI/UX Products • To be able to communicate with non-designers • To be able to understand the different roles of Design in a

business context • To be able to understand why design strategy is important for

UI/UX How:

• Best practices case studies • Applying the learnings in hands-on worksessions • Discussing current articles on the topic of design strategy in

today’s industry • Developing a (design) strategy in a practical project

Teaching methods

This course will be given in 8 day sessions. These sessions will be planned as a mix of theoretical input, impulse videos, speeches & articles and each session will involve a practical worksession part in which the students can practise the theory discussed.


33. Design von Mensch-Maschine-Schnittstellen (in English!)

Language English Content Anhand einer konkreten und praxisnahen Aufgabe wird ein Design-

Entstehungsprozess durchlaufen. Dieser beinhaltet: • Ideenfindung • Skizzen (Paperprototyping) • Wireframing (Balsamiq, Axure, UXPin, Experience Design…) • Usability • Interface Design (Illustrator | Photoshop) • Animation (After Effects) • Storyboarding • Video (After Effects | Premiere Pro) • Hi- and Low Fidelity Prototyping • Dokumentation • Präsentation

Objectives Nach dem Besuch des Moduls können die Studierenden ein vorzeigbares und umfassendes Design-Projekt nachweisen, bei dem sämtliche Bereiche des UCD-Prozesses berücksichtigt und durchlaufen wurden. Schwerpunkt der Arbeit liegt neben der Konzeption und Usability vor allem im Interface Design. Die Stu-dierenden erlangen Erfahrung in der Teamarbeit und können unterschiedliche Methoden in einem Designprozess identifizieren und der Aufgabenstellung entsprechend anwenden. Durch eine abschließende Präsentation (meist mit Gästen) vertiefen die Studierenden ihre Präsentationsfähigkeiten.

Teaching methods

tbd


none

Type of examination


Media Students: Lecture notes, work sheets, case studies, lab work, presentations Lecturer: Blackboard, LCD-Projector, Tablet-PC, OHP, Video


• MOSER, Christian, 2012. User Experience Design. • STEANE, Jamie, 2014. The Principles and Processes of Interactive

Design.. • ROSENYWEIG, Eliyabeth, 2015. Successful User Experience. • STAPELKAMP, Torsten, 2010. Interaction- und Interfacedesign.

Usability und Interface als Corporate Identity. • GARRETT, Jesse James, 2012. The Elements of User Experience. • FERSTER, Bill und Ben SHNEIDERMAN , 2013. Interactive

Visualization


34. Development Methodologies for Automotive Systems (Master´s level)

Language English Content • Introduction: automotive systems

• Automotive microcontrollers: architecture, memory • Fundamentals of microcontroller programming: structure of

automotive software, memory mapping, efficient and portable programming, MISRA C programming guidelines

• Architecture of automotive software: modularity, software layers, real-time systems (tasks, scheduling), resource management (deadlocks, semaphores, priority inversion), interrupts and timers

• Software processes: V-model and MISRA development guideline, process assessment (CMMI, automotive SPICE), model-based development (Matlab/Simulink/Stateflow)

• Safety: IEC 61508 and WD 26262, safety measures (self test, redundancy, COP, diagnostics)

• AUTOSAR development process, AUTOSAR classic architecture: Virtual Function Bus, Application Components, RTE, BSW, AUTOSAR OS, Adaptive AUTOSAR

Objectives After successful completion of this module, the students

will understand the basics of the E/E development process in the Automotive Industry. will be able to develop and design software for embedded, automotive, real-time systems using AUTOSAR. will have a basic understanding of the overall software development process for automotive systems.

- Teaching methods

tbd


35. Digital Factory

Language English Content Es werden Grundlagen, vertiefte Kenntnisse und digitale

Anwendungen in der Industrie mit dem Schwerpunkt Produktion gegeben und Herausforderungen bei der Einführung und dem effizienten Betrieb von Software-Anwendungen erläutert. Historischer Einordnung der Digitalisierung in die Industrialisierung und Begriffserläuterung von Industrie 4.0 Motivation: Wieso digitale Lösungen Übersicht zu Softwarelösungen in der Fabrik (Industriebetrieb) Herausforderungen: Weshalb scheitern so viele Digitalisierungsprojekte It provides basic and advanced knowledge and digital applications in industry with a focus on production and explains challenges in the introduction and efficient operation of software applications. Historical classification of digitization in industrialization and explanation of terms used in Industry 4.0 Motivation: Why digital solutions Overview of software solutions in the factory (industrial company) Challenges: Why do so many digitization projects fail Solution approaches for the successful introduction of software/digitization projects

Objectives Nach erfolgreicher Teilnahme an der Lehrveranstaltung sind die Studierenden in der Lage: Die Historische Einordnung bei der Digitalisierung der Fabrik zu wissen Beispiele von Digitalen Lösungen (Schwerpunkt Software Lösungen) in der Fabrik zu kennen Herausforderungen bei der Einführung von Software in der Fabrik zu verstehen Erfolgreiche Vorgehensweise zur Digitalisierung der Fabrik kennen After successful participation in the course the students are able to to know the historical classification of the digitization of the factory to know examples of digital solutions (focus on software solutions) in the factory Understand the challenges of implementing software in the factory Knowing the successful approach to digitizing the factory

Teaching methods

Lecture, moodle room, videos, whiteboard, notebook



36. Digital Procurement Engineering - Master´s level

Language English Content • Software along the personnel resource planning from a

procurement perspective • Underlying theories and practical application of the presented

software • Programming • Neural networks

Objectives Students…

• get to know different IT tools along a personnel resource planning of complex products

• get to know IT methods of modern procurement • are able to use modern project data management software (PDM

or similar) and analyze relevant global procurement data (supplier market, technologies, costs...)

• are able to use modern software for contract preparation (ASTRAS + e auctions), change management, purchase order processing and administration, and model procurement processes

• are able to develop a blockchain application in the context of global SCM

• learn Python programming language and develop a simple neural network for use in modern procurement management

Teaching methods

tbd


37. Digital Technologies in Engineering – Master´s level (APE)

Language English Content • Product Life Cycle Management (PLM)

• Product Data Management (PDM) • CAx strategies • Digital factory (planning) and manufacturing (process) simulation

Objectives The students: • Can assess the considerable significance of PLM/PDM as a means of communication in the product development process. • Are familiar with the management of product and production data in the engineering process. • Know and understand models, concepts and methods of PLM/PDM • Can handle exemplary, specific PLM/PDM systems. • Get to know and understand CAx strategies (amongst others, for CAD, CAQ, CAE, CAM, DMU etc.) and their interactions on corporate processes. • Know possibilities and systems of the “digital factory“ for production and factory design, planning and development, in particular for Simultaneous Engineering, and their involvement in the product development process. • Understand the theory behind different simulation methods such as discrete event simulation, continuous simulation, FEM simulation as well as the according modelling steps • Can handle exemplary, specific systems of the digital factory (e.g. system layout, process/availability simulation, robot offline programming, system simulation, assembly and ergonomics simulation). • Know foundations (FEM methodology) and different systems of (physical) manufacturing process simulation (e.g. forming simulation, casting simulation, joining simulation, painting simulation etc.) and their fields of application as well as limits.

Teaching methods

tbd


38. Electrical Engineering

Language English Content Direct current circuits:

• voltage, current, Ohm’s law, energy, power, Kirchhoff´s laws, Thévenin equivalent, Norton equivalent circuit, series connection, parallel connection, maximum power transfer, calculation of networks

• Electric field • electric field quantities, capacitance, energy in the electrostatic field,

forces in the electrostatic field, switching operations • Magnetic field • magnetic field quantities, coil inductance, magnetic circuit, magnetic

flux law, magnetic energy of the coil, forces in the magnetic field, induction law, self induction, switching operations

• Alternate current circuit • sinusoidal change of electric quantities, circuit analysis of alternate

current networks, power, frequency response, transformators • Semiconductors • diode, transistor, operational amplifier, basics of electric circuits • digital circuits • Measuring electric quantities

Objectives The students … • know and use specialist terminology confidently • know the basic physical laws of electrical engineering and their

connection • know the boundary conditions of particular laws of physics • are able to select the appropriate laws defining a given problem • are proficient in calculations with appropriate units • are proficient in methods calculating direct current and alternate

current networks • know the electrical field quantities and are able to calculate them • know the magnetic field quantities and are able to calculate simple

magnetic circuits • know simple circuits with a transistor • know basic circuits with an operation amplifier and are able to

calculate those • know measuring instruments for electric quantities and know their

possible uses • are able to familiarise themselves with subjects regarding electrical

engineering self-reliantly and within a team and are able to discuss these matters competently


Calculus, linear Algebra

Type of examination



• Hambley, Electrical Engineering, Pearson • Hagmann, Gert: Grundlagen der Elektrotechnik, Aula-Verlag • Bird, John: Electrical and Electronic Principles and Technology • Maxfield, Bird, Laugthon, Bolton, Leven, Schmitt, Sueker : Electrical En-gineering, know it all, Elsevier


39. Electronics, Signals and Measurement

Language English Content • Introduction to Signals

• Fourier Transform and Fourier Series • Sampling, and Aliasing • Kirchhoff’s Laws, Resistor Networks, Resistive Circuit Analysis • Circuit Analysis using the Node and Mesh Methods, Linear Circuits

Analysis • Equivalent Circuits, Power Transfer • Dependent Sources, Op Amps, Current Sources • Capacitors and Inductors • Sinusoidal Steady State Response of RL and RC Circuits • Sinusoidal Steady State Response: Impedance • Filters, Bandwidth, Q Factor • Transient Response • Diodes, Signal Conditioning, Voltage Regulation • Transistors, Biasing and Amplification • Introduction to the Op Amp

Objectives The course is designed to provide a practical - hands on - introduction to electronics with a focus on measurement and signals. The prerequisites are basic math courses including differential and integral calculus as well as electricity and magnetism.

No prior experience with electronics is necessary. The aim of the course is to provide students with the theoretical and practical knowledge necessary to work in a modern science or engineering setting. The students will get the ability for basic electronic circuit design. The students are empowered to perform electric measurement and judge the correctness and accuracy of the measurement.

The students are capable to analytically calculate and experimentally measure continuous current and time dependent voltage and current signals in electronic circuits. The student understands the time and frequency behavior of signals and the concept of time-frequency dualism.

Teaching methods

tbd.


40. Energy Policies and Economies – Master´s level (RES)

Language English Content • Energy and climate change

• • Climate protection policies worldwide, in Germany and other selected countries • Energy legislation in Germany and other selected countries • Renewable energies as economic factor • Energy economy / industry in Germany and other selected countries

Objectives The students

• understand climate protection policies worldwide and their relation to energy issues

• are able to critically reflect on and discuss issues of climate change and energy

• understand different shaping of energy legislation in selected countries

• are able to critically reflect on and discuss issues of energy legislation

• understand renewable energies as an economic factor • understand the energy economy in selected countries • are able to critically reflect on and discuss issues of the energy

economy

Teaching methods

tbd


none

Type of examination

tbd



tbd


41. Engineering Mechanics

Language English Content • Introduction to the basics of statics (bars, beams, plates, etc.,

bearings and hinges, equilibrium conditions) • Central and common force systems • Determinacy • Internal force variable • Balance points • Definition of stresses and strains, deformation, stress state, Mohr’s

circle • Linear elastic material law, elasticity theory • Combined loading • Strength analysis • Buckling • Notch effects • Extensive examples and exercises for a competent application to

engineering tasks Objectives The students …

• get knowledge in the effects of forces and moments • are able to get to the root of static problems • use equilibrium equations • determine competent outer and inner load reactions • solve friction problems • estimate stresses, strains and deformations of bars and beams • get insight in the theory of elasticity • transfer there knowledge to the analytical strength assessment of

com-ponents in mechanical engineering Recommended prerequesite

Mathematics 1&2

Type of examination



42. Engineering Processes in Automotive Industry – Master´s level (APE)

Language English Content • Product development and quality management (during the product

de-velopment process) in the automotive industry • Project and process management in the product development

process • Prototype, pilot production and release processes

Objectives The students … • get to know the strongly networked and parallel processes in the

product development of automobiles (“product process“ and “product development process“)

• can recognise, assess and include in their work interactions between production and product in particular.

• know the significance and working methods of Simultaneous Engineering (SE) including the involvement of suppliers in product design and product and process quality to meet the requirements of production.

• can handle tools of project and process management (e.g. master prod-uct processes with structured levels of action in terms of decisions and themes, milestone definitions and synchronisation, levels of product ma-turity, EHPV, 3Ps „Production Preparation Process“, etc.) and know the working methods and processes, for example, for networking, decision-supplier companies

• know the significance of prototype, pilot production and release processes, their tools (e.g. Meisterbock processes, audit scores, process ca-pability evidence, VFF, PVS, etc.) as well as their involvement in the product and engineering process

Teaching methods



Fundamental knowledge of product development processes as well as development and construction methodology.

Type of examination


Media students: lecture notes lecturer: LCD-projector, blackboard or whiteboard, Tablet-PC, OHP


To be determined


43. Exercises in Programming for Multimodal and Interactive Systems (Master´s level)






• Der Schwerpunkt des Moduls ist, aufbauend auf dem Produktdesign, das Arbeiten an dreidimensionalen Objekten und Produkten. Der Fokus liegt hier auf Objekten, die agieren und interagieren können, und deshalb mit einem Arduino-Mikrocontrollerboard, Sensoren und Aktuatoren ausgestattet sind. Die konkreten Projektthemen werden zu Beginn des Semesters in einem vom Design-Thinking abgeleiteten Prozess entwickelt.


Objectives Die Schwerpunkte dieses Faches liegen in der Entwicklung von Kenntnissen und Kompetenzen in den Bereichen:





Teaching methods

tbd


44. Financial Accounting

Language English Content • Basic principles of accounting

• German and internal accounting standards • Profit and loss accounts and appropriation of profits • Cash flow statements • Annual financial statements • Case study: Founding and closing of a firm over six periods,

preparation of balance sheet, profit and loss accounts and cash flow statements for each period

• Basic principles of book-keeping • Specific balance sheet items and accounting and valuation principles • Basic principles of cost and performance accounting • Introduction to full costing

Objectives The students … • gain an understanding of the theoretical background in regard to

accounting, balance sheets, profit and loss statements, cash flow statements and annual finacial statements

• gain a basic understanding of the differences between German and international accounting standards

• can based on an opening balance sheet and given transactions prepare a closing balance sheet, a profit and loss and a cash flow statement

• are able to perform bookings and prepare accounting records by using t-accounts

• understand the basic theory of cost and performance accounting • are able to perform respective calculations such as cost cost

distribution • can perform product costing by using different calculation methods


Business Administration

Type of examination


Media Students: Lecture notes, moodle Lecturer(s): Blackboard, LCD-projector, Tablet-PC, moodle


To be determined


45. Financing and Company valuation

Language English Content Objectives Recommended literature

To be determined


46. Foundations of Computer Science


Representation of information in computer systems Basic concepts of computer architecture, basic structure of universal computers, basic principles of program execution Instruction set architecture: instruction set, addressing modes, interrupts Basics of machine-oriented programming: memory planning, control structures, subprograms Concepts of modern computer systems: pipelining, superscalarity, memory hierarchy, cache memory, SIMD-processors, GPUs

Objectives - After successful participation in the module courses, students are able to - - present information of different kinds for processing by digital

computers - identify the elements of an instruction set architecture and assess their

implications for programming, based on the representation of information in a manner appropriate to data processing and the principles of instruction-based execution of processing rules

- explain the interaction of hardware and software - formulate basic elements of procedural programming in a machine

language - evaluate the effect of programming alternatives on the execution speed - explain concepts for performance enhancement in modern processors

and the problems associated with them


47. Foundations of Engineering Sciences

Language English Content • Physical properties

• Mechanics • Reonances and waves • deflection and interference • Ideal Gas Law • basic electrodynamics and electrics

Objectives After successful participation the students should be able to:

Solve basic physical problems, validate calculations, estimate relevant input tolerances/errors and their impact on the results

determine the center of gravity of multibody-problems, apply the sentences of conservation of momentum and energy

Calculate the inertia of rotating bodies

Solve problems with help of the Ideal Gas Law

calculate damped and undamped oscillations

Analyse and calculate wave problems

Apply the fundamental equations of optics

do calculations regarding simple electrical problems

- Teaching methods

tbd


48. Industrial Energy System – Master´s level (RES)

Language English Content • Energy efficiency

• Rating of energy systems • Example project meat processing • Definition of boundaries • Applied thermodynamics for energy efficiency • Presentation and Reporting • Cross cutting technologies • Drives and pumps • Mechanical power • Lighting • Thermal Energy • Renewable Electricity Integration • Bio energy • biogas • Anaerobic fermentation • Construction of biogas plants • operating parameters and environmental conditions • substrates and manure • process and plant engineering • process variants • biogas production and storage • Solid biomass • basics of combustion • special features and design of the furnace • combustion concepts • cyclic processes • plants for electricity and heat generation an their components • basics and concepts of gasification • Project • Building an energy-efficient and environmentally friendly energy

supply for an industrial company

Objectives The students have an overview of the most important consumers of electricity, heat and gas in a typical industrial operation can establish and evaluate the different energy consumptions and efficiency improvement strategies in an industrial operation. are familiar with the biogas process, the construction of biogas plants, the most important components and process parameters and can dimension a biogas plant. are familiar with the most important procedural basics and concepts of the combustion of solid biomass and the corresponding plant technology for heat and power generation and can design a corresponding power plant. know the most important procedural basics and concepts of the thermal gasification of solid biomass and the corresponding plant technology for heat and power generation are able to project the energy supply of an industrial company with the acquired knowledge.


49. Integrated Safety and Assistance Systems (Master´s level)

Language English Content • Introduction to IS & DAS

• Examples of Driver Assistance and Integrated Vehicle Safety Systems: Parking Systems, Adaptive Cruise Control, Autonomous Emergency Braking

• Position and Orientation: Pose, Representing Pose in 2-D and in 3-D

• Time and Motion: Generation of Trajectories, Rate of Change and Inverse Problem

• Vehicle Motion Models: Decoupled X- and Y-Dynamics, Constant Velocity Model, Constant Steering Angle and Velocity Model, Constant Turn Rate and Acceleration Model, One-Track Model, Two-Track Model

• Navigation and Localization

Objectives After successfully completing the module the students are able

to explain basic vehicle components that are required for driver assistance systems and for vehicle integrated safety functions; to analyze and evaluate state of the art driver assistance systems; to describe testing procedures that are used for vehicle active safety functions; to explain mathematically the concepts for motion planning that are used in algorithms for driver assistance systems and integrated safety functions; to implement basic trajectory planning algorithms in Matlab.

- Teaching methods

tbd


none

Type of examination

tbd

Media • White board

• Projector

• Lecture notes

• Exercise sheets

• Matlab exercises in computer pool


50. International Management

Language English Content Objectives Recommended literature

To be determined


51. Intelligent Decision Systems

Language English Content • Distinction of (classical) artificial intelligence, operations

research and machine learning • The role of AI and OR in industrial applications (Industry

4.0/Industrial IoT, Smart Factory) • Intelligent decision systems: Strategic, tactical, operational • Intelligent and rational agents • Constraint programming, propagation and search • Local search, Large-neighborhood search • Linear programming and mixed integer programming • Evolutionary algorithms and reinforcement learning • Modern software frameworks and solvers: MiniZinc, Google

OR-Tools, Gecode, Chuffed, COIN CBC, LocalSolver • Integration of machine learning and predictions in decision

making

Objectives After successfully completing the module, the students are able:

to define and describe the goals of artificial intelligence (AI) and operations research (OR) with respect to software-based intelligent decision systems with a particular focus on manufacturing and logistics

to state the difference between artificial intelligence, operations research and machine learning

to mathematically explain common optimization techniques such as linear programming, mixed integer programming, constraint programming, local search, and heuristic optimization with their strengths and weaknesses

to define optimization models in a high-level modeling language (MiniZinc)

to experiment with different solving algorithms implemented in a variety of solvers and to systematically document computational experiments in a presentable manner

- Teaching methods

tbd


52. Interaction Design (Master´s level)

Language English Content • An analytic view on basic ideas and paradigms in interaction

design, different design approaches and the role of interaction design in the larger context of product development processes and digitalization.

• Discussion of existing products regarding the design concept, formal execution and social relevance.

• Familiarization with the fundamental aspects of visual, physical and sensory interactions patterns in stand-alone products, connected systems and services.

• Simple design concepts will be created emphasizing the human perspective on technology through functional and emotional qualities in the interaction design.

• Creation of experience prototypes applying different prototyping techniques in various degrees of fidelity

Objectives After successfully completing this module, students will:

- understand historical aspects, future trends, different approaches to and fundamental concepts of interaction design.

- understand basic advantages and challenges of visual, physical, and sensory dimensions in interaction design.

- have had an introduction to and practice in the fundamental methods and problem-solving strategies in design processes.

- be able to solve design problems including human centered design research, ideation, concepting, testing and prototyping.

- will be able to discuss interaction design concepts and products in regard to their functional and emotional qualities as well as their larger context within systems, digitalization and society.

- Teaching methods

tbd


53. Interface Design (Master´s level)

Language English Content • Development history of graphic surfaces and input/output

devices. • Conception, design, variant development of hardware and/or

software interfaces. • Evaluation (visual design, interaction design) as well as

prototypical realization. • Getting to know the users with their physical, motor, cognitive

and perceptual abilities. • Introduction to the use of design templates (design manuals

and style guides), design, presentation and simulation tools and their use.

• Orientation knowledge in development and realization processes.

Objectives On successful completion of the course, students will be able to:

- know basic aspects of interface design, including design and technical aspects,

- appropriate technical as well as methodical skills, - acquire knowledge about development history, conception and

design of user interfaces, - are capable of assigning potential areas of application and

designing appropriate usage and operating scenarios, - know basic methods of conception, design, linear and

interactive simulation and the prototypical realization of interfaces.

- Teaching methods

tbd


54. International Negotiation Training - Master´s level

Language English Content tbd

Objectives Students will

• understand the sensitivities of different cultures regarding the importance of negotiations in the purchasing environment

• learn about common scientific approaches to successful negotiation management (Harvard, Schranner)

• learn different methods of negotiation techniques • practice various negotiation situations in challenging

environments (technology dependency, market monopolist, oligopolies, corporations)

• can implement learned theories in negotiation strategies and deepen them in practical exercises

Teaching methods

tbd


55. Introduction to AI and Neural Networks - Master´s level

Language English Content • Distinction of (classical) artificial intelligence and machine

learning • Constraint solving and reasoning in MiniZinc as part of classical

AI • The role of AI in industrial applications (Industry 4.0/Industrial

IoT, Smart Factory) • Categories of machine learning (supervised / unsupervised /

reinforcement learning) • Linear regression, logistic regression • Artificial neural networks: Perceptrons, feedforward neural nets • Modern software frameworks and auto-differentiation: PyTorch,

TensorFlow • Training (deep) neural networks: Initialization, numerical

optimization, regularization • Deep learning architectures: Convolutional neural nets for

image processing, recurrent neural nets / LSTM for sequential data

• Reinforcement learning for process optimization • Explainability and dependable machine learning in engineering

applications

Objectives After successfully completing the module, the students have acquired

solid foundations in artificial intelligence (AI) and neural networks. In particular, they are able:

• to analyze and evaluate state of the art AI systems in automotive production

• to know the difference between artificial intelligence, machine learning and deep learning

• to mathematically explain the training procedure in deep learning systems

• to program basic machine learning algorithms in Python and NumPy

• to describe necessary steps for continuous quality assurance of learning systems

• to implement modern deep learning systems using state-of-the-art software frameworks such as TensorFlow, Keras or PyTorch

Teaching methods

tbd


56. Introduction to Computer Science 1

Language English Content Algorithms

Concept of algorithms, properties, forms of representation Computability Turing computability LOOP, WHILE, GOTO computability Church-Turing thesis Decidability, halting problem Complexity O notation Complexity classes P and NP Computer architecture Binary representation of information Natural, negative, fractional numbers Machine instructions and programs Digital circuits Logical elements, combinational circuits Storage elements, registers, counters, sequential circuits Von Neumann architecture Advanced concepts in today's computer architectures Caching Multi-core architectures Instruction pipelining Graphics processing units

Objectives The objective of this course is to develop a basic understanding of how algorithms (sequences of machine-executable computational steps) are executed on computers (program-controlled information processing systems). After successful participation, the students are able to explain the concept of an algorithm, to assess whether a problem is calculable, i.e. an algorithm can be formulated to solve it, to estimate the complexity of a given algorithm, to understand how an algorithm is processed on a computer, to describe the structure of a universal computer and how it works, to classify various advanced computer architecture concepts.


57. Introduction to Statistical Learning

Language English Content Fundaments of statistical learning

Linear Regression Classification Model assessment, selection and inference: Cross-Validation & Bootstrap Decision Trees Unsupervised Learning Overview of non-linear models: Splines, support vector machines and neural networks

Objectives Statistical learning refers to a set of tools and concepts for modeling and understanding complex data sets. It combines statistics and machine learning. Thereby it sets the fundament for a lot of data science fields like business analytics, model based machine learning and artificial intelligence. Aim of the lecture is to convey this data analytics fundaments to students to enable lifelong learning in data science and machine learning. After finishing this course including excercises students are able to Choose and calculate appropriate metrics and visualizations for describing a data set understand and master fundamental principles and modelling techniques for the analysis of regression and classification problems Have deep knowledge about model assessment and inference techniques for linear and non-linear models Use the acquired techniques in Python


58. Innovation Management Methods

Language English Content Agile management of innovation processes and projects

Creativity methods and tools for ideation and problem solving Design Thinking Open Innovation Stage-Gate-Process Marketing of innovations

Objectives The students know modern methods for the creation, management and marketing of innovations and can explain them can apply the methods learned in case studies


59. Java Based Cloud Architectures

Language English Content • fundamentals of architectures and frameworks (design

patterns, dependencies, programming based on interfaces) • aspect oriented programming (AOP) • best practices for configuration techniques (reflection,

annotations, XML) • techniques for concurrency and synchronization • dependency injection, fundamentals of the spring framwork

(spring beans, spring aspects, dependency injection, remote messaging)

• JDBC and transaction management - Java transaction API (JTA)

• hibernate (ORM, JPA annotations, relationships, inheritance)

Objectives After successful completion of this course the students are enabled to understand and apply relevant JEE software architectures and frameworks. In addition, we focus on recent techniques used in the field of Java development.

Teaching methods

Demonstrations using board, beamer, computer


60. Machine Learning

Language English Content • Basic concepts of Machine Learning

• Preprocessing • Supervised Learning

o Regression o Classification

• Unsupervised Learning • Reinforcement Learning • Evaluation and Validation • Neural Networks • Deep Learning • Frameworks and Tools • Practical applications of modern machine learning algorithms

Objectives In this learning module, algorithms and their applications are illustrated by real world examples. After successfully attending this module, students know and understand the basic principles of learning systems and their applications to real world problems. They know

• the different methods how to learn from data • the mathematical basis and the most important algorithms to train

machine learning models on their own • the different building blocks of deep neural networks and how to

apply them to solve real world problems, e.g. for computer vision or natural language processing.

• how to evaluate and validate machine learning models • the basic pitfalls and problems when training models and how to

solve them efficiently

Teaching methods

tbd.


61. Maintenance and Certification

Language English Content • Basic principles of aircraft maintenance (types, procedures, tasks)

• Legal rules and regulations • Documents of manufacturers and users (AMM, CMM, IPC, MEL) • Approaches for fault identication and analysis • Mandatory documentation for aircraft maintenance

Objectives The students… • know and understand technical wording • know and understand relevant legal rules of aircraft maintenance • know processes and standard practices of aircraft maintenance • know concepts of maintenance of modern civil aircraft • are able to plan working instructions and their execution • are able to work with specific technical documentation • understand basic requirements for safety and economics

Teaching methods

Lecture with integrated exercises


Type of examination


Media students: lecture notes, moodle lecturer: LCD-projector, blackboard, moodle; tablet



62. Mobile App Development - Master´s level


Foundations: Web development, traditional app development, challenges, best practices, progressive web apps, Popular PWAs. Technologies: Load times, push notifications, offline access, home screen shortcuts, app-like experience, browser APIs, service workers, full-screen web apps. PWA Frameworks: Angular, Cache API, Push API, Payment Request API. Web App Design: App design, native fonts, CSS. Evaluation: Evaluating App Experiences, Lighthouse.

Objectives On successful completion of the course, students will be able to • create web apps that behave just like native apps on iOS and

Android (progressive web apps), • apply the push notification approach for creating new app user

experiences, • successfully deal with new user experience opportunities and

challenges of progressive web apps, • implement the offline-first paradigm and deal with loss of

connectivity

Teaching methods

tbd


63. Kommunikationsnetze (in English!)

Language English Content • Fundamentals: Tele- and data communication networks, Internet,

protocol, service, access and core network, transmission media, performance evaluation, layer model, history

• Application Layer: Basic principles, HTTP, FTP, SMTP, DNS, P2P • Transport Layer: Services, multiplexing/demultiplexing, reliable

data transfer, flow and congestion control, UDP, TCP • Network Layer: Services, switching techniques, addressing, routing

algorithms, routing in the Internet, IP, ICMP • Data Link Layer: Services, frame synchronization, fault detection

and correction, multiple access, addressing, Ethernet, Switch, PPP, ATM, MPLS

Objectives Students are familiar with the key terminology of a communication network in particular of the Internet. They are able to describe fundamental concepts of modern wired and wireless communication networks and prevalent communication protocols. Students understand applied principles within protocol layers and know different architecture paradigms and implementations of network applications. Students have the ability to apply proven methods and algorithms of information transfer and to differentiate between typical network components. They can select appropriate network technology, configuration, protocol functions and methods according to given requirements.

Teaching methods

Lecture


none

Type of examination

tbd


64. Marketing

Language English Content • Marketing fundamentals: customer orientation, purchase behaviour of

consumers, purchase behaviour of organisations, customer relationship management

• Key terms and tools of business strategy • Market research, market segmentation, target market definition,

positioning & differentiation • Product policy, incl. Innovation, brand management, after-sales

management • Price (and terms & conditions), incl. price determination process,

price-demand-function, price differentiation and modification, value-pricing

• Distribution policy, incl. sales channels, push vs. pull, vertical marketing systems, multi channel sales, introduction to retail and wholesale business

• Communications (Promotion), incl. advertising, sales promotion, public relations, personal selling, direct marketing

• Selected marketing topics, e.g. e-commerce, internet marketing, viral marketing

Objectives The students … • understand marketing and market oriented management, as well as

key marketing concepts such as customer satisfaction, purchase behavior and processes

• realise the relationship between business strategy, marketing plan (esp. market segmentation and positioning) and marketing-mix

• comprehend how market mix policies (product, price, place, promotion) work and interact with each other

• know key marketing tools in theory and practice Teaching methods

lecture


65. Material Science

Language English Content • Atomic structure and the nature of chemical bonding

• Structures of solids, especially metals • Imperfections in real crystals • Plastic deformation in ideal and real crystals, hardening effects by

disorders • Diffusion – mechanism, meaning and applications • Phases and phase diagrams • Kinetics of solidification • Kinetics of solid-state reactions – martensitic transformation and

precipitation reactions Objectives The students…

• know different types of chemical bonds and their occurrence in materials.

• are familiar with the most common metallic lattice structures and know the influence of these structural types on plastic formability.

• are able to denominate and sketch structural disorders and to explain the role of dislocations during plastic deformation.

• understand the context between different hardening mechanisms of metals and the kinds of disorder, responsible for the considered hardening effect.

• can explain the mechanisms of diffusion in solids, know the time and temperature dependence of diffusion processes and selected technical procedures, where diffusion plays an important role.

• are familiar with the basic types of phase diagrams in general and with the constitutional diagram Iron Carbon in particular.

• know well, how solidification processes are influenced by nucleation and crystal growth and therefore, how the microstructure and properties of cast parts can be controlled.

• know the fundamentals of the kinetics of solid‐state reactions and understand the mechanism, course and result of martensitic transformation and precipitation reactions as well.


tbd

Type of examination


Media Students: Lecture notes, moodle, presentations, worksheet Lecturer(s): Blackboard, LCD-projector, Tablet-PC, moodle


To be determined


66. Management Accounting & International Taxation

Language English Content • Economics of public sector, the tax systems

• International taxation: taxation of global groups, Value added tax, withholding tax, transfer pricing

• Principles of Cost Accounting • Advanced management accounting systems, • Budgeting and strategic planning as a base for strategic decisions

making

Objectives Understand the importance of international taxation systems for strategic decision-making Achieve sound understanding of the most important aspects of international company taxation Understand the core concepts of cost and management accounting Be able to use advanced management accounting concepts as a base for strategic management in global companies


67. Mathematical Modelling and Simulation – Master´s level (IAE)

Language English Content The following topics are covered:

• continuous time modelling of mechanical, electrical, and hybrid systems by means of linear graphs and bond graphs

• event discrete modelling by means of Stateflow • tools: solution of dynamic problems using a digital simulation

packages for continuous time/sampled data systems such as MATLAB/Simulink

Objectives After successfully completing the module, students … • understand the process of system modelling • are able to formulate mathematical models of physical systems by

means of input/output equations • are able to model systems of different energy domains in state space

representation according to unified approaches • are able to use software tools (e.g. Matlab/Simulink) for modelling,

simulation, and analysis Teaching methods



Engineering mathematics; Relationships between describing variables (force, torque, current, ...) of the mechanical and electrical energy domain

Type of examination


Media LCD-projector, blackboard, overhead projector Recommended literature

• SEELER, Karl A., 2014. System dynamics: an introduction for mechanical engineers [online]. New York, NY [u.a.]: Springer PDF e-Book. ISBN 978-1-4614-9152-1, 978-1-4614-9151-4. Available via: http://dx.doi.org/10.1007/978-1-4614-9152-1.

• BROWN, Forbes T., 2007. Engineering system dynamics: a unified graph-centered approach. 2. edition. Boca Raton, FL [u.a.]: CRC, Taylor & Francis. ISBN 978-0-8493-9648-9, 0-8493-9648-4

• KARNOPP, Dean C., MARGOLIS, Donald L., ROSENBERG, Ronald C., 2012. System dynamics: modeling, simulation, and control of mechatronic systemsc [online]. Hoboken, NJ: Wiley PDF e-Book. ISBN 978-1-118-15281-2, 978-0-470-88908-4. Available via: http://dx.doi.org/10.1002/9781118152812.

• KARRIS, Steven T., 2007. Introduction to Stateflow with applications. [Fremont, CA]: Orchard Publ.. ISBN 978-1-934404-07-2, 1-934404-07-1


68. Mathematics 1 (CAI)

Language English Content Differential & Integral calculation

- Continuous Functions - Sequences (explicit & recursive) - Convergence - Mathematical induction

Objectives After successful completion of this course, the student is able to •state the basic facts in logic and apply results to appropriate examples. •understand the structure of proofs and construct proofs in computer-science related problems (for ex-ample, mathematical induction). •represent complex numbers in various forms in order to solve equations and inequalities. •analyze limit processes to sequences (explicit and recursively defined). •state, apply, and interpret formulas and theorems in differential calculus. •develop Taylor polynomials and approximate the error using Lagrange remainders., •develop infinite series and determine their radii and intervals of convergence. •state and apply the definition of Riemann integrals, the fundamental theorem of calculus and the meanvalue theorem for integrals. Apply the basic integration techniques such as substitution and partial inte-gration.


69. Mathematics 1 (AVE)

Language English Content Fundamentals: propositional logic, set theory, relation, function,

inverse function, sequences, limits, convergence

Complex numbers: cartesian and polar/exponential coordinates, exponentiation, complex conjugate, fundamental theorem of algebra, polynomials, application: harmonic oscillation, AC current

differential calculus with one variable: continuity, differential quotient, derivative, derivative of the inverse, derivation rules, basic functions, hyperbolic functions, postion vector, tangent vector

differential calculus with more than one variable: scalar functions with tow and more variables, potential function, partial derivative, gradient, total differential, implicit derivation, directional derivative

integral calculus with one variable: definite and indefinite integral, primitive function, fundamental theorem of calculus, basic primitives, integration rules, product integration, integration by substitution, partial fraction method, integration of rational functions, improper integral

Objectives After successfully completing the module, students shall

know the major mathematical techniques and their interrelations to solve engineering problems understand the underlying principles are able to apply the learned methods to solve tangible technical problems.


70. Mathematics 2 (AVE)

Language English Content • Power series, elementary functions: exponential function,

trigonometric functions. Taylor series, • integral calculus with one variable: definite and indefinite

integral, primitive function, fundamental theorem of calculus, basic primitives, integration rules, product integration, integration by substitution, partial fraction method, integration of rational functions, improper integral

• differential calculus with more than one variable: scalar functions with tow and more variables, potential function, partial derivative, gradient, total differential, implicit derivation, directional derivative

• Integral calculus with more than one variable: two- and three dimensional area integral, polar coordinates, path integral over vector and scalar field, scalar potential and gradient field, path independent integral, spherical coordinates, surface integral over vector and scalar field, flux, divergence theorem with application, vortex field, curl, Stokes’ theorem, Nabla operator, Maxwell equations

Objectives After successfully completing the module, students shall

• Have gained advanced competences in applying mathematical methods

• Can analyse complex problems and decompose them in to solvable parts

• Have knowledge in order to combine various mathematical techniques in order to solve challenging, heterogeneous tasks

• Can judge the convenience of possible solution approaches and compare alternative methods to solve technical problems

Teaching methods

tbd.


71. Mathematics 1 (EGM)

Language English Content • Rational and real numbers, complex numbers

• Limits, series and convergence, continuity and functions • Differentiation and rules, higher derivatives, applications • Introduction to integration, integration methods, applications • Differential equations

Objectives The students … • develop the capability, to apply mathematical knowledge to technical

and economic problems and to model mathematical tasks • understand and master mathematical tools • gain expertise in flexible and abstract thinking


Arithmetics, elementary functions, geometry, trigonometry and vectors

Type of examination




• Stroud, Booth: Engineering Mathematics • Riley, Hobson: Mathematical Methods for Physics and Engineers.


72. Mathematics 2 (EGM)

Language English Content • Linear Algebra: matrices, vector spaces, determinants, eigenvalues

and eigenspaces • Differential and integral calculus in n dimensions and applications • Systems of differential equations and applications

Objectives The students … • deepen their ability to apply mathematical knowledge to technical and

economic problems and to model mathematical tasks • gain security in the application of mathematical tools for engineering

problems • continue their development of flexible and abstract thinking


Mathematics 1

Type of examination




• Stroud, Booth: Engineering Mathematics • Riley, Hobson: Mathematical Methods for Physics and Engineers


73. Mechanical Design 1

Language English Content • basic principles of drawings and schemes, parts lists

• basic principles of machine elements such like bowls, screws, rivet, tooth wheel

• welding technique such like gas, laser, electric • joining techniques such like riveting, clinch, braiding, • design of gear box and engine parts • design of example components such like mechanical press and

riveting machine Objectives The students …

• should be able to understand the main principals of mechanical design

• should be able to make own calculations and design on machine parts and structural components

• should be able to read design schemes and parts list • know the main principals of machine elements and joining technique • are able to make calculations an transmission gear boxes, engines

and engineering components Format lecture Prerequesite for attendance

lecture, excercises, documentation and given literature

Type of examination




To be determined


74. Mobility Future Programme


• History and future What do we learn from automotive history? How will the automotive ecosphere look like in ten years?

• New business opportunities

What opportunities arise from the CASE *) areas? What are the value creation stages in the mobility industry?

• Strategy

What trends affect automotive and mobility? How do digital business models work?

• Methods

What do leadership principles look like in a creative working environment? What role do agile principles play and how can they be implemented?

• Acceptance for change

What are the best strategies for acceptance? How can we train change management?

• Sustainability in the context of mobility business

How can a holistic sustainability concept be developed? How can sustainability be anchored in an organisation?

*) CASE: Connected Autonomous Shared Electric

Objectives The module “Mobility Future Program” provides students with contents and challenges of automotive and mobility that implicates the future of the sector. It gives insights into current developments and a possible outlook for future tasks. Students • give an overview of the major trends in automotive industry and

mobility • can present the holistic view of the corporate context • give a detailed insight into the VUCA *) world and derive possibilities

in the changing mobility industry • deal with questions concerning the development of promising

business models • are able to transfer acquired CM strategies to a case study

understand the advantage and dependencies in order to shape the future


• transfer the learned methods to drive forward the transformation of the mobility branch

• can present and discuss the results in a confident manner *) VUCA: Volatility Uncertainty Complexity Ambiguity


75. Natural User Interfaces (Master´s level)

Language English Content • Technologies: Hard- and software solutions for natural

interfaces, frameworks, best practices, • Types: Touch interfaces, multi-touch interfaces, pen-based

interfaces, gestural interfaces, • Interaction: Interaction paradigms, gesture sets, primitives,

design principles, interaction with natural interfaces, • User Experience: User-centered gesture design, Testing

gestures, NUI Mock-Ups, Wizard-of-Oz experiments for gesture interfaces, Prototype implementation.


- understand basic terms, methods and concepts for natural user interfaces,

- apply principles of project management and teamwork within the scope of a project on natural user interfaces,

- choose appropriate hard- and software solutions for realizing on projects on natural user interfaces,

- plan, design and develop their own natural user interfaces, - evaluate the practical suitability of their developed applications. -

Teaching methods

tbd


76. Numerical Methods and Computation Simulation


Numerical approximation of derivatives, Numerical solution of large systems of linear algebraic equations, round-off error, Numerical solution of the linear heat equation Introduction into numerical flow simulation theory (computational fluid dynamics, CFD) Finite-volume method and its mathematical background Application to 3D fluid simulation with commercial software Theory of computational simulation of thermal and hydraulic processes Thermal and hydraulic simulation in building services engineering Computational simulation of thermodynamic processes Application to practical problems (computer lab)

Objectives The students can estimate the error of a numerical approximation of derivatives and use a suitable order of approximation for the given application, understand the influence of the round-off error and conditioning on the numerical solution of linear algebraic equations and can assess which direct or iterative methods are suitable for the given purpose, recognize the above methods in the finite difference discretization of the heat equation, can explain consistency, stability and convergence, are able to evaluate the merits of the explicit and implicit approaches, are familiar with simple implementations of the discussed numerical methods in some widely used computer algebra system (e.g. MATLAB) or programming language are familiar with the mathematical background of the Finite-Volume method are able to apply different computational methods like Computational Fluid Dynamics and 1D simulation of thermal and hydraulic processes to problems in renewable energy systems are able to evaluate and discuss simulation results with respect to theory and experiments

Teaching methods

tbd


none

Type of examination

tbd


77. Off-Grid Energy System – Master´s level (RES)

Language English Content Voltage Control

Frequency Control Generators (Synchornous, Asynchronous) Converters description Load flow calculation Load behavior Energy Storage Energy conversion and transport Wind Power description

Objectives The students: Can model an offgrid electrical system Know the main components in an Offgrid System : Generators, Loads, safety devices… Know the principles of the grid frequency control Know the principles of the grid voltage control Are able to determine the stability of an off grid system Know how to do a power flow analysis Can take the decision of the needed requirements (Hardware an control) to desigm an offgrid system Can write the project specification for the given system

Teaching methods

tbd


none

Type of examination

tbd


78. Power Engineering

Language English Content • Actual situation of energy supply

• Influence on environment and climate • Use of fossil fuels for power and heat generation • Steam and gas turbine process • Combined cycle power plant • Combined heat and power plant • Use of nuclear power • Basics of renewable energy • Hydropower; wind power; biomass; solar energy • Storage of energy

Objectives The students … • know and can use the subject-specific terminology • know the most important methods of energy conversion and their

pros and cons • acquire fundamental knowledge in thermodynamics and fluid

dynamics • are able to calculate and evaluate cyclic processes • are able to estimate the efficiency of different methods of power

and heat generation • develop sensibility in regard to the social relevance and the

enviromental effects of the different energy technologies Teaching methods

lecture


Selected Topics in Physics

Type of examination


Media students: lecture notes, Moodle lecturer: LCD-projector, blackboard, Tablet-PC, Moodle


• Demirel, Y.: “Energy: Production, Conversion, Storage, Conservation, and Coupling”; Springer

• Kaltschmitt, M. ; Streicher, W.: “Renewable Energy: Technology, Eco-nomics and Environment”; Springer


79. Power Train – Master´s level (IAE)

Language English Content • basics of vehicle movement and driving resistances

• market-specific test procedures for series-production vehicles/certification

• design principles of internal combustion engines (ICE) • advantages/disadvantages of different IC-engine concepts

(diesel/gasoline, ...) • concepts for fuel consumption reduction in modern IC-engines • emission generation in IC-engines/exhaust gas aftertreatment • gearbox concepts and start-up elements • hybrid and electric drivetrain concepts • potentials of electrified drivetrains according to fuel consumption and

emission generation • energy storage systems for vehicle applications

Objectives After successfully completing the module the students … • know details about legal framework conditions for current and future

powertrain developments (CO2- and emission legislation, test procedures, test cycles, ...)

• understand advantages and disadvantages of different drivetrain concepts according to driving per-formance and energy consumption

• show detailed knowledge of internal combustion engine design principles and operation strategies

• are able to explain the operating principles of different gearbox constructions and know advantages and disadvantages of the different concepts

• have a detailed understanding of hybrid drivetrain architectures and know about the potentials of hy-brid drivetrain technology

• know different energy storage systems for vehicle applications and their advantages and disad-vantages

Teaching methods



basic knowledge of physics (Work, Power, Forces, Torques, ...), engineering mathematics (differential and integral calculus), engineering mechanics

Type of examination


Media LCD-projector, blackboard, overhead projector


80. Power Supply and Energy Distribution


After successfully completing the module the students should • have good knowledge in the field of modern energy distribution

systems in cars and of the components used in the automotive energy nets

• understand why energy management systems are important for the operation of electric energy nets in cars

• understand the operation principle of power electronic converters for automotive applications

• understand and to use methods to develop steady-state and dynamic models of power electronic con-verters for given type of problems

• analyze and judge the steady-state and dynamic performance of automotive electrical energy nets with power electronic components according to given targets

• understand the operation principle of modern electric machines for electric and hybrid electric vehicles including the control of the electric machines

• be able to use steady-state and dynamic models of electric machines in order to analyze the energy flow in automobile electrical energy nets dependent on the operation strategy of the vehicle

• be able to derive models of given automotive energy nets and the components and to perform simula-tions for optimization purposes

Objectives • Power Devices and Converter Topologies

• 14V / 48V Power Supply and Energy Distribution • Generation of electric Power in Vehicles • Energy management Systems • High Voltage electric Energy Distribution for Hybrid Vehicles • Electric motor Drives and motion Control • Starter / Generator • Simulation

Teaching methods

tbd.


81. Practical Training in Interaction Design (Master´s level)






• Der Schwerpunkt des Moduls ist, aufbauend auf dem Produktdesign, das Arbeiten an dreidimensionalen Objekten und Produkten. Der Fokus liegt hier auf Objekten, die agieren und interagieren können, und deshalb mit einem Arduino-Mikrocontrollerboard, Sensoren und Aktuatoren ausgestattet sind. Die konkreten Projektthemen werden zu Beginn des Semester in einem vom Design-Thinking abgeleiteten Prozess entwickelt.


Objectives Die Schwerpunkte dieses Faches liegen in der Entwicklung von

Kenntnissen und Kompetenzen in den Bereichen:





-


82. Production and Logistics Networks – Master´s level (APE)

Language English Content • Production networks and skills strategies

• Logistics systems and networks • Logistics concepts in manufacture (intralogistics)

Objectives The students … • get to know the significance, elements, basic structure, design and

execution of production and logistic networks in the automotive industry

• can capture and assess interactions between production network, location factors, suppliers, logistics network, own/external skills, own manufacturing penetration, product design/technologies, production design/technologies etc...

• get to know possible production strategies, their effects on the production and logistics network including suppliers’ environment and can systematically assess and develop different production strategies

• can design skills strategies in conjunction with the production strategy and hence derive and establish skills development including supplier development

• get to know procurement, intra/production and distribution logistics systems used in the automotive industry (e.g. JIT, milkrun, supermarket, kanban concept, single/multi-level, combined logistics systems etc.)

• can assess and fundamentally calculate the effects of different logistics concepts

Teaching methods



none

Type of examination


Media students: lecture notes lecturer: LCD-projector, blackboard or whiteboard, Tablet-PC, OHP


To be determined


83. Programming 1 (CAI)

Language English Content Variables

- If-statements - For/While statements - Functions - Basic data structures (set, linkedlists, hash-tables) - Sort (with introduction to run-time complexity) ...

Objectives The module is designed to teach students to program in Python in a practical manner using industry standard methods, tools and technologies. It not only teaches students the Python programming language but also improves their algorithmic thinking and problem-solving capabilities so that they can write code that actually works and produces the desired functional results. After completion of the module the students will be able to • understand the programming basics (operations, control structures, data types, etc.) • readily use the Python programming language • apply various data types and control structure • understand class inheritance and polymorphism • understand the object-oriented program design and development


84. Programming 1 (AVE)

Language English Content • The following topics are covered:

• • Introduction: foundations of algorithms and information

processing • Information representation: Data Types, variables and basic

data structures • Control structures: conditional execution, loops, lists and list

processing • Procedural abstraction: functions modules and packages • Objects and dlasses • Advanced topics: exceptions, events and event-driven

programming

Objectives The module is designed to teach students to program in Python in a practical manner using industry standard methods, tools and technologies. It not only teaches students the Python programming language but also improves their algorithmic thinking and problem solving capabilities so that they can write code that actually works and produces the desired functional results. Giving students enoughwell thoughtcoding exercises ensures this. After completion of the module the students will be able to understand the programming basics (operations, control structures, data types, etc.) readily use the Python programming language apply various data types and control structure understand class inheritance and polymorphism understand the object-oriented program design and development understand and begin to implement code

Teaching methods

tbd


85. Programming 2

Language English Content • Introduction: Object Orientation and C++

• Development environment and runtime environment • Memory management, references • Classes, inheritance, polymorphism • Dynamic Polymorphism in C++ • Generic modules based on templates • Static polymorphism based on templates • Metaprogramming, function objects and λ-expressions • STL library, iostreams library • Potentials and effects of optimising translators in C++

Objectives After attending the module, students will be able to

• state and explain the essential features of an object-oriented programming language.

• use the basic programming constructs of C++ in concrete programmes.

• explain the most important functions of a modern development environment and use them to create programmes.

• explain the problem of proving the correctness of a program and describe and apply a systematic test methodology for error reduction.

• successfully demonstrate the practical application of the contents learned in a medium-sized programming task (=practical course)

Teaching methods

tbd.


86. Production Management and Optimisation – Master´s level (APE)

Language English Content • Quality management models

• P-FMEA and quality assurance on process level • Principles and methods to analyse manufacturing operations • Process data with focus on productivity and quality • Optimisation of work stations and production systems • Information and personnel management in production • Integration of product and process changes • Additional practical exercises and field trips

Objectives The students: • are familiar with the principles, models and components of quality

management (e.g. TQM, Six-Sigma, EFQM) and operative quality assurance

• are able to analyse quality impacts of manufacturing processes by using suitable methods (i.e. P-FMEA)

• learn to understand any production system as a value stream and get knowledge to document, to analyse and to improve such a system on a data based approach

• are in the position to use methods, tools and principles (i.e. value stream mapping, SMED, 5S) in order to optimise production systems (i.e. machining, assembly, tool room) as well as elements (e.g. topology, manufacturing and handling processes, provision of materials) of the production system

• know the aspects and significance of information management in production and the fundamental functions of the systems used for it (e.g. visual management, IT, industry 4.0)

• know basic principles of shop floor management and the meaning of process data visualization

• are aware of the integration of new processes in existing manufacturing systems caused by product changes or completely new start-ups

Teaching methods

tbd


none

Type of examination

tbd



tbd


87. Production System and Plant Design – Master´s level (APE)

Language English Content • Production systems and their development

• Production and factory planning processes and strategies • Added value, value-stream design, aims • Benchmarking • Ergonomics (Industrial Engineering/work preparation) • MTM, REFA target time determination, using TICON • Ergonomics, EAWS, stress-strain assessment and design • Product design to meet the requirements of production, PROKON • Design of manufacturing and operating organisation • Workplace, facilities and factory planning concepts • Design possibilities of internal logistics

Objectives The students … • get to know production systems in the automotive industry with

their concepts and forms (e.g. TPS, APS …) • get to know explanatory variables and aims of design and control

(added value, motivation, demography, KPI, etc.) • can assess the influence of the product on production costs • understand the structures and elements (e.g. “Takt-Fluss-Pull-

Perfektion“, …) as well as connections of a production system and can hence assess concrete implementations as well as develop their own

• know strategies and methods involved in production and factory plan-ning and can use these independently (e.g. connection between product, production, system, 3Ps “Production Preparation Process“, etc.)

• know various possibilities of manufacturing and operating organisation and are in the position to use and assess these in concrete cases of application in the automotive industry including suppliers

• can handle methods of ergonomics (e.g. workplace evaluation and de-sign, EHPV-F time determination/REFA/MTM, cycle order planning etc.) and assess their possibilities (e.g. occupational psychology, ergonomics, demography etc.)

• can plan a production system with concrete workstations and facilities

Teaching methods

lecture


Fundamental knowledge of production planning and control (PPS) as well as factory planning at bachelor level, MTM basic knowledge, REFA GA2.0 basic knowledge

Type of examination

Performance record and written exam (90 minutes)

Media Students: lecture notes, moodle Lecturers: LCD-projector, blackboard/whiteboard, OHP, Tablet-PC


• Dangelmaier, Fertigungsplanung, 2. Auflage, Springer Verlag 2001 • Tschätsch, Praktische Betriebslehre, Vieweg Verlag1996 • Schulte, Logistik, 6. Auflage, Vahlen Verlag 2013


• Torke/Zebisch, Innerbetriebliche Materialflusstechnik, 1. Auflage, Vogel Verlag, 1997

• Martin, Transport- und Lagerlogistik, 8. Auflage, Vieweg Verlag 2011

• REFA, Methodenlehre der Betriebsorganisation, Carl Hanser Verlag 1991

• Der REFA Ordner/Lehrunterlagen GA 2.0 • REFA, Industrial Engineering, 1. Auflage, REFA 2011 • Lotter, Manuelle Montage, 1. Auflage, Expert Verlag 1998 • Schmidt, Konzeption und Einsatzplanung flexibel automatisierter

Mon-tagesysteme, 1. Auflage, Springer Verlag 1991 • MTM Schulungsunterlagen • Bonkranz/Landau, Produktivitätsmanagement von

Arbeitssystemen, 1. Auflage, Schäffer/Pöschel 2006 • Klein, Einführung in die DIN Normen, 1977


88. Production Planning and Logistics

Language English Content • PPS Systems / MRP II

• Kanban • Utilisation oriented order release system (BOA) • Cumulative quantities concept • Optimized Production Technology • Frozen Period planning • Integration of PPS in ERP/CIM • Inventory management systems and their KPI´s • Production programme planning • Quantity Planning • Scheduling • Supply Chain Management in different branches, design, KPI´s,

tools • Different examples from industry

Objectives The students … • will understand the challenges of production planning in different

branches and sizes of industry • will know about the different tasks and results of long-, mid- and

short term production planning • will understand and are able to adapt the different production

planning philosophies push/pull • will be able to design themselves their own production planning tool

tak-ing into account enterprise specific needs • will know and understand the different tools of production control

methodologies and are abe to adapt these methodologies on the specific cir-cumstances in production companies

• will know and adapt important KPI´s to control the success of production planning methodologies

• will be able to adapt the production planning methodologies in the whole supply chain including external customers and suppliers

Teaching methods

lecture


none

Requisites according to Examnination Regulations

none

Type of examination


-


89. Production Systems: two parts with two different lecturers

Language English Content • introduction, basic terms, definitions

• tasks of industrial engineering in production • processes in purchasing of technical equipment • applied research • types of tool machines • history of tools machines, global situation • requirements for tool machines • elements and function of tool machines • components of tool machines • introduction to assembly technology • assembly systems, types and range of application • basic requirements for assembly systems • assembly systems used for different ranges of complexity, flexibility

and number of pieces • components of assembly systems, industrial robots • tasks ad objectives of logistic systems • components and systems of transportation and handling in

production • storage systems, basics of storing • commissioning systems and organisation • excursions and case studies

Objectives The students… • know and use the specific terms • are able to purchase production machines methodically • get a survey about production machines and systems in assembly,

logistics and manufacturing • are able to decide about the productive application of technical

elements in production • are able to calculate the hourly rates ans costs of production

technology and the quantity/number of pieces to decide about automation and machine type

• know the basic ways of organizing and applying production systems • can use the holistic view on industrial production systems • are able to design logistic systems with components and organization • know basic safety regulations in production • know the state of the art in the process chain of production • can solve specific tasks designing production systems in teams • are able to present the results

Format Seminaristic instruction with practical exercises Prerequesite for attendance

Practical experience in producing units (internship, apprenticeship, …) useful

Type of examination



90. Programming for Multimodal and Interactive Systems (Master´s level)

Language English Content • Introduction: Voice User Interfaces, Chatbots, Alexa Skills,

Amazon Echo, Chatbot User Experience • Design: Design Fundamentals, Voice User Interface Design,

Personas, Avatars • Concepts: Cognitive Load, Error Recovery, Grammars, “Put-

that-there” • Technologies: Modalities, Devices, Speech Recogntion, Voice-

Enabled Devices • Evaluation: User Testing, Mock-Ups, Wizard-of-Oz-

Experiments, Prototype Implementation


• use and combine different modalities when prototyping and developing interactive systems,

• evaluate the suitability for perception and action modalities for their specific use case. On the basis of this evaluation, students will be able to build a multi-modal user interface,

• evaluate the practical suitability of their developed applications.

Teaching methods

tbd


91. Project:

Language English Content Working on a semester-related project task in a team (size ca. 10

students). In many cases, the offered pro-jects are carried out in cooperation with external companies or the university's research center FORTEC. Alternatively, lecturers also specifically present project topics that are to be processed as part of their teach-ing or research activities.

Project management and organization are carried out by students. The lecturer acts only as a coach and/or client (product owner). The project management method can be classical methods or agile methods such as Scrum or Kanban. The decision about which method to use is up to the project team as are the tools that are used for project management.

Objectives The project serves the development of interdisciplinary contexts as

well as the development of methodo-logical and social competence. This involves

• the development of alternatives from literature and/or lectures to solve a given problem,

• the implementation of a solution (approach), and • the presentation of the results in a project report.

At the same time, the project serves to gain experience in interdisciplinary cooperation and the organization of team processes as well as in the application of creativity techniques, moderation and presentation.


92. Project: Implementation and deployment of a ROS software environment for autonomous model car

Language English Content Students will work on a semester-long project assignment from the

field of computer science in a team.

Generally, projects are carried out in cooperation with external companies or the university's own research center. Alternatively, lecturers can also specify specific project topics to be worked on as part of their teaching or research activities.

The project management and organization are carried out by students. The lecturer/teaching assistant acts only as a coach and/or client. Classic methods or agile methods such as Scrum or Kanban can be used as project management methods. The decision on which method to use is up to the project team.

At the beginning of the project, the lecturer/lecturer clearly communicates his/her expectations regarding deadlines, form and proof of individual performance to be provided by all students. The project team agrees with the instructor/lecturer on the forms of communication and documentation to be followed by all project participants (students, instructor, client) for the duration of the project.

To be clarified:

• Frequency and duration of planning meetings • Type and execution of meetings (joint or virtual/electronic) • Regular meetings (possibly daily in the form of scrum meetings) • Type and scope of deliverables • Type and scope of individual input by students • Criteria for assessment/grading by the instructor

The main objective of this project is to develop and test a software environment for an autonomous model car. The model car to be used in this project is the hardware platform developed for 'Audi Autonomous Driving Cup'. The model car is equipped with the following sensor suite: 8 ultrasonic sensors, 2 Cameras (Front and Rear), RP2 Lidar, IMU, Accelerometer.

Computations in the model car are handled by an Intel processor and an Nvidia graphics card. The model car can be used as a platform to test and develop autonomous driving functionalities like lane following, automated parking, autonomous emergency braking, etc. Images of the model car are available under the link: https://www.digitalwerk.net/en/adas-modellauto-2/ .

In this project, the goal will be to develop a software environment for interfacing with the model car using the Robot Operating System (ROS, see link: http://www.ros.org/). The ROS software environment will be used for the following tasks:

https://www.digitalwerk.net/en/adas-modellauto-2/


• Reading the raw sensor data from the available sensor suite • Sending driving commands (steering, brake and acceleration)

to the motors • Vehicle battery management • Visualization of sensor data and the vehicle • Remote control of the model car.

Optionally autonomous driving functionalities like autonomous emergency braking, lane detection, etc. can also be implemented. The project will be given in English. Two model cars are available. Hence, only a maximum of 9 students can be accommodated in the project.

Objectives After attending the module students…

• have experience regarding at least one specific project management method

• are familiar with concrete tools that are used in the context of implementing IT projects

• have learned to deal with technical and non-technical problems that may arise during the implementation of a project lasting several weeks

• are able to analyze complex technical tasks and work successfully in a team over the course of a semester.

• will be able to report on project progress in varying but always appropriate detail in oral and/or written form

The students will get a first-hand experience on using sensor hardware similar to the ones used in real autonomous vehicles. In addition to that, the students will be exposed to ROS, which is widely used by the robotics community for prototyping. Also, the participants will learn to work as a team and how to deal with timelines, version control, etc.

Teaching methods

Assigning tasks, supervising team meetings, blackboard writing, presentations, demonstrations on computer and models.

Recommended Requirements

• Good knowledge of C/C++/Python • Basic knowledge of Linux environment (optional) • Basic knowledge of ROS (optional)


93. Project: If the user can’t use it, it doesn’t work: Development of an Interactive System using the Human-Centered Design Approach - Master´s level


students). In many cases, the offered projects are carried out in cooperation with external companies or the university's research center FORTEC. Alternatively, lecturers also specifically present project topics that are to be processed as part of their teaching or research activities. Project management and organization are carried out by students. The lecturer acts only as a coach and/or client (product owner). The project management method can be classical methods or agile methods such as Scrum or Kanban. The decision about which method to use is up to the project team as are the tools that are used for project management. At the beginning of the project, the lecturer clearly communicates his expectations regarding the dates, form and proof of the individual achievements to be provided by all students. The project team agrees with the lecturer on the forms of communication and documentation to be adhered to by all project participants (students, lecturer, client) during the project period. To clarify are: frequency and duration of planning sessions type and conduct of meetings (shared or virtual / electronic) regular meetings (possibly daily in the form of Scrum-Meatings etc,) type and scope of deliverables type and extent of individual amounts by students criteria for assessment/ rading by the lecturer Topics of the projects offered in this term are: TBD

Objectives The project serves the development of interdisciplinary contexts as well as the development of methodological and social competence. This involves the development of alternatives from literature and/or lectures to solve a given problem, the implementation of a solution (approach), and the presentation of the results in a project report. At the same time, the project serves to gain experience in interdisciplinary cooperation and the organization of team processes as well as in the application of creativity techniques, moderation and presentation.


94. Project: User-Centered Design of Autonomous Shuttle Buses for Use in Public Transport - Master´s level


students). In many cases, the offered projects are carried out in cooperation with external companies or the university's research center FORTEC. Alternatively, lecturers also specifically present project topics that are to be processed as part of their teaching or research activities. Project management and organization are carried out by students. The lecturer acts only as a coach and/or client (product owner). The project management method can be classical methods or agile methods such as Scrum or Kanban. The decision about which method to use is up to the project team as are the tools that are used for project management. At the beginning of the project, the lecturer clearly communicates his expectations regarding the dates, form and proof of the individual achievements to be provided by all students. The project team agrees with the lecturer on the forms of communication and documentation to be adhered to by all project participants (students, lecturer, client) during the project period. To clarify are: frequency and duration of planning sessions type and conduct of meetings (shared or virtual / electronic) regular meetings (possibly daily in the form of Scrum-Meatings etc,) type and scope of deliverables type and extent of individual amounts by students criteria for assessment/ rading by the lecturer Topics of the projects offered in this term are: TBD

Objectives - The project serves the development of interdisciplinary contexts as well as the development of methodological and social competence. This involves

- the development of alternatives from literature and/or lectures to solve a given problem,

- the implementation of a solution (approach), and - the presentation of the results in a project report. - At the same time, the project serves to gain experience in

interdisciplinary cooperation and the organization of team processes as well as in the application of creativity techniques, moderation and presentation.

Teaching methods

tbd


95. Probability and Statistics

Language English Content Descriptive Statistics

- Inference Statistics - Hypotheses tests, maximumlikelihood estimator, ... - Probability theory - Random variables, Conditional distribution, N(0,1), Limit theorems, ...

Objectives


96. Qualitative UX Design Research & Methods

Language English Content Previous UX research (Bargas-Avila & Hornbæk, 2011) informs us that

most researchers agree that UX is context-dependent, that the shift in HCI towards UX is accompanied by a change in favor of qualitative methods. Rational decision-making favors objective data and a formal process of analysis over subjectivity and intuition. However “User experience goals” differ from the more objective “usability goals”. Instead of assessing how useful or productive a system is they are concerned with how users experience an interactive product from their perspective. Accordingly, different individuals, or even the same individual at a different time, may experience technology in quite different ways, and that is not easy to capture in rationalist models. Rationalist models abstract in a way that excludes particular circumstances, perhaps the very circumstances that turn out in practice to be most salient (McCarthy, 2004). Qualitative methods are used to access people’s feelings, aspirations, and imaginations and can delve deeper into the explicit, observable, tacit and latent needs of the participants. Qualitative methods are suitable for addressing the ‘how’ and ‘why’ questions. They focus on the experiences of participants and support the understanding of the culture/behavior of a group. As a result, in this course, we address the value of qualitative research and design methods for UX, and we present examples of their application and their implications for design. The course will introduce students to ethnographic interviewing, participatory design, co-design activities, and generative techniques, for collecting qualitative data. The course will additionally introduce techniques and tools for coding, analyzing, and informing, design for UX. Some of the techniques and tools include thematic analysis, affinity diagraming, glass-wall mapping, and UX goal-directed personas and scenarios of use.

Objectives Purpose of the Course As a learning objective, students will become familiar with the most appropriate qualitative methods for UX research and design. Through


their assignment, they will be exploring the qualitative methods, techniques and tools that we describe in the course and learn how to collect, analyze, and design for user experiences based on qualitative data. Desired course outcomes: After successful completion of the course, students will be able to Select and apply the most appropriate qualitative UX research and design methods for the UX problems they are assigned. Use qualitative research and design methods to inform UX designers with actionable insights. Undertake UX research and design briefs from start to finish applying qualitative methods.

Teaching methods

A group assignment will help students address questions, including: What is the value of qualitative research and design methods for UX problems? Why is the qualitative method they used the most relevant to their problem? How to apply qualitative research and design methods to inform UX design? What were the limitations of their UX research and design approach? What would they avoid in the future? Presentations (pptx,pdf,prezi) Online questionnaires Quizzes Videos


none

Type of examination

tbd


97. Rechnernetze (Computer Networks)

Language English Content • History, classification and layered architecture model of computer

• networks • Physical layer, line encoding, transmission media • Data Link Layer, frame synchronization, flow control, channel • coding, protocol example PPP, access control, Ethernet • Network layer, RIP, OSPF, IP-Addressing, ARP, IP, ICMP, IGMP • Transport layer, TCP, UDP • Application layer, DNS, FTP, Telnet, SMTP, HTTP, P2P

Objectives Students are familiar with key terminology, classifications and reference models of computer networks as well as the most important protocols of the TCP/IP-protocol family. Participants understand fundamental principles of computer communication and are able to describe prevalent network components, their intended use and mode of operation. Graduates of this course have the ability to apply proven methods and algorithms of computer communication. They understand the operating principle of client/server protocols and are able to design simple TCP/IP application protocols. Course participants know the most important performance measures of computer communication, their dependence on network parameters and can analyze and optimize communication network performance for specific scenarios. By own practical experiments with the help of a popular tool for protocol analysis Students learned to analyze communication sequences and typical problems of network installation and to apply methods for fault diagnosis. They are able to configure common network components and link them via different transmission media as well as to select appropriate network configurations and structures depending on specific requirements.

Teaching methods

Seminaristic instruction, exercises, practical exercises


none


• Andrew S. Tanenbaum, Computer Netzwerke, Pearson Studium, 4. Auflage, 2003

• Andrew S. Tanenbaum, David J. Wetherall: Computer Networks, Pearson, 5th ed., internat. ed., 2011


98. Selected Topics in Digitalization

Language English Content Disruptive technologies

Drivers of digitalization Dimensions of digitalization at a glance: business models, processes, products, integration and communication of products with the environment, human-machine interface Digital business models and value networks Digital business processes Process mining and Robotic process automation (RPA)

Objectives get to know the drivers of digitalization as well as the typical phases, from digitizing existing processes to new digital business models and ecosystems gain insights into the possible effects of digitalization in society understand that it is no longer acceptable to just look at processes and data in isolation work in exercises with current software (e.g. process mining) practice digital collaboration in teams are able to analyse problems in the field of digitalization, using a systematic approach, and to present alternative solutions


9. Research Methods in HCI (Master´s level)

Language English Content • Intro to Human Factors Engineering

• Task Analysis (Physical and cognitive task analysis). • Design Methods (Iterative design and refinement, heuristic

evaluations). • Qualitative or descriptive methods (Usability testing, content

analysis, interviews, focus groups) • Controlled studies (Constructing laboratory studies, ecological,

internal, and external validity) • Data Analysis of Controlled Studies (Study designs, correlation

vs. causality, AB testing) • Quasi Experiments, Survey Design (Quasi experiments and

evaluation research, developing survey instruments, survey sampling methods; analysis of survey data)

• Observational Methods and Naturalistic Research, Extraction of naturalistic data for analysis)

• Objective vs Subjective Measures (Performance and physiological measures, Capturing attitudes, perceptions, stress, workload, performance)

• Synthesizing Research Results (Data visualization, reporting results, how to prepare awesome presentations?)

The schedule is tentative and subject to change. Objectives The objective of this course is to provide students with the principles of

human factors engineering, and the research tools that are used to examine these principles. The class will showcase (through weekly journal article readings) the value of qualitative (e.g., focus groups, interviews) and quantitative (e.g., controlled A/B testing, design of experiments) methods for human factors research. That is, how to capture abstract thoughts, people's opinions, and trends as well as design studies to capture the impact of design changes and interventions more formally. The focus of the class is centered on human factors design principles for safety, productivity, functionality, and usability. Upon course completion, students will be able to begin fundamental research in human factors. The journal articles will cover research methods and design issues related to operator performance given functional, psychological, physiological, and environmental constraints.

Successful students will understand:

- research methods to test human-machine interactions, - measurement tools to capture human performance and

behavior, - task analysis to identify gaps in the process, - examine user trust, acceptance, and satisfaction, - differences in experimental designs and the corresponding

analysis challenges, - design studies to examine a product or service with the human

operator in mind.


100. Selected Topics in Physics

Language English Content • Introduction to dynamics, mechanics and energy, collision equations

• Thermodynamics (ideal gas equation cycle processes, work and heat exchange, entropy)

• Fluid mechanics (mass conservation, energy conservation, Bernoulli equation)

• Heat exchange (conduction convection) • Practical exercise from one of the following areas: dynamics,

oscillations, aerodynamics and thermodynamics Objectives The students …

• understand and correctly apply the physical concepts related to: dynamics, fluid mechanics and thermodynamics.

• predict the movement of objects also after collisions • judge correctly the efficiency and feasibility of thermodynamic cycles. • calculate fluid dynamic cases without losses • identify and determine heat transfer processes • can think abstractly and they can solve exercises individually and in

teams • can evaluate and execute physical experiments


Mathematics

Type of examination


Media Students: Lecture notes, moodle, presentations, worksheet Lecturer(s): Blackboard, LCD-projector, Tablet-PC, moodle, materials for the practical exercises


To be determined


101. Selected Topics in International Management

Language English Content • Selected aspects in global marketing, e.g. product definition,

communication, distribution • Commercial aspects in international business, including transfer

pricing, differences in financial accounting, different tax systems, import duties

• Managing a global supply chain, incl. global sourcing, international production networks, global logistics

• Developing products leveraging global R&D networks • Global human resource management in light of cultural differences

and local labor legislation Objectives The students …

• understand the additional challenges global players face in key business functions (finance, marketing, supply-chain, R&D, human resource management)

• learn best practices of how successful companies cope with the challenges of running global businesses

Teaching methods

lecture


Business administration, financial accounting

Requisites according to Examnination Regulations

none

Type of examination

Oral exam (15 minutes)

Media students: lecture notes, Moodle lecturer: LCD-projector, blackboard, Moodle


To be determined


102. Sensor Technology and Signal Processing – Master´s level


Introduction to Automotive Sensors Automotive Sensor Market Sensor Technologies Sensor Types and Characteristics Multi-Modal Sensor Systems Statistical Signal Processing Signal Types and Characteristics Basics of Statistical Signal Processing Pattern Recognition Kalman Filter Sensor Data Fusion Data Association Track-To-Track Fusion Analog and Digital Processing of Signals Analog Filters, Amplifiers and A/D Converters Fourier Series and Transform, Laplace- and z-Transform Digital Filters

Objectives • After successfully completing the module the students are able to • describe major trends in the automotive sensor market; • categorize automotive sensors with respect to the underlying

physical effects; • to analyze sensor signals in the time- and frequency-domain; • apply statistical signal processing algorithms (e. g., Kalman filter) to

automotive sensor data; • to evaluate algorithms for sensor data fusion; • to design and apply simple machine learning algorithms • to implement statistical signal processing algorithms in Matlab. •

Teaching methods

tbd


none

Type of examination

tbd



tbd


103. Smart Mobility: Trends in Intelligent and Sustainable Mobility Systems

Language English Content • Fundamentals of transportation theory

• Intelligent transportation systems (ITS) • Stakeholders in a mobility system • User centric perspective on mobility (demand, acceptance,

satisfaction, mobility patterns etc.) • Mobility data: Collection, usage, data management & quality • Public transport • Mobility on demand and mobility as a service • Routing and the role of routing apps in a mobility system • Micromobility • Urban Air Mobility • Mobility platforms

Objectives Objective of the course is to give an overview of innovative mobility

concepts and intelligent transportation systems and to show the influence of digitalization and artificial intelligence on mobility systems. Different scientific areas (transportation theory, machine learning & ICT, user experience, sustainability) are combined for a holistic view on the subject and worked on in an interactive way. After finishing this course including the seminar paper/presentation students are able to Know fundamental concepts of transportation theory Explain certain innovative mobility concepts and their properties Explain and evaluate the role of digitalization and artificial intelligence in mobility Know stakeholders, their interplay and resulting challenges in mobility systems

Teaching methods

tbd


104. Software Development

Language English Content • Basic principles of object oriented programming

• Inheritance, Polymorphism • Basic concepts of the java api • The whole software development process • Principles of software architecture • Quality assurance

Objectives The students develop a practical understanding of the field of software development. They are familiar with the basic principles of object oriented programming, software engineering and modelling of software.

Teaching methods

lecture


none

Type of examination


Media students: lecture notes, Moodle lecturer: LCD-projector, blackboard or whiteboard, PC demonstrations, lecture script, Moodle


To be determined


105. Special Topics in Financial Modelling

Language English Content • create a business plan for a company

• Budgeting of different departments of a company • decission making in the financial planning process • Instruments of company valuation • What financial figures have a major impact on company valuation • Where to get the appropriate Data for company valuation • Do all the calculations via Excel

Objectives The students get to: know how to create a Excel-Tool for company valuation know the important aspects of company valuation know how to create the financial model of a Business Plan via Excel know the important aspects of business plan modelling


106. Statics

Language English Content • Introduction to the basics of statics (bars, beams, plates, etc.,

bearings and hinges, equilibrium conditions) • Central and common force systems • Analysis of mechanical structures, including trusses • Forces, Moments, Resultants, Support Reactions • Internal forces and moments • Spatial mechanical systems • Center of gravity • Friction

Objectives The students • Get knowledge in the effects of forces and moments • Are able to get to the root of static problems • Use equilibrium equations • Determine competent outer and inner load reactions • Solve friction problems • Know the technical terms and are able to use them • Are able the think abstractly and solve problems independently and

efficiently


107. Statistics

Language English Content Descriptive statistics

• Vizualization of distributions • Scaling • Metrics for descriptive analyses of a data set • Metrics and models for bivariate connections

Probability theory and inductive statistics

• Probability space • Conditional probability and Bayes • Random variables • Discrete and continuous distributions • Selected hypothesis tests • Linear regression • Markov chains

Objectives After finishing this course including excercises students are able to:

• Choose and calculate appropriate metrics for describing a data set

• Understand different kinds of data and scaling • Understand and interpret vizualizations of distributions • Explain and analyze bivariate connections • Understand fundamentals of probability and apply them to a

given data set • Explain and apply the concept of conditional probability and

Bayes‘ theorem • Name the most important distributions and know appropriate

applications • Understand and use linear regression for analyzing a given

dataset

Teaching methods

tbd.


108. Strategic Management

Language English Content • Definition of strategic management

• External analysis using porter´s five forces model • Internal analyses using SWOT analysis, portfolio analysis, benchmarking and value chain analysis • Strategy formulation • Common strategies: cost leadership, differentiation, integration, diversification, Ansoff matrix • Case Work

Objectives Students • know and use specific terms of strategic management, • understand meaning of strategic management, • can prepare an analysis of companies competitive situation by performing an external analysis using porter´s five forces model and an internal analysis using SOWT analysis, portfolio analysis, benchmarking and value chain analysis. • understand the process of strategy formulation, • can distinguish between cost leadership and differentiation and can apply the knowledge to analyses real life cases • understand corporate strategies such as integration, diversification as well as strategies shown in the Ansoff-matrix and can apply the knowledge to analyses real life cases. • Can solve case studies using above content

Teaching methods

tbd


cost accounting, controlling

Type of examination

Presentation: Grade for presentation is determined as follows: content 40%, visualization 40% and presenting 20%. Presentation will be hold in in the lecture time in the second half of the semester. Prerequisite for holding in the presentation will be the participation in group work and a proof of understanding regarding theoretical basics.




109. Strategic Foresight and Trend Analysis

Language English Content Customer-, technology-, and competitor-foresight

Trend analysis and strategic early identification Visioning Strategic simulation methods Prognostic crowdsourcing Delphi method Scenario technique Trendreceiver method Analysis of Science Fiction

Objectives The students understand the most important foresight methods and can distinguish and explain them can apply the methods learned in case studies can methodically analyse trends and derive future developments

Teaching methods

tbd


110. Studiendesign und Durchführung von UX-Tests

Language English and German Content Studierendengruppen können aus verschiedenen Themen im Bereich

Human-Computer Interaction (Augmented/Virtual Reality, User Experience, Produktivität, Vertrauen und Akzeptanz beim automatisierten Fahren, Fußgänger-Fahrzeug Interaktion beim automatisierten Fahren, usw.) wählen. Diese werden im Rahmen aktueller Forschungsprojekte von wissenschaftlichen Mitarbeitern und Doktoranden der THI/ CARISSMA gestellt. Jede Studierendengruppe hat somit zusätzlich zum Dozenten der Veranstaltung einen individuellen Ansprechpartner und Experten für das gewählte Themengebiet.

Objectives Nach dem Besuch dieses Moduls kennen die Teilnehmer die unterschiedlichen Schritte, die bei Benutzerstudien zu beachten sind sind Studierende in der Lage, selbst Experimente zu entwerfen, durchzuführen, auszuwerten und die Ergebnisse zu beurteilen können Teilnehmer die unterschiedlichen Methoden für Experimente unterscheiden und richtig einsetzen wissen Studierende über die Probleme, die bei Benutzerstudien im Labor oder Feld auftreten können, Bescheid und können Lösungen anbieten haben Studierende die Kompetenz erworben, basierend auf einer Problemstellung eine Forschungshypothese abzuleiten und in ein Studiendesign zu überführen haben Studierende Basiskenntnisse im wissenschaftlichen Arbeiten und können das Textsatzsystem LaTeX inkl. BibTex bedienen

Teaching methods

tbd


none

Type of examination

Im Rahmen dieser Lehrveranstaltung wird von Studierendengruppen ein konkretes Experiment entworfen, designed, im Rahmen des Praktikums durchgeführt und die Ergebnisse werden schließlich evaluiert und interpretiert. Das Endergebnis ist ein, an einem wissenschaftlichen Paper angelehnter, Report in LaTeX.

Media

Beamerpräsentation

Tafelanschrieb

Brainstorming und Diskussionsrunden

Workshops zu verschiedenen Themen

Feedback-Runden in der Gruppe und individuell


111. Symbolic AI: Knowledge Representation and Reasoning


Basic classification of AI technologies and differentiation between symbolic AI and numeric approaches such as Machine Learning Graph-based knowledge representation using the Resource Description Framework (RDF) Querying RDF graphs using the SPARQL query language Axiomatic knowledge representation using the Web Ontology Language (OWL) Practical knowledge modelling using Ontology Design Patterns Utilization of automatic reasoning to infer implicit knowledge

Objectives Application areas and limitations of symbolic AI Overview of technologies and formalisms for symbolic knowledge representation and reasoning Proper use of graph-based and axiomatic knowledge representation formalisms Understanding and proper use of automated reasoning and its relation to human intuition Hands-on experience in knowledge modelling and querying, including the use of modelling pattern

Teaching methods


Type of examination

Media



112. System Analysis and Control – Master´s level (RES)

Language English Content • System description,

• Definition of a control loop • Stability in a control loop • Transfer function • Frequency response • Main control variables • Root locus method • Alternative Design Methods • Design variables in a control system (calculation frequency, sample

frequency, variables to be measured etc..) • Response of first order and second order Systems • Speed Control of a Wind turbine • Frequency control in an electrical grid • Application to practical problems (computer lab Matlab)

Objectives The students … • can model a physical system • can characterize a control loop understanding what is the

controller, the actuator, the measurement device and the system • can take a decision on the dynamic needs of a system response • understands different methods of tuning the controllers to fulfill the

dynamic demands • knows the different controller types and can decide which

controller is needed for each case • are able to apply different controller tuning methods and are able to

predict the dynamic behavior of a system • are able to evaluate and discuss simulation results with respect to

theory and experiments • can take the decision of existing hardware to design a given

Teaching methods

tbd


none

Type of examination

Media Students: Lecture notes, moodle Lecturer(s): Blackboard, Tablet-PC, moodle


• Frequeny and Control for Everyone, Springer Verlag, 2010. Pedro Albertos

• Hydraulic Control Systems: Theory and Practice, World Scientific, Shizurou Konami 2016

• Modern Control Engineering, 2009, Prentice Hall, Katuhiko Ogata ISBN: 978-0136156734


113. Systems Engineering

Language English Content -Basic concepts of systems engineering: system context analysis;

concept studies; ideal system vs. real product; top-down, middle-out and bottom-up approach; design-for-variants; life cycle models. - Agile, Lean and Value: scrum; Kanban; pull-principle; value streams; waste; managing-by-means - Active Innovation: Design thinking; TRIZ and morphological box. - Case Study: Systems Engineering in ITER, the world’s largest engineering experiment. - Model-based Systems Engineering: How to model complex systems; architectural frameworks; information models; technical and physical models; UML/SysML. - Simulation and Digital Twins: types, theory and use of simulation in product development; feedback minimisation and closed-loop approaches; Product-in-the-loop; Digital Twins - companion for life. - Development phases: V-model; Concurrent engineering; Customer-in-the-loop; re-use. - Data, information and knowledge management. - Technical Management Processes: project; risk; configuration; variant; requirements engineering and quality management; decision making and design-to-cost (qualitative and quantitative).

Objectives The students are familiar with the reasons for and principles of structuring development projects to master system complexity. They are able to apply methods and procedures to solve problems, take decisions and manage development projects. They understand architectural frameworks and the advantages of using models to solve engineering problems.

Teaching methods

Seminar, project work, group work, exercises and assignments


Product Design & Development; Modelling Basics;

Type of examination

15 min presentation following the successful completion of a project and proof of a working knowledge of SE basics.

Media students: lecture notes, Moodle lecturer: LCD-projector, blackboard, Tablet-PC, Moodle


114. Technology Design and Evaluation

Language English Content Modern technologies and technology trends

Successful development and marketing of technologies and products Application-specific selection of adequate technologies Product lifecycle management (Product creation process, product data management etc.) Technology portfolio analysis and -roadmap Evaluation of innovation projects and technologies

Objectives The students know modern technologies and technology trends and can name them know important methods of technology management and can explain them can develop new technologies, evaluate them, use them for specific applications and market them

Teaching methods

tbd


115. Technology Development & Innovation Management

Language English Content • Technology and innovation management

• Technology development: processes, methods, examples • Benchmarking

Objectives The students … • know the significance, methods, elements and processes of

innovation and technology management. • understand the involvement in corporate and product development

processes • can independently use methods of innovation and technology

management • can install processes suited for systematic technology development

and use methods • know about the significance, effect and limits of IP protection

(Intellectual Property) and its targeted application as well as patenting processes

Teaching methods

lecture


none

Type of examination


Media -


• SCHUH, Günther, 2013. Future trends in production, innovation and technology management: [2011]. 1. edition. Aachen: Apprimus-Verl.. ISBN 978-3-86359-098-7

• SCOTT, Shane, 2008. The Handbook of Technology and Innovation Management.

• SCHUH, Günther and Günther SCHUH, , Band 52014. Handbuch Produktion und Management. 2. edition. Berlin [u.a.]: Springer Vieweg. ISBN 978-3-642-54287-9, 3-642-54287-5

• MÖHRLE, Martin G., 2008. Technologie-Roadmapping: Zukunftsstrategien für Technologieunternehmen. 3. edition. Berlin [u.a.]: Springer. ISBN 978-3-540-74754-3, 978-3-540-74755-0

• JOVANE, Francesco, Engelbert WESTKÄMPER and David J. WILLIAMS, 2009. ˜Theœ manufuture road: towards competitive and sustainable high adding value manufacturing. Berlin ; Heidelberg: Springer. ISBN 978-3-540-77011-4, 978-3-540-77012-1


116. Testing and Simulation Methodes for Vehicle Safety Systems (Master´s level)

Language English Content • Testing as part of the development process (ISO 26262/ V-

Model) • Testing methods and testing metrics • Test planning • Application of simulation based methods • Components of simulation • Different model types

Objectives After successfully completing the module the students

• shall know how to test automotive safety systems and control units while its development process

• shall understand different testing methods and their usage for different types of control units and different criticalities.

• shall know when and how to use simulation as an improvement of the testing process, which types of simulation can be used and their pros and cons.

- Teaching methods

tbd


none

Type of examination

tbd

Media


117. User Experience Design Strategy

Language English Content • Previous research highlights the importance of experiences

in the progress of the economic value model (Pine and Gilmore, 2011). Experiences are strongly interconnected with the company's offer and the Brand promise that the company delivers. People use products, services, systems and interact with the companies to experience specific elements of the offering. Previous work in Design Driven Innovation (Verganti, 2008) and in Brand Driven innovation (Abbing and Gessel, 2010), highlight the importance of the Brand identity and Brand image and describe ways of mapping the experience journey of people interacting with the offerings. Designing User experiences for a Brand is one of the most relevant industry practices in UX and various tools and methods are previously designed for this purpose (Abbing and Gessel, 2010).

• When design qualities are aligned to Brand qualities, meaningful experiences can be designed to fullfill the needs of people (Van de Sand et al., 2020). Proposing Technology as an experience (J McCarthy, 2004) incorporates the understanding of the soft value and supports designers in designing unique User Experiences. UX designers should be able to envision the social relationships and feelings of their users when interacting with their digital products or services and state their vision for their designed interactions. Previous work on Vision in Design (Hekkert and Dijk, 2011) by User experience and interaction design pioneers can support towards this direction.

• The course will introduce students to vision in the design method

• identifying the future context for their brand, • identifying future interactions for their brand, • forming mission/vision statements, and designing for a User

experience, • The course will additionally introduce brand dimensions and

elements that brand mature companies incorporate, such as • Mission statement brand image and brand identity, • Brand history, Product portfolio, Brand hierarchy, Brand

portfolio, Brand design, and human-computer interaction/UX,

• UX and competitors analysis, • Human-centered branding (BX, UX and UXi method).

Objectives Purpose of the Course: As a learning objective, students will

become familiar with the most vital branding concepts for designing user experiences with industrial and societal relevance. Through their assignment, the students will be exploring the possibilities of brand design and applying principles, guidelines, and good practices in their designs to enhance the UX of their products.


Desired course outcomes: After successful completion of the course, students will be able to State a vision applying VIP method to support drive their user experience designs. Identify essential dimensions of any given brand including: Mission statements, Brand history, Brand hierarchy, Brand identity, Brand image, Brand portfolio and Product portfolio. Design user experiences inspired by the different brand dimensions and elements, including design strategy from, sounds, metaphors, analogies, and colors. Use methods and tools to compare brands and evaluate the performance of their brand.

- Teaching methods/Examinatio

A group assignment will help students address questions, including: • What is the mission statement, the brand image and the

brand identity? • What is product portfolio and brand portfolio? • What is form hierarchy and form strategy design? • How to envision a brand? • How to envision the future context of their user experiences

and the future interactions? • How to map brand competitors and alliances run an

analysis? • How to design UXs inspired by brand dimensions and

elements? • How to design for a UX journey and orchestrate the

touchpoints of their experiences?

• Presentation (pptx,pdf,prezi) • Online questionnaires • Quiz • Videos


none


118. User Experience Participatory Design - Master´s level

Language English Content Participatory design in HCI has to do with participation, with how

stakeholders - especially users, developers, and planners - cooperatively make or adjust systems, technologies, and artefacts in ways, which fit more appropriately too the needs of those who are going to use them. Participation can be approached as an ideology, and also clearly refers to questions of ethics, politics, democracy, and empowerment. A Participatory Design practice entails tools and techniques that combine telling, making and enacting. Tools and techniques for making give people, both designers, and non-designers (not trained in design users), the ability to create ‘things’ which helps in externalizing and embodying thoughts and ideas in the form of (physical) artefacts. As a result, these artefacts can describe future objects or provide views on future ways of living. Participatory prototyping using mock-ups and other low fidelity models are most often used in the early stages of the design process. ‘Making as prototyping presupposes that you have already identified the object of the design, e.g., you are designing a product or a device or an environment, etc. Thus, in the traditional design spaces, the focus has been on using prototypes to create representations of future objects to give shape to the future, i.e., to help us see what it could be.’(Simonsen and Robertson, 2013, p. 155) Participation through Co-design has rapidly gained the attention of the researchers in Human-Computer Interaction who need to gain rich insights on the explicit, observable, tacit and latent needs of the participants (Visser et al., 2005) and share control, share expertise and get inspired to change (Vines et al., 2013). Researchers across disciplines also recognize the need for more active participation, with psychology having a considerable amount of studies where the attention is on the co-creation or the ‘continuum of consumer experiences,’ an interplay between traditional, holistic, immersive, and co-creation.

Objectives The learning objective for this course is to gain expertise in participatory design methods. Recently HCI methods that actively involve participants in the process of interaction design have gained the attention of both the industry and the scientific community. participatory User Experience design and the Democratization of Innovation in the early stages of the design process help us extend the understanding of designing User experiences for the users. Applying a user-centered design paradigm to designing with the users.

Desired course outcomes: After successful completion of the course, students will be able to


• ... prepare, plan and run PD workshops. • ... take advantage of ad-hoc solutions developed by individuals

and refine them into products • ... identify problems that users have assumed unfixable • ... actively involve real users in real-life settings to design for

experiences in the lived context

Teaching methods

• Presentations (pptx,pdf,prezi) • Online questionnaires • Quizzes • Videos • Collaborative work (Miro, Mural)


119. Vehicle Crash Mechanics and Biomechanics – Master´s level (IAE)

Language English Content The following topics are covered:

• Crash Modelling: o crash mechanics o Multibody modelling

• Finite element analysis • Biomechanics and traffic psychology Accident reconstruction and data analysis.

Objectives To develop the basic concepts and knowledge in crash mechanics and vehicle safety. The program is structured to cover the four important topics related to the vehicle crash: crash modelling, finite element analysis, biomechanics & traffic psychology and accident reconstruction & data analysis. At the completion of this course, students should be able to construct and simulate simple crash models, understand human anatomy and its mechanics during vehicle crash and investigate, analyse and draw conclusions about the causes and events during a vehicle collision.

Teaching methods



Basics knowledge of Mechanics, Matlab and Simulink.

Type of examination

Written exam (90-120 minutes)

Media LCD-projector, chalkboard, overhead projector, PC


M. Huang, Vehicle Crash Mechanics, CRC Press, 2002


120. Vehicle Dynamics – Master´s level (IAE)

Language English Content • Repetition of driving behaviour

• Repetition of tire behaviour, Kamm’s circle • Estimation of driving conditions based on sensor inputs • Necessary Hardware (hydraulics, specific sensors like yaw velocity,

wheel speed, ...) • Influencing driving behaviour by longitudinal slip (ESP, TCS, ABS) • Influencing driving behaviour by lateral slip (active steering) • Influencing driving behaviour by normal forces (active suspension)

Objectives The students … • shall know the physical possibilities how an active vehicle dynamic

system can influence the driving behavior of a car • shall understand how the software estimates the actual driving

condition, including the limitations of such estimations • shall be able to predict how different systems interfere • Being able to analyze and judge solutions

Teaching methods



none

Type of examination


Media LCD-projector, blackboard, computer demonstrations


To be determined


121. Wind Power


• Main different technological topologies of Wind Turbines • Mechanical design of a Wind turbine • Electrical design of a wind turbine • Aerodynamic design of a wind turbine • - Resource assessment

Objectives The Students: • Understand the basic principles of the Windturbines. • Understand Electrical and mechanical systems of Wind Turbines . • Calculate the main design variables of a turbine • Understand all the players involved in the industry of the wind

turbines. Grid operators, Maintenance, Park operators. • The students are able to present their creative ideas in working

groups and expose them.

Teaching methods

tbd


122. Wissensmodellierung und maschinelles Lernen

Language English Content • Grundlagen der statistischen Signalverarbeitung

(Zufallsvariablen, Bayes-Klassifikator, Bias-Variance Zerlegung, Merkmalsselektion)

• Lineare Klassifikations- und Regressionsmodelle (Herleitung, Umsetzung, Anwendungen)

• Support Vector Machines (Herleitung, Umsetzung, Anwendungen)

• Deep Convolutional Neural Networks (Herleitung, Umsetzung, Anwendungen)

• Ensemble Methoden, insbesondere Random Forest Algorithmus (Herleitung, Umsetzung, Anwendungen)

• Autoencoder (Herleitung, Umsetzung, Anwendungen) • Reinforcement Learning (Herleitung, Umsetzung,

Anwendungen) • Clustering- und Visualisierungsmethoden (Herleitung,

Umsetzung, Anwendungen) • Hardware für Deep-Learning Methoden • Anwendungen im Bereich des automatisierten Fahrens

Objectives Nach erfolgreicher Teilnahme an der Lehrveranstaltung sind die

Studierenden in der Lage,

• die mathematischen Grundlagen der statistischen Signalverarbeitung für die Wissensmodellierung und das maschinelle Lernen zu verstehen und anzuwenden

• klassische Methoden für Klassifikations- und Regressionsmodelle (lineare Modelle, Support Vector Machines, Entscheidungsbäume) mathematisch zu beschreiben, zu implementieren und anzuwenden

• fortgeschrittene Methoden des maschinellen Lernens (Deep Convolutional Neural Networks, Random Forest, Autoencoder, Reinforcement Learning) mathematisch zu beschreiben, zu implementieren und anzuwenden

• Clusteringverfahren und Methoden zur Visualisierung von Daten zu verstehen und anzuwenden

• die Methoden in Anwendungen für das automatisierte Fahren zu nutzen

Teaching methods

tbd


none

Study Programme for Exchange Students

Documents

Transcript of Study Programme for Exchange Students