Is Systems Engineering Ready For The Future

IEEE SoSE Conference – June 2018

1

Kerry Lunney CPEng EngExe ESEP INCOSE President-Elect Thales Australia Country Engineering Director / Chief Engineer

Complexity of Flight

2

Leonardo Da Vinci’s Human-Powered Ornithopter – ca 1485

Source: www.flyingmachines.org

Douglas A-20 Invader Source: acepilots.com

Source: www.wrightbro.com

Wright Brothers Kitty Hawk

Source: By Maarten Visser from Capelle aan den IJssel, Nederland - A6-EDY A380 Emirate s 31 jan 2013 jfk, CC BY-SA 2.0, https://commons.wikimedia.org/w/index.php?curid=56233674

A380-800 Emirates

Boeing 747-400 British Airways

Source: Wikipedia British Airways

Ariane 6 rocket, artist’s concept

Source: Spaceflight Now, April 9 2018

Apollo 11

Source: Apollo 11 Image Gallery, NASA

Space Shuttle Atlantis Source: Space Shuttle Image Gallery, NASA

European Space Agency Columbus Module Source: NASA

Burma Resorts

Source: Burma Resorts

Complicated Vs Complex?

Communication Advancements

3

Source: Thales

KONNECT VHTS – next generation VHTS satellite system, supporting the development of the European fixed broadband and in-flight connectivity business • A Thales satellite and ground segment solution • Will offer capacity allocation flexibility with its digital VHTS payload, optimal

spectrum use, progressive ground network deployment • Weigh 6.3 ton, Ka band capacity of 500 Gbps • Due to enter service in 2021

Source: Internet - feelgrafix wallpaper

Machines – Collaboration Or Competition • Over 90 Google Research papers

published in the last 4 years in Deep Learning alone

• Rapid acceleration on the use of deep learning at Google

Machine Learning Machines that learn to be smarter

Machine Intelligence Building smarter machines

Artificial Intelligence The science of making things smart

Source: https://research.google.com/pubs/BrainTeam.html Building the future with Machine Learning, Alexander Lynch

4

Machine learning isn’t magic… It’s just a new engineering tool set

Source: Alexander Lynch

Quick Outline

5

• Complexity On The Rise • Foundations of Engineering Systems • SE Creativity in the Future

• Boundary techniques, representations & transforming practices

• Critical focus areas • Case Studies

• New Horizons • CubeSatellites • Hyperloop

• Adaptation, Adoption & Collaboration • Learning from other disciplines • Organisation Connectedness

6

Complexity On The Rise Is Systems Engineering Ready For The Future

Complexity – Observed Trends (1 of 2) • Increasing Complexity of Systems • Increasing Rate of Technology Adoption

7

“With technology infusion rates increasing, the pressure of time to market will also increase, yet customers will be expecting improved product functionality, aesthetics, operability, and overall value. “

Source: INCOSE SE Vision 2025 Source: INCOSE SE Vision 2025

Complexity – Observed Trends (2 of 2)

• Increasing Connectedness

8

Complexity On The Rise – The Car

9

Source: Internet – WSP Mobility Banner for Autonomous Vehicles The car was not originally designed

with traffic jams in mind…

Exhibiting “Emergent Properties” Autonomous Transportation

Complexity On The Rise – Cities & IoT

• Smart Cities • Internet of Things (IoT)

10 Source: INCOSE SE Vision 2025

Complexity Characteristics

11

Source: Thales

12

Foundations of Engineering Systems Is Systems Engineering Ready For The Future

INCOSE - Systems Engineering (SE)

• Elements of SE: Enabling Achievement of Systems Solutions

13

- SE Competencies & Learning

- Technical Mgt - Technical Leadership

- Soft Systems

- Systems/SOS Thinking

- Technical Processes - Tools & Models - MBSE

- Domain Knowledge & Applications

- Systems Science

SE

Current SE Adoptions (1 of 2)

14

Functional Flow Block Diagrams (FFBDs)

Enh

ance

d FF

BD

s

Mis

sion

Sor

ties

Use Cases

Swim

lane

Dia

gram

s

N2 Diagrams

Interface Matrices

Context Diagrams

Meta Models

Dat

a Fl

ow D

iagr

ams

Sequence Diagrams

Operational Scenarios

Who

le o

f Life

Cyc

le C

osts

Kan

o M

odel

s

IDEF0 Diagrams

Behaviour Diagrams

Model Based Systems Engineering (MBSE)

Trade Studies

Analytical Hierarchy Processing

Technical Performance Measures Measures of Effectiveness

Prototyping

Simulation

Object Oriented SE Method

Pro

duct

Bre

akdo

wn

Stru

ctur

e

System of Interest Diagrams

State Transition Diagrams

Casual Analysis

Specialty Engineering Models

Req

uire

men

ts A

naly

sis

Requirements Traceability

Node Diagrams

Requirements Partitioning

Verification Cross Reference Matrices

Source: Sample Diagrams from Thales

Current SE Adoptions (2 of 2) • Development Life Cycles

– Waterfall – The V Model – Incremental – Evolutionary/Iterative – Spiral – Agile – Lean – Product Line Engineering

• Architectures – Open Architectures – Protocols & Standards – Architecture Frameworks &

Viewpoints – Logical & Physical Models – Mathematical Models – Schematic Models

15

11

1 2 311 22 33

1 2 311 22 33

Waterfall - V

Incremental

Iterative NAF V3 – Simplified Meta Model

16

SE Creativity in the Future Is Systems Engineering Ready For The Future

SE CHALLENGE • Adapt Foundation SE

Practices • Utilise boundary

techniques, representations & transformation practices

• Increase focus on Resilience & Human Systems Integration (HSI)

SE & Cynefin Framework Alignment

17

BEWARE! • Identify concepts &

techniques to move out of this space

Join INCOSE Complex Systems Working Group

CURRENT SE ADOPTION • Embrace Foundation

SE Practices • Apply the Library of

Tools & Applications • Implement appropriate

Development Life Cycle(s)

Possible System Approaches • Embrace New/Adapted Techniques -

– Complexities have always existed • Build on your Engineering

foundations – Dynamics in complexity are

constantly changing – Tools & techniques are constantly

evolving – • Model based Engineering • Digital Engineering • Digital transformation • Simulations • Prototypes eg mock-ups, rapid

prototypes • Performance models • Tool selections • etc

18

• Deterministic • Linear • Predictable

• Non-Deterministic • Evolutionary • Stochastic

Boundary Techniques (New/Adapted)

19

• Contain vs Control • Transference • Views & Viewpoints • Think holistically -

• Complement reductionist activity • Time awareness –

• Change over time • Impact of delays • Short term vs long term

Use Case: “Road” Transportation

Source: Airbus – Drones to Carry Cars

Emergent Property – Traffic Jams

Representations (New/Adapted)

20

• Systems Thinking • Model Based Systems Engineering • Digital Engineering • Patterns & Anti-Patterns • Behaviour Equivalency • Unintended Consequences

Use Case: Smart Cities - Connectedness

Transforming Practices

Positive Effects - • Improve productivity • Operate continuously • Increase information sharing • Process tremendous volume of data • Work where we cannot safely go Negative Effects – • Emergent behaviour • Continuous change • Human/machine interface • How to do Verification & Validation (V&V) • Trust • Attack vulnerabilities • Unemployment • Unintended changes to other businesses • Ethics • Issues from new interfaces • Information overload

21

• Collaborative Engineering • Complex System Understanding • System of Systems Engineering • System Architecting for multiple

viewpoints • Composable Design • Design for Resilience • Design for Security – system integrity • Decision Support • Virtual Engineering and MBSE – part of

the digital revolution • Change of process implementation to

address technology & application • Tailoring and scaling practices for value

Use Case: Autonomous Systems

Source: Heather Kelly Photo, CNN Internet Article

Source: Sophia, The Economic Times, India

Source: Internet, Sleepless Sentries Giant Ant – Animatronic Movie Study

Are we ready to deal with these new issues?

Source: Paul Nielson, “Systems Engineering & Autonomy, Opportunities & Challenges; INCOSE IS2017, Keynote Speaker

Importance Of Interoperability In The Future Future Interoperability Considerations - • Continuously evolving through the need of

connectedness • Missions may be independent from each other • Governance may present issues • Vast libraries of data are available • Scalability is essential • Leveraging new technologies as well as integrating

old/existing technologies is critical • Virtualisation, MBSE, digital transformations are

integral

22

It is not necessary to change. Survival is not mandatory. (W. Edwards Deming)

Inte

rope

rabi

lity

Source: Thales

uncertainty

Interoperability + Uncertainty Focus on Resilience & Human Systems Integration

Critical Focus Area - Resilience • Resilience is the ability to prepare and plan for, absorb or mitigate, recover

from, or more successfully adapt to actual or potential adverse events (INCOSE SE Handbook V4.0)

23

Attribute Ability to… Resilience examples Capacity …withstand a threat • Multiple branches (Physical redundancy)

• Different and independent branches (Functional redundancy) Buffering …maintain a distance from boundary

of unsafe operation or collapse • No single point of failure (layered defence) • System can reduce number of elements / interfaces • Capable of detecting hidden undesirable interactions amongst its elements

Flexibility …bend or restructure • System capable of restructuring itself after a threat (reorganization) • System capable of repairing itself following a disruption (repairability)

Adaptability …prevent the system from drifting into unsafe behaviours

• Capable of detecting approaching threat and performing action in response • System capable of entering neutral state to allow decisions to be made • Human in the loop where needed • System resistant to cascading failure - slack and delays at nodes (loose coupling)

Tolerance …degrade gracefully • Individual elements of a system capable of independent operation following failure of other elements (localised capacity)

Cohesion …of elements of a system to operate together as a system

• System has connection between its nodes

How Resilient

Source: INCOSE SE Handbook V4.0, adapted for Thales Training

Critical Focus Area – Human Systems Integration (HSI) • Human systems integration (HSI) is the interdisciplinary technical and

management process for integrating human considerations within and across all system elements. (INCOSE SE Handbook V4.0)

24

HSI Domain Definition Manpower • Numbers and types of personnel, including any speciality occupations required Personnel • Knowledge/Skills/Abilities (KSA), experience and aptitudes required, gap analysis Training • Resources and system required to provide personnel with requisite KSA

• Associated skill enhancement options and training systems Human factors Engineering HFE

• Requires understanding of cognitive, physical and sensory human capabilities • Involves task and function analysis, design trade-offs • Maximise usability for targeted users and reduce design characteristics that induce frequent errors

Environment • Consideration of environmental factors affecting human performance Safety • Promoting design characteristics that minimise risk of accidents (e.g. safety of operators, working/walking

surfaces, emergency egress, pressure and temperature extremes, prevention of hazardous energy releases) Occupational Health

• Minimising injury, illness and disability (and enhance performance) when using / supporting the system (e.g. noise, skin, vibration/shock radiation protection, repetitive motion protection)

Habitability • Working conditions (e.g. lighting, ventilation, space, personal hygiene factors etc.) Surviveability • Reducing susceptibility to injury, loss of life or mission failure (e.g. life support, body armour, plating, seat belts)

Source: INCOSE SE Handbook V4.0, adapted for Thales Training

How Human

25

Case Studies Is Systems Engineering Ready For The Future

Case Study - New Horizons

26

Furthest Image

Source: NASA New Horizons Photo Gallery

Launched in 2006, New Horizons space probe sent back photos from 6.12bn km away in the Kuiper Belt – the furthest

pictures every taken from earth (top right photo)!

New Horizons – The Systems Challenge A Systems Challenge - • Interrelationships

– Interfaces – Exchanges (physical,

power/electrical, data, controls) – Time / spatial awareness

• Emergent Properties – Science – Social – Engineering/Technology

• Resilience • Autonomy/Human System

Integration • Reliability & Longevity • And many more…

27

Source: NASA New Horizons Photo Gallery NASA/John Hopkins University

New Horizon

Spacecraft Systems

Structure

Command & Data Handling

Thermal Control

Propulsion

Guidance & Control

Communications

Power

Mission Systems

Ralph (Visible & Infrared Imager/Spectrometer)

Alice (Ultraviolet Imaging Spectrometer)

REX (Radio Science Experiment)

LORRI (Long Range Reconnaissance Imager)

SWAP (Solar Wind Around Pluto)

PEPSSI (Pluto Energetic Particle Spectrometer Science Investigation

SDC (Student Dust Counter)

Base (Earth) Systems

Operational System

Training System

Case Study - CubeSatellites

28

Source: Internet, BISA

Picasso CubeSat (PICosatellite for Atmospheric & Space Science Observations Cubsat) • Designed to investigate the upper layers of Earth’s

atmosphere

Source: Internet, NASA

CubeSats released in 4 Oct 2012, from Kibo Lab on the International Space Station

CubeSat Reference Model (CRM)

Project Objectives • Demonstrate Model Based

Systems Engineering (MBSE) methodology as applied to a CubeSat mission

• Provide a CRM that CubeSat teams can use as a starting point for their Mission-specific CubeSat model (MCM)

• Develop the CRM as an Object Management Group (OMG) specification

29

Source: INCOSE Space Systems Working Group (SSWG) CubeSat MBSE Reference Model – Development & Distribution – Interim Status #3 Presentation

Join INCOSE Space Systems Working Group

Examples of In-Work MBSE of CRM (1 of 4)

• Architecture • CubeSat Mission Enterprise

30 Source: INCOSE Space Systems Working Group (SSWG) CubeSat MBSE Reference Model – Development & Distribution – Interim Status #3 Presentation

Examples of In-Work MBSE of CRM (2 of 4)

• CubeSat Subsystems • Ground Segment

31 Source: INCOSE Space Systems Working Group (SSWG) CubeSat MBSE Reference Model – Development & Distribution – Interim Status #3 Presentation

32

Source: 2017 IEEE Aerospace Conference – A MBSE Approach for Defining the Behaviours of CubeSats

Examples of In-Work MBSE of CRM (3 of 4)

• Collect Mission Data Activity Hierarchy

Examples of In-Work MBSE of CRM (4 of 4)

• Decomposition diagram • Related activity diagram

33 Source: 2017 IEEE Aerospace Conference – A MBSE Approach for Defining the Behaviours of CubeSats

CubeSatellites – Space Clutter Challenge Complexity Sets In: Space Traffic Management - • Kessler Syndrome –

– The density of objects in Low Earth Orbit (LEO) is high enough that collisions between objects could cause a cascade where each collision generates space debris that increases the likelihood of further collisions. – “A domino effect”

• Options – – Predict and mitigate (now & future)

• Track and deflect (lasers, satellite nets, etc) • Track and orient and re-position (use in-built

propulsion systems) – De-orbit CubeSats at the end of their mission

(use in-built propulsion systems) • Bonus – frees up orbital slots for others

• As Systems Engineers – – Think holistically – Model various viewpoints – Adapt & Transform

• Our MBSE approach for the CRM can be adapted and expanded to address this challenge!

34

Source: Adapted from photo from NASA New Horizons Photo Gallery; CubeSats added, representative only, not to scale

Source: Figures quotes from Peter Farquhar, 30 Jun 2017, “How the nanosatellite boom and battle for space could end in disaster for us all”

• 2007-2016: 1100-1500 functioning satellites + 20000 pieces of debris 10cm or bigger

• 2017:1430-1950 functioning satellites (30% increase in 1 year)

• 2018 onwards : Satellite swarms begin • 2020: Approximately 20000 satellites orbiting Earth

What If = New Horizons + Space Clutter Options - • A new mission system • Big Data Analysis • Interoperability with

– Existing satellite orbit systems

– Existing laser systems • Interfacing to satellite

Health & Usage Monitoring Systems (HUMS)

• ….

35

New Horizon

Spacecraft Systems

Structure

Command & Data Handling

Thermal Control

Propulsion

Guidance & Control

Communications

Power

Mission Systems

Ralph (Visible & Infrared Imager/Spectrometer)

Alice (Ultraviolet Imaging Spectrometer)

REX (Radio Science Experiment)

LORRI (Long Range Reconnaissance Imager)

SWAP (Solar Wind Around Pluto)

PEPSSI (Pluto Energetic Particle Spectrometer Science Investigation

SDC (Student Dust Counter)

Base (Earth) Systems

Operational System

Training System

Space Clutter System

Source: Adapted from photo from NASA New Horizons Photo Gallery; CubeSats added, representative only, not to scale

Case Study – Hyperloop: Disruptive Or Not Systems Challenge – • Autonomous transportation

projects are silent on this potential disruptive technology

• Environmental considerations not satisfactorily addressed

• Human systems integration limited to date

• Track/tube material sensitivity • Trust • Integration into existing

transportation networks

36

Source: Internet - Hyperloop Transportation Technologies

Source: The Weekend Australia Article 2016

Hyperloop – Actors & Interoperability

37

SOI = System of Interest

L SOI Wider SOI Environment

Wider Environment

Corridor Security

Pipe Corridor

Comms/ Satellite

Pipe Infrastructure

Passengers Freight

HUMS

Existing Transport Corridors

Transport Policy

Environmental Laws

Crossings

Trains

Planes

Cars

Stations

Service Centres

Operational Centres

Suppliers

Land Owners

Hyperloop

Ground System

Pod System

Pipe System

Maintenance System

Passenger Wear

Power Source

The ultimate success of the system depends upon “systems’ beyond the SOI

– a SoSE problem

Legislation

Healthcare Policy

38

Adaptation, Adoption & Collaboration

Is Systems Engineering Ready For The Future

Cone Of Plausibility Adaptation

How do we move to Predictable? • Scenarios – eg

– look for interoperability impacts – “Test” under alternate environments

• Modelling – focus on – Resilience – Security – Agility – Flexibility

• Search for those “unintended consequences”

• Assume technology evolutions will happen

• Ask what if/why , again and again • And more…

39

Preposterous

Possible

Plausible

Probable

Source: Voroscope: Adapted from Voros (2003)

Past Present Expected Future

Predictable? Future Solution Trajectories – Prediction impossible but desirable

VUCA Adaptation

40

Volatility Uncertainty

Complexity

Ambiguity

Patterns Innovation/Creativity Agility & Flexibility

Minimal Viable Product Resilience

Human Systems Integration Behaviour Equivalency

Machine Learning Digital Twin Modelling

And more…

Think Big-Start Small-Learn Fast Adoption

41

Source: Internet, Devil’s Advocate Group Article by Chunka Mui, Forbes 3 Jan 2016

Minimal Viable Product (MVP)

Psychological Safety

Agile/Lean Approaches

Experimentation

Collaboration

Trusted Organisation Mindset

Systems Thinking

Design Thinking

Or Scale Fast Or Act Fast

“SE Of The Future” – New INCOSE Collaborative Initiative • Intended to address threat – “Adapt or become irrelevant” • Intended Outcome – Evolving application of SE that enables

us to leverage the new technologies that drive us fully into a dynamic, nondeterministic, and evolutionary environment

• Draft Framework – – Define problem statement – Define the challenges that will drive change – Identify impacts to SE – Establish roadmap – Initiate actions, projects, research, and

benchmarking

42

“SE Of The Future” A Systems World Perspective Of Context

Environments

• Ecosystems– Natural & Artificial/Manmade

• Economical Environment • Political Environment • Health Environment

Technological Advances • Artificial Intelligence (AI) • Autonomy • Big Data • Internet of Things (IoT) / Smart

Things • Smart X (eg Smart Cities) • Cloud Computing • Ubiquitous Access to

Information • Power/Energy • Augmented Virtual Reality • Simulation/Stimulation • Sustainment/Elegant Systems • 3D Printing • Cyber-Physical Systems • Ability to find Unique (Old) via

eBay, Amazon, etc

Domains

• Defense • Space • Healthcare • Games – serious games • Transportation • Communications • Information • Consumer Electronics • Public Policy • Biomedical • Housing • Infrastructure • Power & Energy

System Science & SE Foundations • Processes, Methods &

Guidelines • Models & Tools • Standards • Tailoring Guidance • System Research & Theories

System Science & SE Foundations

Technological Advances

Environments

Domains

43

“SE of the Future” – Collaboration Alliances • AIAA • IEEE Systems Council; Computer

Society; Systems, Man, and Cybernetics Society

• IIE (UK) • ISSS • INCOSE • ITEA • MORS • NDIA • PMI • US DoD • TTCP (The Technical Cooperation

Program – Australia, Canada, New Zealand, UK, US)

• EU Commission

• Embedded Systems Institute (Netherlands)

• Fraunhofer Center for Experimental Software Engineering (USC)

• INCOSE Academic Council (collaborative association, not individual universities)

• INCOSE Corporate Advisory Board (TBD)

• JHU APL • Software Engineering Institute (CMU) • Systems Engineering Research

Center (SERC) University Affiliated Research Center (UARC)

• Others? Are you interested?

44

Source: Internet NASA International Space Station Photos

Represented at 19 Jan 2018 Strategy Session

Don’t Forget - Consider Worldwide Dimensions

45

Today’s Connectedness

? Tomorrow’s Connectedness

OR

…And Those Black Elephants

46

SE future readiness will need…

Project Management

Contract Management

Lifecycle Changes

Risk Management/Trust

Collaboration Boundaries

Strategic Management

Supply Chain

Acknowledgements-References-Copyright Acknowledgements • The material for this course is reproduced with permission from -

– INCOSE – Thales – Charterhouse Systems Ltd (developer of the Thales INCOSE Bootcamp

material) • Material for this course includes reproduction of figures and tables

contained within the – INCOSE (2015). Systems Engineering Handbook: A Guide for System Life

Cycle Process and Activities (4th Ed.) – INCOSE (2014) . A World in Motion, Systems Engineering Vision 2025 – INCOSE Space Systems Working Group – Thales website

• Any use of this material, for external purposes must be agreed to with Thales Australia and INCOSE

References • INCOSE (2014). A World in Motion, Systems Engineering Vision 2025 • INCOSE (2015). Systems Engineering Handbook: A Guide for System Life

Cycle Process and Activities (4th Ed.). D. D. Walden, G. J. Roedler, K. J. Forsberg, R. D. Hamelin, and, T. M. Shortell (Eds). San Diego, CA: International Council on Systems Engineering. Published by John Wiley & Sons, Inc.

• INCOSE (2014). Guide to the Systems Engineering Book of Knowledge (SEBoK 2014)

• CubeSat Model-Based Systems Engineering (MBSE) Reference Model – Development and Distribution – Interim Stats #3; D Kaslow, INCOSE, Space Systems Working Group (SSWG)

47

SE Vision 2025 Copyright (for Vision extracts)

48

For INCOSE related information or to share ideas contact:

Kerry Lunney Garry Roedler INCOSE President-Elect INCOSE President kerry.lunney@thalesgroup.com.au garry.j.roedler@lmco.com