Virtual Technology in Operator TrainingWithin Manual Assembly Processes

JAKOB ROLENERIK LINDVED

Degree Project in Product Realisation and Industrial Engineering (15 credits)Degree Programme in Industrial Engineering and Management (300 credits)

Royal Institute of TechnologySchool of Industrial Engineering and Management

KTH ITMSE-100 44 Stockholm, Sweden

Abstract

The manufacturing industry faces complex challenges, and is forced to con-stantly develop to encounter the increased global competition. This thesisexamines if virtual technology can be used to make assembly processes moreefficient. The technologies Virtual Reality (VR) and Augmented Reality (AR)are examined. The thesis is based on two parts: a literature review and a casestudy. The results show that there are benefits of VR and AR, these rangefrom off-line training, cognitive perception and mass training to cost savings,product and operator feedback and ability to encounter product and volumefluctuations. But, there are limitations including the need for physical trainingand vast space demands. However, the conclusion shows that there are severalproduction benefits of VR and AR in operator training.

Sammanfattning

Idag star tillverkningsindustrin infor nya utmaningar, och det stalls hoga kravpa att standigt effektivsiera processer for att mota den okade globala konkur-rensen. Denna avhandling utreder hur virtuell teknik kan anvandas for atteffektivisera upplarning av montorer i industrin. Detta i syfte att utreda hu-ruvida tekniken kan anvandas for att forbattra produktionsprocessen. BadeVirtual Reality (VR) och Augmented Reality (AR) har undersokts. Arbetetutgors av en litteraturstudie samt en intervjustudie. Resultaten fran dessa visaratt tekniken kan anvandas for att underlatta hantering av produkt- och volym-flexibilitet, skapa kommunikationsvagar mellan FoU och montering samt attinlarning av framforallt kognitiva fardigheter gar snabbare. Tekniken har ocksavissa begransingar da virtuella traningssystem kan vara utrymmeskravande pagrund av all kringutrustning. Dessutom finns det alltid ett behov av fysisktraning. Slutsatsen av arbetet ar att det finns en potentiell framtida anvand-ning av virtuell teknik for att effektivisera produktionsprocessen.

Acknowledgements

We thank Bita Daemi, Royal Institute of Technology, for methodology guid-ance and comments that greatly improved the thesis, and Bo Karlsson, RoyalInstitute of Technology, for assistance with methodology as well as forming theresearch focus. We would also like to show our gratitude to Lars Hanson, Scania;Ivan Radulovic, Volvo Trucks; Pontus Jensson, Scania, and Andrea de Giorgio,Royal Institute of Technology, for sharing their expertise with us during thecourse of this research. We are also immensely grateful to anonymous reviewersfor their comments on earlier versions of the manuscript. We take full respon-sibility of potential errors in this thesis, these esteemed persons should not beheld responsible.

Contents

1 Introduction 11.1 Staying Competitive in a Modern World . . . . . . . . . . . . . . . 11.2 Objective . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.3 Research Question . . . . . . . . . . . . . . . . . . . . . . . . . . . 31.4 Delimitations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41.5 Definitions of Central Concepts . . . . . . . . . . . . . . . . . . . . 5

1.5.1 Manufacturing Industry . . . . . . . . . . . . . . . . . . . . 51.5.2 Digital Factories, Virtual and Augmented Reality . . . . . . 6

2 Method 72.1 Approach I: Literature Review . . . . . . . . . . . . . . . . . . . . . 72.2 Approach II: Case Studies . . . . . . . . . . . . . . . . . . . . . . . 8

3 Literature Review 93.1 Operator Skill Requirements . . . . . . . . . . . . . . . . . . . . . 93.2 Hardware and Software Requirements . . . . . . . . . . . . . . . . 113.3 Integration and Interface Design of VR and AR Systems . . . . . . 143.4 VR and AR Systems vs. Traditional Methods . . . . . . . . . . . . 163.5 Industrial Management Perspective . . . . . . . . . . . . . . . . . . 19

4 Case Studies 204.1 Current Operator Training at Volvo Trucks . . . . . . . . . . . . . . 204.2 Current Operator Training at Scania . . . . . . . . . . . . . . . . . 224.3 Research within Virtual Operator Training at Scania . . . . . . . . . 23

5 Results 25

6 Discussion 286.1 Which technology is more promising: VR or AR? . . . . . . . . . . 286.2 Does VR and AR increase manufacturing performance? . . . . . . . 306.3 Methodology Criticism and Areas for Further Research . . . . . . . 32

7 Conclusion 33

8 Bibliography 34

9 Appendices 369.1 Appendix I: Questionnaire A . . . . . . . . . . . . . . . . . . . . . 369.2 Appendix II: Questionnaire B . . . . . . . . . . . . . . . . . . . . . 379.3 Appendix III: Interviewees . . . . . . . . . . . . . . . . . . . . . . . 38

1 Introduction

1.1 Staying Competitive in a Modern World

The current age of globalisation, technological development and increased com-petition forces companies among all industries to constantly develop themselvesand adapt to new changes. At the same time, the demand for customised prod-ucts has increased, and price levels have harmonised all over the world. It ismore important than ever to find ways to produce attractive products to a lowcost.

However, the willingness to increase efficiency has always been present. Thishas been driving the manufacturing industry forward, thus emerging paradigmshifts. Three industrial revolutions played a critical role in the evolution ofmanufacturing industry [1].

• The possibility to use the power of steam engines

• The discovery of electricity

• The usage of electronics

These three revolutions laid the foundation for modern manufacturing compa-nies. Ever since, the development of internet information and network collab-oration has grown to be of outermost importance. Today, it is not enough toautomate and standardise the workflow. There must be a digital connectionbetween the different production steps, machines and units.

Due to the digitalisation, the principles of manufacturing are rapidly changingand the concept of Smart Factories is emerging. The factory should no longerbe just a producing unit with humans handling the interactivity between theprocesses, the factory must be able to think and communicate on its own.

In 2011 the German government concretised and conceptualised the fundamen-tals of the smart factory. They gave it a name insinuating a fourth industrialrevolution: Industry 4.0, illustrated in Figure 1. The concept is built on threemain pillars: Internet of Things, Cyber-Physical Systems and Cloud Comput-ing. These three fundamentals was considered as the most critical areas whichthe modern company should focus on in the era of digitalisation [2].

One component of the modern factory is the ability to digitalise and simulatemanufacturing processes. This concept is commonly known as Digital Factories.The simulation technology enables editing and configuration of, for instance,production lines and workstations without actual changes in the physical world.Therefore, testing and training, can be done without causing interruptions inthe production.

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Figure 1: The four major industrial revolutions [3]

Traditionally, operator training within assembling has been done either directlyin action on the production line or at physical separate training stations. Thesemethods require resources in form of personnel, equipment and can, if the train-ing is done in an active production line, affect the quality and flow of products.

The idea of training in a simulated virtual environment is to enable the operatorto train off-line. This means training out of the production line, and doesthereby not affect factory output. Since the training is virtual, no materialis wasted and no machines are damaged. Thus, virtual training systems showgreat potential in increasing efficiency. This is a necessity to stay competitivein the modern world of globalisation and digitalisation, and what this thesisexamines.

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1.2 Objective

The objective of this thesis is to determine whether virtual simulation can im-prove operator training within manual assembly lines. VR and AR are comparedto traditional operator training from several perspectives, explained in detail be-low. Also, the future outlook within the area, and the costs benefits associatedwith implementing the technology are examined.

The results are based on a literature review and case studies, which connectacademic results with the current status in the industry. This research is donewith the purpose to give producing companies and academia an understandingof the fundamentals of the emerging virtual technology. Actors can use theresearch and conclusions as a reference basis in R&D and in decisions concerninginvestments in techniques for operator training.

1.3 Research Question

Objective and constraints taken into consideration, the main research questionis: What are the benefits of VR and AR in operator training? The thesis isdivided into the following sub-questions:

• Which technology is more promising: VR or AR?

• Does VR and AR increase manufacturing performance?

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1.4 Delimitations

Since the topics of VR and AR are broad and cover a wide range of implemen-tations, which all cannot be covered in this thesis, three constraints were takeninto account:

• Focus will be on producing companies within assembly manufacturing.Traditionally, this area has more manual elements than process manufac-turing does, and also is hard to automate.

• The area of assembly manufacturing consists of several parts, among thecontent of this thesis is constrained to operator training.

• Applications of VR and AR outside operator training will not be examinedin this thesis, although there are many other applications.

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1.5 Definitions of Central Concepts

1.5.1 Manufacturing Industry

There is a distinction between assembling and processing, and Industry 4.0 isapplicable on both. Assembly manufacturing is where different components areput together to an actual product. An item is typically moved sequentiallyalong workstations while parts and components are added until the product iscompleted. The assembly line can be more or less automated, ranging from aline completely free from human interaction to pure manual labour.

Process manufacturing is typically when the relevant factors are ingredients,rather than parts. This manufacturing method is often fully automated. Incontrast to process manufacturing, assembly manufacturing is usually a combi-nation between the exorbitances mentioned above. But during the last decadesan automation trend has spread through companies with assembly lines.

Mainly, this is an effect of high labour costs in the Western world. In order toautomate the assembly process the worktasks must be repetitive and the com-ponents easy to put together. This has risen the requirements on the productsand concepts as Design for Assembly – DFA has been developed [4]. The de-sign of the products has not only an aesthetic purpose, they must also facilitatethe assembly process. This demands collaboration between the design and theproduction departments [4].

Manufacturing companies usually cuts costs by increasing efficiency and de-creasing manual labour. Robots never get tired, bored or neglectful. Neither,they demand overtime compensation or vacation. But, there are many indus-tries where manual labour is necessary due to complex products and a demandof high flexibility. The operator and its knowledge has a crucial role in theseindustries.

Even though the automation trend has grown there is still one main problemthat companies encounter: the demand for customised products. Customisa-tion requires flexibility in the production line which makes standardisation andautomation hard, and costly to implement [4]. Due to this fact, the manuallabour still plays a critical role in most manufacturing companies and will mostlikely do for a foreseeable future.

If one accepts the fact that human involvement have to be a part of the assem-bly process, the need for efficient ways of developing skilled operators becomesobvious. This is why digital factories, virtual reality and augmented reality areinteresting subjects with potential upside for manufacturing companies.

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1.5.2 Digital Factories, Virtual and Augmented Reality

Virtual Reality – VR is generally defined as a computer simulated, interactive3D environment which responds to the actions of the system user. To buildthe virtual environment, interactive software and hardware is required. Thehardware is typically made up by sensors to track the user’s motions togetherwith a visualisation screen [5]. The main idea of the technology is to enable theuser to interact with a virtual world.

Although many applications of VR has been within entertainment, the technol-ogy has been proved to be useful in other fields such as education, military, andmedical training [6]. The technology enables training of inexperienced personswithout the real life consequences of failure, and this is why the military andhealth care are such early adopters.

Training in both professions is generally considered to be risky and the VRsimulation eliminates this element. With VR it is also possible to repeat specificpatterns and situations in order to concentrate the training on specific tasks.Moreover, it allows the user to collect data regarding the user’s motions. Thisdata enables in depth studying of the trainees’ performance.

Augmented Reality – AR is typically referred to as a combination between thephysical reality and a simulated virtual reality. The physical reality is said to beaugmented with computer generated virtual objects. As VR, AR systems are acombination of hardware and software. The hardware is typically a collectionof displays, sensors and input devices. AR software can be run on for examplesmart phones, tablets and smart glasses using cameras to perceive the physicalreality. The virtual objects is then added on the screen of the device [5].

With a wide range of applications, VR and AR has already been establishedin assembly lines of many companies such as BMW, Boeing and Volkswagen[7]. In these certain cases, the technology has been used mainly as improvedinstruction manuals for operators. For example, to clarify the work process forthe operator, additional virtual information is displayed to him or her.

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2 Method

To investigate our research question, the focus is on two approaches: literaturereview and case studies. The two approaches are described in detail below.

2.1 Approach I: Literature Review

The objective of the literature review is to give a broad understanding of up todate research focusing on operator performance using VR and AR technology.The examined literature enables a comparison between the scientific facts andconclusions to the current implementations in the Swedish industry. By studyingcurrent research, one is able to identify gaps in the research area which needto be filled. The search for literature has been done according to the followingcriteria:

• The references have to specifically treat technology referred to as VirtualReality or Augmented Reality.

• The references shall describe VR and AR implemented only for trainingof manual tasks. General simulation of, for instance, machine operationsare therefore left out.

• The references must contain information relevant to at least one of thesub-questions stated in section 1.3.

Since there are many forms of simulation, this thesis has chosen to excludeall references not containing technology referred to as VR or AR. The thesiswill only present specific results of the technology examined, therefore generalsimulation is left out.

References describing implementation of VR and AR used to improve manualskills are all included. According to this, technology to train operators in forexample repair and maintenance, is included since these type of tasks are similarto the tasks performed within assembly. Further on, VR and AR used to trainmachine operators is not included since these processes differs too much fromthe topic examined.

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2.2 Approach II: Case Studies

The objective of the case studies is to compare the results found in the literaturewith the current practice in the industry. The case studies focus on the Swedishtruck industry in general, and Scania and Volvo Trucks in particular where aseries of interviews were conducted. The Swedish truck industry is chosen asfocus due to its high concentration of assembling operations. The industry isprogressive, but not in the frontier. Thus the findings from the industry can begeneralised to several other industries.

The interviewees were selected in various ways. Contact with Lars Hanson wasestablished through a recommendation from the faculty. One of the authorshas done an internship under supervision from Pontus Jensson and therebyestablished contact. And the interview with Ivan Radulovic was the result ofcold calling major Swedish manufacturing industries. All three interviewees aredescribed in detail in Appendix III.

The interviewees were chosen due to their current role within the manufacturingindustry. Hanson represents the research frontier of the Swedish truck industry.Jensson and Radulovic were chosen to be representatives for the current industrypractice within operator training.

The interview sessions were semi-structured. Meaning the questions asked dur-ing the interviews were broad in order to receive general answers concerning thecurrent industry status. This includes a disadvantage of obstructing a deeperand more narrow focus. The questionnaire used for the interview with LarsHanson is provided in Appendix I, and the questionnaire used for the remaininginterviews in Appendix II.

The interview with Hanson was conducted at Scania’s production plant inSodertalje, making it possible to get a deeper understanding for products andtools. Radulovic was interviewed through Skype, and was thereby able to showus PowerPoint slides supporting the statements. The interview with Jenssonwas carried out through an ordinary telephone call.

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3 Literature Review

3.1 Operator Skill Requirements

Malmkold et al. state that assembly operators need both cognitive and crafts-manship skills to fully master a sequence of assembly operations. These skillsare acquired through knowledge in four main areas: product, process, assemblysequence and finesse [8].

Knowledge Phases Cognitive Training(Computer-based Training)

Craftsmanship Training(Physical Training)

Product Product shape, special features,differences between different vari-ants, used fasteners α

How to handle, i.e., grip positions

Process Interface parts, ”third hand”,placement in car, needed equip-ment & tools, and how they in-teract with parts, functionalityof equipment & tools, qualityor safety demands, tightening se-quence demands

Fitting in, adjustment, assemblypath, tool path, handling of tools

Assembly sequence Knowledge about valid sequencesfor different variants on differentstations

Performance of operations in rightsequence with right quality withinavailable cycle time

Finesse Knowledge about quality issues,i.e., things to have in mind whenperforming and why it is impor-tant to perform the operation ina certain way

Performance of operations in rightsequence with right quality withinavailable cycle time but also withfinesse care included γ

Table 1: Assembly operator skills [8]

As shown in Table 1 above, the process starts with product knowledge markedas α. The end of the process is denoted by the γ. The learning process iscomplete when the operator is able to assemble with sufficient quality withinthe time constraints together with the finesse care.

The product knowledge constitutes of the understanding of how the productsworks, the variation between different product types and how the product shouldbe assembled. The process knowledge is made up by an understanding of howthe component should be positioned, which tools that are required and othernecessities for a successful assemblage.

The assembling sequence requires cognitive skills in order to remember the as-semblage sequence. The trainee also needs to perform the assemblage sequencewith sufficient speed, this can be defined as craftsmanship knowledge. Thecraftsmanship skills also include a habit of using tools. The trainee must knowhow to use the tools and be able to follow the correct tool path. A sense of howa detail behaves, how it feels and how much it weights is also necessary. Anoperator also have to be able to adjust the details into the correct position and

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fit them correctly.

The final results of the assembly process depends very much on the operatorsskill in performing the assembly tasks. This final skill is the factor which influ-ences the output quality of the product the most. This thesis assesses the virtualtechnology from how it affects the learning factors described in this section.

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3.2 Hardware and Software Requirements

The virtual reality allows the user to experience a full synthetic world by tak-ing a ”step through the computer screen into a three-dimensional (3D) world”[9]. In this world, the operator can look, move and interact with the virtualenvironment. The output is given by visual and haptic devices where the mostcommon devices providing visual output are known as Head-Mounted Displays– HMDs [9]. Figure 2 shows some examples of HMDs.

Figure 2: The most prominent wired HMDs [9]

The system mentioned above takes input from body tracking and navigationdevices. The navigation devices creates an illusion of moving through an end-less space by using Omnidirectional Treadmills1 [9]. Even though this form oftraining has proven effective, the technology lacks some crucial aspects. TheVR technology does not allow the user to have physical contact with simulatedobjects, thus a dimension of high importance is lost. It is also difficult to modela physical world with full accuracy [5].

An augmented reality is allowing user interaction with physical objects. Thereis no need to simulate a whole environment since AR consists of the physicalworld, augmented with digital features. The digital features makes it possibleto display complex information and provide user guidelines. The technology iscurrently being incorporated in various fields due to its usefulness. These fieldsare ranging from medicine, entertainment, education and art to engineeringdesign, military, maintenance and repair [10].

A general requirement list for a fully functional AR system is described byWang et al. [5]. Just like VR, AR is usually visualised by HMDs, but canalso be displayed by Hand Hold Displays – HHDs. Besides visualising immerseenvironments, the displays are equipped with RGB-D cameras which enablesintuitive hand-based interaction [11]. The possibility to interact with the aug-mented reality and virtual objects without sensors is one of the major benefitswith AR.

In addition to the display and camera, a physical workspace, with tools andassembling parts is needed. With these modules in place, data can be sent to aprocessing unit handling the information and rendering augmentations based on

1A treadmill allowing the user to walk in any direction without changing position

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the input. The rendered augmentation is then sent to the visualisation moduleand a loop is created. A more detailed explanation can be seen in Figure 3.

Figure 3: Visualisation of AR-loop [5]

One additional item that can be included in the VR or AR system is a hapticbracelet that uses vibrations to give feedback and hints to the user’s motions.This device gives an additional channel of communication that increases thepedagogical tool box. For example, small and complex hand movements, likerotational directions of the hand, could be hard to learn through video or textinstructions. These movements could be taught through haptic devices instead[12].

Nee et al. summarise the current status and implementation possibilities ofVR and AR technology [13]. The authors describe the 3D natural bare handaugmented reality which allows the user to move digital visual objects with hisor her hands. This technology will allows a novice operator to train assem-bling workprocesses and, according to the article, case studies has proven thetechnology to shorten the learning curve for users.

The article also states four main areas within VR and AR where development isneeded for further expansion of the technology. First of all the tracking accuracyof the hardware devices is crucial for advanced implementations. The authorsstate that laser tracking have to be used in the future to assure enough precision.There must also be technology in place which converts visual information intothe augmented reality systems. This, as with the movement tracking, requires

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accurate sensors to register the physical world.

The third critical issue is the problem of latency. AR displays requires extremelylow latency in order to work properly. The latency typically constitutes of thelag time between the actual movement, registration, and screen display. Thisissue sets requirements on both the data rendering devices and the trackingdevices.

The fourth and last issue is which kind of user interface VR, and especially AR,should focus on. Either the technology can develop towards an interface wherethe user is interacting with visual digital tools, or the technology developmentcould focus on an interface where the user is handling physical tools and augmentthis world with digital content [14].

Another aspect is the flexibility of the virtual environment. The trends of todaywith, for example, agile product development and high clock speed are requiringflexibility in all parts of the production, including assembly training. Due tothis, a VR or AR training systems must be adaptable [5].

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3.3 Integration and Interface Design of VR and AR Systems

In order to fully exploit the opportunities of a virtual training system there haveto be a structured way of handling performance tracking data. The trainingsystem itself is therefore often a part of a larger, central, system. Gorecky et al.describe the design and function of a VR training system called VISTRA2, anEuropean collaboration project. In their article, the authors state three mainchallenges for a VR system; user acceptance, how to get enterprise data intothe training system and how to manage the data from the training system.

The VISTRA simulation system is connected to a central system called theVISTRA knowledge platform. This central unit handles the conversion fromexternal data into the system and it also sends data to a second sub-platformcalled VISTRA SharingCentre which distributes the information from the train-ing simulation.

A proven critical factor behind learning is the feedback given to the trainee.This is also the case with VR and AR systems. There are different solutions onhow the feedback can be handled. For instance, the feedback can be given froman instructor, supervising the ongoing training process through screen sharingvia a display. There is also digital tools available, such as analyses on theergonomics done with the help of input data from visual sensors [5].

By combining VR and AR technology with intelligent algorithms, personalisedfeedback can be provided to the user based on previous performance. Wester-field et al. describe AR connected with an Intelligent Tutoring System - ITS.The technology was applied and tested on a motherboard assembly process.Feedback handling was programmed into the ITS and, depending on the datasent from the AR system, the user received real time feedback on his or heractions [15].

Every step made by the trainee was tracked by the AR and sent to the ITSwhich determined if the action was within the allowed constraints. If the con-straints were broken, an error message was displayed on the HMD. The feedbackprovided by the ITS was customised, programmed and added by a human in-structor. The instructor could also determine how the information should beprovided to the trainee. For example, the amount of information provided couldgradually increase proportional to the errors made.

This forced the trainee to try by his or her own on every task and thereby learnthe process through trial and error. This makes the learning more efficient.The connection with the ITS system proved to be more efficient than regularAR without the ITS support [15]. These results exemplifies the need for effi-cient feedback handling, the strength in VR and AR does not only lie in thetechnologies themselves, but also in the systems connected to them.

2Virtual Simulation and Training of Assembly and Service Processes in Digital Factories

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When it comes to how an actual user interface should be designed it is a matter ofpsychology. Webel et al. present a collection of design rules, based on cognitiveresearch. Within psychology, the typical skills for assembling tasks, the abilityto replicate step-by-step instructions, are referred to as procedural skills [12].The learning speed of these skills has been proved to increase when the traineeis supplied with not only how-to-do skills, but also how-it-works skills [12].

How-to-do knowledge refers to list procedures, which traditionally has been themost frequently used learning method within assembly manufacturing. Furtheron, the how-it-works knowledge gives the learner a context. According to Canaset al., the performance of the trainee is improved by a psychological represen-tation of the device, known as mental model, implying that learning by virtualrealities increase understanding [16].

For increased understanding, system overviews and visualisation has been prov-en effective. During the learning period, the trainee should be provided grad-ually less detailed information about each assembly step as the education goesforward. The information, applied with AR technology, can consist of high-lighted areas, text boxes, buzzwords, videos and can be presented in both 2Dand 3D [12].

If too much visual guidance is given to the user, the active exploration will beimpeded. Instead, the trainee will uncritically follow the instructions, withoutactually understanding the context, thus not improving the comprehension ofthe trainee [17]. Webel et al. give an illustrative example of a driver followinga route guidance system, causing the driver to have less control and orientationthan a driver exploring the way without any guidance systems [12].

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3.4 VR and AR Systems vs. Traditional Methods

According to earlier sections, visual learning increases understanding more thantraditional, but is the operator assembly also more efficient? And which tech-nology is showing most potential, VR or AR?

Borsci et al. evaluate VR and AR technology applications in the car servicemaintenance industry, and conduct a case study at Jaguar Land Rover [18].The authors summarises results and cases from several articles, giving a thor-ough study of the current industry status. Since the car service maintenanceapplications are similar to industry assembling tasks, their results are of interest.Their article states the following four general results from VR and AR testing.

• Even though the evidence is weak, AR has been proven more effectivethan VR.

• The training time decreases with VR and AR.

• The trainees experience an increased understanding of tasks and proce-dures.

• Depending on the level of skill of the trainee, VR and AR can be more orless effective. Expert trainees tend to have more effective learning usingvisualisation than novice trainees.

The cases studied in the article state that VR and AR is more efficient; decreasestraining time and gives the operator a better understanding. But Borsci et al.criticise the narrow evaluation criteria that are being used to compare trainingmethods. For example, factors like cyber sickness, skill decay and technologyacceptance are often left out even though they are relevant. How adaptable thesystems are to different organisational needs is also of outermost importance,but not included in the study [18].

A more quantitative approach comparing VR, AR and traditional methods wereconducted by Gavish et al. [19]. In this study, operators with neither VR orAR experience were exposed to virtual training. The task was to assemble anelectric actuator of a motorised modulating valve.3 The subjects were split intogroups, each group learnt the assembly task using either VR, AR or traditionallearning.

These results, displayed in Figure 4, shows that the AR outperformed VR whenused on the same assembling task. The control group that used traditionaltraining was poor in performance compared to the AR system (not shown in thefigure). The authors also state that there was no significant difference betweenthe VR system and the traditional training in this type of low-level problemsolving [19].

3Assembly of the belt roller, the cover, the clamp, and the electronic board

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I II III IV V VI0

2

4

6S

core

VRAR

Figure 4: Performance differences between VR and AR, part 1 [19]

VII VIII IX X XI XII XIII0

2

4

6

Sco

re

VRAR

Figure 5: Performance differences between VR and AR, part 2 [19]

I Completion of the required task after trainingII Satisfaction with the performance of the taskIII Willingness to recommend the systemIV The system is a valuable training toolV Length of practice timeVI Concentrated more on the task than on how to use the systemVII Ease of performing the taskVIII EfficiencyIX Clarity of instructionsX Recovered from mistakes easilyXI Recovered from mistakes quicklyXII Comfortable experienceXIII Easy to use

Table 2: Explanation of Figure 4 and Figure 5 [19]

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This contradicts the theories of Webel et al. arguing visual learning is moreefficient than traditional. Although, the visual learning is affecting the long-termmemory in a wider extent than the short-term memory. This is probably notshown in this study where only the latter is examined, but problems requiringhigh-level problem solving would probably benefit from VR and AR. Moreover,one of the major benefits from AR contra VR, is the short length of the practisetime, shown in bar V in Figure 4. In manufacturing companies, short trainingtime for operators is of outermost importance.

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3.5 Industrial Management Perspective

In this thesis, management benefits and disadvantages will be evaluated fromthe following criteria. The criteria stated will be used in the discussion andevaluation of the virtual technology.

• Quality

• Cost

• Flexibility

• Lead time

According to Hayes et al. these parameters are central in industry competition[20]. In the assembly context, quality will be measured in number of componentsdamaged or misplaced during the process. If a company’s products lack qualitythere will be a decrease in customer satisfaction which will cause a decrease indemand. The cost constitutes of the cost of labour and capital.

Flexibility is a measure of how well a company can handle changes in volume andproducts. In this case, the focus will be on how well an operator training systemhandles changes in product design and fluctuations in production volume. Thelead time is the time from the creation of the sales order until the customerreceives the product. In the assembly processes the production flow affects thelead time.

These parameters are used to evaluate the performance of a value chain. Op-erator training is typically not referred to as a part of the value chain, but itaffects the components. This thesis will focus on how improved operator train-ing affects the value chain and thus indirectly the cost, quality, flexibility andlead time.

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4 Case Studies

In the following sections the content from three interviews will be presented.

4.1 Current Operator Training at Volvo Trucks

To obtain a representative picture of how operator training is conducted in thetruck industry, an interview was held with Ivan Radulovic, Product QualityManager at Volvo Trucks.

At Volvo, the learning process of a new operator at the assembly line of truckproduction starts with three days of introductory activities. During these days,the trainee receives basic practical skills, experience of tool usage and productknowledge. After the introduction, the training continues in the productionline. When the trainee enters the production line he or she receives a personalinstructor. The instructor guides the trainee through all work balances4 andshows all specific tasks.

The assembly sequence is first learnt through reading a standard operating sheet,which includes instructions and pictures of how and why a component shouldbe assembled. Tasks that are critical for product performance, quality andsecurity are highlighted with different symbols. The knowledge from the sheetsare then practically trained on the assembly line supervised by the instructor.The instructor takes full responsibility for the assembly quality on the line.

An average trainee will learn a balance in one to ten days, the average trainingtime is approximately ten days. Before a trainee can start to work indepen-dently, the person must pass a test constituting of 24 questions within thefollowing four main areas:

• What to do?

• How to do it?

• Why it should be done the specific way?

• Can it be done practically?

Both theoretical understanding and craftsmanship knowledge must be sufficientin order for the trainee to pass the examination. A trainee can work and con-tribute to the production output once one balance is fully trained. But everyworker typically rotates on three to four balances, and every balance take oneto ten days each to learn.

4A work station with a sequence of assembly tasks

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The working force within assembly at Volvo constitute of long term employed,experienced workers combined with short term workers from labour hiring agen-cies. The hired part of the workforce is typically volatile. It is adapted after thecurrent production demand. This entails that the amount of operator trainingneeded rises when there is a peak in work hiring. Radulovic states that hiringpeaks have had a negative impact on production quality. Further on, Radulovicemphasises that the lack of space has caused great problems when hiring peaksoccur at times of increased production.

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4.2 Current Operator Training at Scania

To further explore how the operator training is conducted in the truck industry,another case study was conducted with Pontus Jensson, Unit Manager at Scania.

According to Jensson, Scania uses a staffing company when hiring operators.The newly hired personnel are then going through an introduction week wherebasics in assembling and safety information are given. Then, they are assignedan instructor and an unit. The trainee then follows the instructor along theproduction line for approximately four weeks, rotating between several stationsuntil the trainee can operate by him- or herself.

The operator training is split into the following four parts:

1. Off-line training

2. The instructor performs the tasks and the trainee observes

3. The trainee operates by him- or herself, but with a quality control

4. Continuous improvement and education of the former trainee

As earlier mentioned, these steps take approximately fours weeks, but variesdepending on the individual and the unit. During the whole process, the in-structor is responsible for the quality control, and all output done by the traineemust be controlled by the instructor. The instructors are personnel from theordinary production line, who has rigid experience and undergone an instructorcertification.

Jensson tells that there is a high labour turnover. Also there are fluctuations inquantities demanded in the production. In situations where many new operatorsare hired simultaneously, there is a distinct decrease in output quality. This canbe seen by lower KPI’s5 and decreased team spirit in the units due to highstress. It is hard to meet a high labour turnover due to the lack of instructors.All personnel is not suitable for instructing, even though they do a superb jobas operators.

There are no training line at Scania where the trainees can operate off-line, butthere are places where they can get to know the products. Jensson do believethere is room for virtual technology within operator training, especially in thefirst two parts of the training, mentioned above. But, Jensson emphasis theneed of physical training and does thereby exclude that all of the training canbe virtual.

5Key Performance Indicator

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4.3 Research within Virtual Operator Training at Scania

In order to acquire knowledge about the current research within operator train-ing in manufacturing industry, a case study was conducted at Scania. Theinterviewee was Lars Hanson, Project Engineer at the Virtual ManufacturingGovernance Group.

No virtual training takes place in the actual production line at Scania today.But the virtual system Vicendo is in use at Scania’s pedal car factory, whereparts of the training is done. Vicendo is described as a ”desktop VR”, andnavigation is done by a hand held mouse. Initially, the trainees are guidedwhat to do, which tools to use, where to put parts et cetera, by text boxesand animations on the screen. But as the training proceeds, this information isstepwise removed and the operator must be able to remember what to do.

The Vicendo program should be repeated several times, each time with lesshelp. After each completed round, the trainee receives a score based on theperformance. This works as an initiative to learn more and faster accordingto Hanson, since the operators want to score the highest. One of the majorbenefits from this virtual training is that difficult operations can be repeateduntil the operator knows what to do. Also, there is no need for every trainee tohave an individual instructor.

Scania has held training with up to 25 trainees and one instructor simultane-ously. This strategy not only decrease the cost in comparison to the traditionaltraining, but also it makes it possible to collect more data. Among other data,it is easy to see in which parts of the assembly process operators are struggling,if they choose the wrong tools or if they apply the details in the wrong way. It iseasy to take time on each operation and Hanson tells that the operator trainingtime has shown indications of decreasing. But there are no confirmed results ofthis from Scania.

Further on, the interaction between the R&D department and the operators canbe tightened with the help of virtual simulations. For instance, the R&D depart-ment can send CAD6 models before the product is launched. These models canbe simulated and operators can try to assemble them in a virtual environment.Feedback about assembly difficulties can then be given to the R&D department,which can develop the product according to DFA principles.

According to Hanson, all the major players within the trucking industry andthe automobile industry are exploring VR and AR. There have been very fewimplementations within trucking yet, but several within automobile which is amore fast moving industry. Hanson do not consider the industry as progressivewithin VR and AR technology, but it is closing the gap. There are collaboratingresearch projects where companies as Scania and Volvo are included.

6Computer-Aided Design

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One major disadvantage with virtual reality is the demand of space. To beable to move in the virtual world in an authentic way, you either need anomnidirectional treadmill or a lot of space. Thus, Hanson is sceptic aboutthis concepts and rather use what is earlier described as desktop VR.

Hanson predicts that AR, and desktop VR, will be the most useful technologiesin the future. The desktop VR can, as earlier described, be used in mass training.And the AR, will probably be used more frequent since this means physical andvisual training can be incorporated - and Hanson is convinced that physicaltraining must be a part of the operator training.

Sequali is a system developed at Saab by Lennart Malmskold and has beenused by General Motors, Nevs and is today used at Scania. The system worksas a game where the operator is given operating sheets with missing parts. Theoperator then has to fill in the blanks and is given a score based on how wellhe or she manages to do this, and thereby achieving continuous feedback. Thegame is supposed to be repeated several times, thus giving the operator a deepknowledge and understanding of the operator sheet, but no physical training.

At Scania, they have been using desktop computers with ordinary screens whentraining. Today, there has been no use of hand held, or head mounted displayswithin operator training, but these have been used within other parts of theproduction. Neither, there has been no use of haptic devices such as bracelets,or any other kind of sensors. Scania will probably explore these technologiesin-depth further on according to Hanson.

Hanson and his team is eager to implement virtual technologies in the real pro-duction as soon as possible. But, according to Hanson, the middle managementat Scania has various opinions regarding the technology.

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5 Results

In the following sections, the key results found in the literature review and thecase studies are presented.

Flexibility

Work forces within assembling are typically volatile and there is a high labourturnover which requires an effective training method. With the operator trainingcurrently used in the truck industry, every trainee requires a personal instructor.With the virtual technology, a single instructor can handle multiple traineessimultaneously.

Product changes also raise the demand for training since a new assembly se-quence must be learnt. In VR, the training systems can be changed rapidlysince the product models can be transferred from the development section tothe training system. This allows product training in an early stage, even beforethe physical product is presented to the operators.

Immediate Feedback

In traditional training there is typically no standardised way to receive feedbackon which tasks are difficult to learn. This knowledge stays between the instructorand the trainee, and is thus not institutionalised. Virtual technology softwaremakes is possible to track steps that are hard to complete, and send data to theinstructor. This enables a thorough analysis of the assembly process.

Importance of Physical Training

All interviewees emphasise the need for physical training. The literature alsoconfirms this fact that in order to fully master an assembly sequence, crafts-manship skills are necessary. These skills cannot be achieved by pure virtualsystems. Physical training is possible with AR and traditional training. Todaythe physical training is done on the production line, thereby affecting productionoutput.

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VR and AR in Cognitive Training

Both VR and AR have proven to improve cognitive skills. This due to the moreexpressive way of displaying graphics and information about the product. Whenprocedural skills are trained the brain is more likely to learn if the trained tasksare given a context. For instance, product knowledge deepens the understandingand gives the assembly sequence a context. The literature also states that VRand AR are more effective when used on experienced operators.

With virtual technology this information can be displayed together with theassembling tasks. This facilitates the learning process. In traditional trainingthe product knowledge and the cognitive skills are learnt separately. Intelli-gent feedback given by a virtual system can also be given step by step as thetrainee progress. The amount of information can also be adapted to the traineesperformance. This has shown to increase the learning speed of procedural skills.

Hardware and Software

The devices used for VR and AR training must be adapted to the implemen-tation. A full VR setup containing HMD, treadmill, and hand held sensorsrequires both space and vast capital investments. Typically there is not muchspace in an industry facility that can be used as training area. Several virtualsystems can therefore risk to take up too much space.

A less space consuming system is the desktop VR which only requires a displayand a navigation tool. AR on the other side can be used with only a HMDor a HHD and is thus not space demanding. The challenge within hardwareis to develop accurate sensors and decrease the lag time between action anddisplaying.

The software used in the AR and VR systems must be able to connect with otherparts of the factory, such as the R&D department, in order to fully exploit theopportunities of pre-physical product training and DFA analyses. For instance,the system should handle CAD models. The software must also have an ITS thatis designed to give constructive feedback with the right amount of informationto the trainee in order to maximise the efficiency.

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Off-line Training

The case studies state that the output performance and quality declines whennew operators train on the production line. VR and AR can be used off-line andthereby not affect the output. The cognitive training can be handled off-linewith the current technology. Craftsmanship training is still problematic to dooff-line. Today’s VR systems do not provide a virtual world realistic enough tosatisfy the need for practical training.

Not only does the user lack the physical characteristics of the products7, alsotoday’s tracking devices are not accurate enough to provide the realistic preci-sion. With AR it is necessary to install a physical training station that providesa physical world that can be mixed with the virtual world. This physical train-ing station would require the same amount of space that a traditional trainingwould do, therefore off-line training is hard to do with AR if the training spaceis limited.

Current Industry Acceptance

The side effects of virtual training systems, such as cyber sickness and useracceptance, are not thoroughly investigated by academia. The implementationof the technology is not well spread in the Swedish trucking industry, but re-search is increasing. The leading actors invest resources and several researchcollaborations are in action.

7Surface, weight, softness et cetera

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6 Discussion

In the following sections the two sub-questions are discussed and analysed basedon the findings in the results. The methodology is evaluated and areas for furtherresearch are discussed.

6.1 Which technology is more promising: VR or AR?

From the literature review one can conclude that most of the articles treat theefficiency and benefits from AR. This technology has been proven as an effectivelearning tool when compared to traditional training methods. In comparingstudies between VR and AR it is the latter that has outperformed the other interms of learning speed and assembling ability.

In the literature review, there has been a difference in the usage of VR and AR.AR implementations often include additional gadgets, such as haptic bracelets,which gives the trainees an additional way to receive feedback and input ontheir training. This may affect the performance of the technologies.

Further on, one major difference between VR and AR is that AR allows theoperator to move the actual physical object with bare hands. VR on the otherside, requires hand held sensors to register the trainees’ movements and there isno actual contact with physical objects. Due to this constraint, one importantdimension of the learning is lost. The discrepancy between the virtual worldand the actual assembly line is vast. This causes trouble when the trainee isfacing the real tasks.

In order for VR to cope with AR in the future, it will be necessary for the tech-nology to decrease the difference between the virtual and the physical world.This will require smarter and more integrated tracking sensors for user move-ment. Hanson does not consider this as the right way to go, he is rather headingfor solutions including AR or desktop VR.

According to all interviewees, the physical knowledge is extremely important.Assembling is a craftsmanship, and thus cannot be replaced by virtual simula-tions. Hanson and Jensson agree on that there is a usage of VR in early stagesof the training, but do not see VR as a possible full replacement to traditionaltraining.

The need for sensors and other equipment also causes a demand for space. Thereis seldom more space than necessary in industry facilities. Radulovic entails thatwhen Volvo increased their production capacity last year, there was not enoughspace to fit all operators and their instructors. If these would have been trainedwith VR, an area many times as big would have been needed which is unrealistic.

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AR equipment is today used in service and maintenance as a replacement totraditional service manuals. In these situations the servicemen face differentproblems every day, compared to assembling where the same procedure is re-peated over and over again. In assembly manufacturing, the operator is requiredto know the assembly process by heart, without any help of additional instruc-tions when he or she is on the production line. An AR system will rather distractthe operator and slow him or her down.

AR is therefore only useful during training within assembly manufacturing, ac-cording to Hanson. But, he adds that if there is a high product flexibility, ARcan be used to give continuous training and instructions. When using AR totrain, the production line have to be slowed down, and this is seldom possi-ble due to short takt times8. AR thereby requires a separate physical trainingstation for every assembly sequence, which will drive costs.

8The average time between the start of production of one unit and the next unit

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6.2 Does VR and AR increase manufacturing performance?

One of the main advantages using VR is the fact that the operator can train in avirtual world, thus not affecting the actual production. Moreover, the operatorcan repeat complex operations until he or she has learnt the operations properlyand therefore minimise the potential decrease in quality when starting to operateat the real production line.

Since the virtual training probably will differ a lot from the actual productionline, a large part of the training must be done physically. This type of trainingwill demand an instructor walking side-by-side, it will affect quality negativelyand increase lead times. With on-line training there is always an increased riskof assemblage errors causing disruptions in the production flow. This is one ofthe major downsides with VR training.

On the other side, one major upside with VR is the possibility to train multipleoperators simultaneously. As an example, several trainees can be trained byone skilled operator in a virtual reality. Since the workforce often adapts afterthe output demand, a mass training system will improve a company’s abilityto handle a volatile product demand. It will also decrease training costs whenthere is no need for an 1:1 relationship between trainees and instructors.

To avoid the extensive gap between virtual training and the actual productionline, AR can be used. If there is room for a separate physical training line,augmented with digital features, the virtual training can be done completely off-line. This guarantees fully skilled workers that can perform assembly tasks withsufficient quality as soon as they enter the actual production. This completelyeliminates the risk of a quality decline seen in the production that is caused bytraining activities.

Both VR and especially AR has shown to decrease learning time for operators.This will also facilitate changes in the workforce since the technology will supplyskilled operators faster. A demand driven organisation, that adapts its capacityafter market changes, must be able to ensure sufficient skill level on its operators.Virtual technology can be a tool to meet this requirement.

Virtual training can also be used to increase the integration between assemblyand R&D. A constant issue that companies nowadays deal with is how to buildeffective communication channels to connect departments. The whole DFAconcept requires communication. With virtual training, CAD models can betransferred to the assembly department. And with the ability to analyse trainingerrors, feedback can be given to R&D in an early stage. This has the potentialto reduce costs in the product development since DFA unfriendly constructionscan be mitigated early.

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The connection between departments build a foundation for agile product de-velopment and concurrent engineering. The products can be development andtested continuously by both R&D and assembly production. This will increasedevelopment speed and help companies cope with an increase competition andmore rapid product life cycles.

Another advantage of feedback handling in virtual technology is that it is easyto standardise the given feedback. The feedback is given to the trainee by analgorithm, which can be programmed to give information in a pedagogical way(ITS). This ensures that the procedural skills are learnt as quick as possible.Since the feedback and information is given in a standardised way, there is areduced risk that trainees learn the tasks incorrectly.

In the interview, Jensson tells that Scania is working with a certain education forupcoming instructors to assure an efficient training of new operators. By usingvirtual technology, the need for an education of new instructors is decreased.Since the human factor is eliminated, standardisation is already guaranteed.Standardised working tend to reduce costs and to improve quality.

Standardisation is extremely important in assembly manufacturing. A compo-nent that is assembled the wrong way may lead to a malfunctioning product.From an ergonomic point of view standardisation is always necessary. The worktasks are often repetitive and wrong movements can cause injuries in the longrun.

From the results found in the literature review, one can also conclude thatvirtual technology is more efficient when used by experienced trainees. Thisinsinuates that virtual technology is more useful to train operators in productchanges rather than to train novices. The answer to why virtual technology ismore effective on experienced operators may lie in abstract factors. For a novicethat is both new to virtual technology and new to the type of tasks that he orshe is supposed to learn, the amount of expressions may take focus from thelearning.

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6.3 Methodology Criticism and Areas for Further Research

There are parts of the report that are imperfect. First of all, implementedVR or AR training system was not fully explored, only prototypes. Thus,results and discussion is built on expectations rather than reality. It wouldhave been appropriate to conduct a study of an implemented system to confirmthe expectations.

Further on, the case studies carried out were semi-structured. This gives abroader picture of the interview topic, but prevent going deeper on a narrowsubject. Carrying out interviews with more companies within manufacturingwould have been worthwhile. This would have provided a more versatile pictureand made it possible to do more detailed comparisons. It would had increasedthe reliability of this study.

On the other hand, the interviews were conducted with appropriate represen-tatives of the manufacturing industry and gave an useful general picture of thecurrent status. Thus, the validity of the case study is high.

In the literature review many references were included in order to receive adiverse picture of the subject. Due to the constraints all references treat themain question. This gives the study both validity and reliability.

Yet, there are few studies showing that VR or AR are more efficient than tra-ditional operator training. Hanson could not show any confirmed results of thiseither, but there are strong indications of high efficiency from several actors.And, as discussed earlier, even if VR or AR do not reduce training time, itmakes it possible to train operators in more cost efficient ways.

Further research would preferably be addressed to the actual efficiency of VRand AR tools contra traditional learning methods. This thesis establishes thatthere is a demand for new ways to train operators more efficient, and that VRand AR technology hold several benefits.

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7 Conclusion

Virtual training tools enable two types of feedback. First, the operator achievesinstant feedback on his, or her, learning process when training off the productionline, thus not affecting actual output. Sequences where the operator is strugglingcan easily be identified by data collected, thus enabling optimisation of thetraining process. Second, feedback can be given to the product developers inearly stages. The R&D department can send CAD models to the virtual trainingsystems. Products can then be visualised and assembling done virtually. Thismakes it possible to address assembly difficulties and thereby improve the designbefore actual production.

The virtual technology also enables mass training of operators. This possibil-ity facilitates the handling of a volatile workforce since there is no need for apersonal instructor to every single trainee. Changes in the workforce is a nat-ural part of the production for many assembly industries since the productioncapacity adapts after the market demand. But, the need for physical trainingcannot be neglected. Thus, virtual training is appropriate for the initial stepsof the training process.

With virtual technology new product changes can be previewed in their virtualform before a physical product is presented to the assembly operators. Thisallows the operators to start the training in an early stage and thereby acquireassembly skills on new products ahead. This will minimise the risk of an outputdecrease when new products are introduced to the production line.

The current demand of 1:1 training belongs to the past if operator trainingcan be done virtually. The technology enables several trainees to learn, trainand repeat with a computer as their only instructor. This will cut personnelcost, which is a major cost for assembling companies. Further on, the earlyfeedback, given before actual production, will reduce the amount of productsdelayed because of assembly difficulties, thus reducing lead times and costs inthe long run.

There are many psychological factors behind the learning curve of proceduralskills. To fully master an assembly task both craftsmanship and cognitive skillsare needed. The virtual training has proven to facilitate the learning of cognitiveskills. Product information and pedagogical learning paths can be incorporatedin the virtual systems thus making the training more efficient than traditionaltraining.

In summary, there are several production benefits of VR and AR in operatortraining. These range from off-line training, cognitive perception and masstraining to cost savings, product and operator feedback and ability to encounterproduct and volume fluctuations.

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8 Bibliography

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9 Appendices

9.1 Appendix I: Questionnaire A

Hardware and Software

• Which VR and AR systems are you currently investigating or developing?

• What kind of sensors are you investigating?

• What kind of display devices are you investigating, hand held or headmounted?

• Are you investigating haptic devices?

• Which set of hardware devices are the most promising?

• What kind of data are you currently able to collect from the VR and ARtraining?

• Does the data give you the possibility to expand and improve the feedbackgiven to the trainees?

• Do you have data on how much faster a trainee learns from VR or ARcompared to traditional methods?

Technology Performance, R&D Investments and Future Outlook

• How is the VR and AR learning compared to traditional learning regardinglearning curve and adaptability?

• What is the future outlook for new technology within the area?

• Do you have any collaborating research projects within VR and AR?

• Do you consider your industry as progressive within VR and AR technol-ogy?

• What is the next step for your company within VR and AR?

• Are you going to implement VR or AR in any part of the real productionline soon?

• Which technology do you think will be the most useful in the future, VRor AR?

• How fast can the training system be adapted to new components andproduct changes?

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9.2 Appendix II: Questionnaire B

Traditional Operator Training

• I which way is the operators trained traditionally?

• How much staff is required for the traditional operator training?

• For how long does your operators typically train today?

• How often do you employ new staff that requires operator training?

• Do you experience a decline in quality when new staff is put into theproduction line?

• How much does it cost to train a single new operator?

• What are your opinions on VR and AR implementations in operator train-ing?

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9.3 Appendix III: Interviewees

Ivan Radulovic

Ivan Radulovic works as Product Quality Manager at Volvo Trucks in Gothen-burg. He has been with Volvo for the last six years and has a deep knowledgeof the production. Radulovic has studied Industrial Operations at GoteborgsTekniska College.

Pontus Jensson

Pontus Jensson works as Unit Manager at Scania in Sodertalje. He has beenat Scania for 13 years, starting as an operator and thereafter exploring variousfields as processing, R&D and assembly among others. He has an academicbackground from Scania’s upper secondary school with industrial focus.

Lars Hanson

Lars Hanson works part time as Project Engineer at Scania in Sodertalje, parttime as Project Engineer at Chalmers University in Gothenburg. Hanson iscurrently working with virtual manufacturing at Scania and is Project Leaderof Scania’s project within this area. Hanson holds a Master of Science in Me-chanical Engineering from Linkoping University and a PhD in Ergonomics fromthe Faculty of Engineering at Lund University.

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