The many faces of (digital) Game-Based Learning in Manufacturing and Business

(digital) Game-Based Learning inManufacturing and Business

The many faces of

Philipp Brauner, Martina Ziefle

Human-Computer Interaction CenterRWTH Aachen University, Germany6th International Conference on Competitive Manufacturing 2016 (COMA), Stellenbosch, South Africa

Brauner P, Ziefle M. How to train employees, identify task-relevant human factors, and improve softwaresystems with Business Simulation Games. Procedings of the 6th International Conference on CompetitiveManufacturing 2016, COMA ’16. Stellenbosch, SA; 2016. p. 541–546.

RWTH Aachen University, Human-Computer Interaction Center

2016-01-29 Game-based Learning in Manufacturing and Business & the Quality Intelligence GamePhilipp Brauner ([email protected]), Martina Ziefle

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n Human-Human & Human-Technology communication

n Design, development, and evaluation of interactive systems– Requirements analysis– Usability & User Experience– Technology Acceptance and risk perception– Human Factors, User Diversity & Aging population

Human-Computer Interaction Center atRWTH Aachen University, Germany


Context: Part of the Cluster of Excellence“Integrative Production Technology for High-Wage Countries”

n Goal: Strengthen competitiveness of high wage countries

n Engineering of future production systems– New materials and processes– Improved and smarter machinery– Optimize assembly cells, shop floor, cross-company cooperation

n > 25 Institutes, > 100 researchers

n Funded by German Research Foundation (DFG)

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Our research objective:Optimize cross-company cooperation

n Optimize cross-company supply chains (SC)– Technical factors influencing performance of SCs– Human Factors influencing performance of SCs– Influence of Interface Factors on SCs– Interrelationship of technical, interface, and human factors

n Why are humans considered?– Humans make final decision– Overview over not explicitly modelled relationships

(e.g., closed-world assumption)– Complexity and uncertainty increases,

less time for making decisions

Information flow

flow of goods

Supply Chain

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Goal: Understand system and user factors that influence efficiency, effectivity, and user satisfaction in Enterprise Resource Planning Systems, Supply Chains and Quality Management.


How can human decision making be investigated?

n Convergence between field and laboratory study

n Simplified & controllable (game-based) environment

n Experimentally manipulate complexity and interface

n Empirical methodology to quantify human influence on decision making and performance

– Identify and measure influencing personality factors– Build a formal model that explains performance

n Side-effect:Usable for game-based learning (GBL) in professional trainings etc.

Test in the field(ecological validity)

Controlled experiment in

laboratory(internal validity)

We are here

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Short definition of(digital) Game-Based Learning (GBL)

n Use motivational potential of (computer) games to convey learning [Prensky 2001]

n Benefits– Increased motivation– Understanding in context– Increases Network Thinking abilities– Explore and understand

cause-and effect relationships– Safe and inexpensive

n Very successful in medical contexts– Physiotherapy and rehabilitation– Knowledge dissemination– Change attitudes and behavior

“Agame isasysteminwhichplayersengageinanartificial conflict,definedbyrules,that

resultinaquantifiableoutcome.”[Salen &Zimmerman,2003]

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Our hypothesis: Game-based learnings in manufacturing and business can be used to…

n Understand task relevant human factors

n Measure aptitude of potential employees

n Train current or prospective employees*

n Benchmark User Interfaces*

Human Factors

Personnel selection

Training intervention

Usability studies

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Practical Example 1:The Beer Distribution Game

Objective of the game: Train prospective employees

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Game-Based Learning in Production Engineering:The „Bullwhip effect“ and the Beer Distribution Game

n “Bullwhip Effect” described by [Forrester] in the 1960’s– Increasing customer demand leads to

exaggerated demand along supply chains– Resulting stock level graphs look like a bullwhip

n Beer Distribution Game:– 4 players / 4 positions in 4-tier supply chain– Costs for out-of-stock and stock keeping– Time lag between order and delivery– Goal: Keep costs minimal– Small variance in customer order function– Learning objective: Sensitize and train

FactoryDistributor

purchase orderforwarded

immediatly

order deliveredimmediately

1 week 1 week 1 week

2 weeks 2 weeks 2 weeks

WholesaleRetailer

purchase orders

shipments

Image source: ft.com

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Our study on the Beer Distribution Game:Train current or prospective employees

n Results:– Bullwhip effect clearly present– Delayed with position in chain– Increases with position in chain

[F3,117=7,941,p<.001**]– Strong correlation between multiple rounds

[r2,112-2=.628, p<.001**]– Players get sig. better

[F1,111=4.204, p<.05*]

n Conclusion:– Replication of similar studies ⇒ concept works– Stables results ⇒ underlying factors– Performance increases ⇒ learnability

-20

-10

0

10

20

30

40

1 5 10 15 20

AverageStockLevel

Week

Retailer Wholesale Distributor Factory

Remember:Small variance in customer’s orders

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Empirical study, n=112 players, 1 of 4 positionsrandomly assigned, 2 rounds played

Week

Ord

er

5 10 15 20

48

Customer order functionorder(round)

⇒


Practical Example 2:A supply chain game with quality management aspects – “QI-Game”

Objective of the game: Benchmark for user interfaces(e.g., usability, efficacy of decision support systems, business intelligence)

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Development of business simulation game

n Extension of „Beer Distribution Game“

n Based on System Dynamics model

n Includes product quality– Product intact or broken– Supplier's quality varies– Internal production quality varies

n Increased complexity (tradeoff 3 parallel tasks)– Management of stocks– Investment in incoming goods inspection– Investment in internal quality management

n Over 20 variables in the user interface

n Players must infer state of the production

Part of the game’s simulation model:Stock level at a given time t:S(t) = S(t-1) + O(t-1) – D(t)

Net profit:P(t) = R(t) – cStock×S(t) – Iigi(t) –

Iipq(t) – C(t-1) – …

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n Continuous discussions with experts and users

n 1st prototype– Based on SD model– Paper based– Layout arrangement

n 2nd prototype– Spreadsheet-based– Definition of game model, indicators, …– Quick optimization of simulation parameters– Simplified discrete event simulation

n 3rd prototype – Web-based interface

Agile design and development process

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The Quality Management Game’s interface

n Web-based game environment– Accessible across the world (scale)– Laboratory studies (scope)

n Captures all metrics and interactions

n Controllable conditions– Varying supplier’s quality, own production quality,

customer’s demand, user interface, …

n Map game performance and other metrics to Human-Factors

– Identification of attitude, aptitude & motivation– Evaluation of the game, interface, …

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Example – Interface evaluation through exchangeable user interfaces:Model-View-Controller pattern (MVC)

n Separation of simulation model, data, and user interface

n User Interface interchangeable

P(t), S(t), …

QAPR

MODEL

CONTROLLER

VIEW

Interface ➝ Profit(t)

Profitt > Profitt?

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Evaluation of user interfaces:n Research question:

– Do interfaces influence player’s performance?

n Interface optimizations based on user feedback– Better spatial layout– Key Performance Indicators (e.g., stock level)

n Method– Study (N=40) with old vs. new interface, surveys

n Results– Users preferred revised user interface– Higher profits and higher product quality w. new interface

n Conclusion:– Good interfaces crucial for performance

(V = 0.263, F1, 38 = 13.548, p = .001 < .05*) revised interface

first interface

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Discussion and Takeaway

n Game-Based Learnings – Address Millennials / Generation Y– Training for Network Thinking, complexity, and uncertainty– Assessment of personnel, Identify task relevant Human Factors– Evaluate User Interfaces

n Studies on Beer Distribution Game & QI-Game– Replication of known effects ⇒ concept works– Good players & bad players ⇒ underlying human factors– Players learn ⇒ training intervention– Good interface lead to higher performance⇒ Usability competitive advantage

n Our next steps– Influence of Business Intelligence & Decision Support on performance

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n Brauner P, Runge S, Groten M, et al (2013) Human Factors in Supply Chain Management – Decision making in complex logistic scenarios. In: Yamamoto S (ed) Proceedings of the 15th HCI International 2013, Part III, LNCS 8018. Springer-Verlag Berlin Heidelberg, Las Vegas, Nevada, USA, pp 423–432

n Brauner P (2014) Understanding Human Factors in Supply Chains and Quality Management by Using Business Simulations. In: Brecher C, Wesch-Potente C (eds) Proceedings of the Conference of the Cluster Of Excellence “Integrative Production Technology For High Wage Countries” 2014/1, 1st edn. Apprimus Verlag, Aachen, Germany, Aachen, Germany, pp 387–396

n Hering N, Meißner J, Runge S, Brauner P (2014) Exzellenzcluster: Was bestimmt die Performance meiner Supply-Chain? – Eine Untersuchung technischer und menschlicher Einflussfaktoren im Hinblick auf die Effizienz von Lieferketten. Unternehmen der Zukunft -Zeitschrift für Betriebsorganisation und Unternehmensentwicklung 27–28.

n Philipsen R, Brauner P, Stiller S, et al (2014a) The role of Human Factors in Production Networks and Quality Management. – How canmodern ERP system support decision makers? First International Conference, HCIB 2014, Held as Part of HCI International 2014, Heraklion, Crete, Greece, June 22-27, 2014. Proceedings, LNCS 8527. Springer Berlin Heidelberg, pp 80–91

n Philipsen R, Brauner P, Stiller S, et al (2014b) Understanding and Supporting Decision Makers in Quality Management of ProductionNetworks. Advances in the Ergonomics in Manufacturing. Managing the Enterprise of the Future 2014 : Proceedings of the 5th International Conference on Applied Human Factors and Ergonomics, AHFE 2014. CRC Press, Boca Raton, pp 94–105

n Stiller S, Falk B, Philipsen R, et al (2014) A Game-based Approach to Understand Human Factors in Supply Chains and Quality Management. Procedia CIRP 20:67–73. doi: 10.1016/j.procir.2014.05.033

n Brauner P, Ziefle M (2015) Human Factors in Production Systems – Motives, Methods and Beyond. In: Brecher C (ed) Advances in Production Technology. Springer International Publishing, pp 187–199

n Mittelstädt V, Brauner P, Blum M, Ziefle M (2015) On the visual design of ERP systems – The role of information complexity, presentationand human factors. 6th International Conference on Applied Human Factors and Ergonomics (AHFE 2015) and the Affiliated Conferences, AHFE 2015. pp 270–277

n Calero Valdez A, Brauner P, Schaar AK, et al (2015) Reducing Complexity with simplicity - Usability Methods for Industry 4.0. 19thTriennial Congress of the International Ergonomics Association (IEA 2015).

n Ziefle M, Brauner P, Speicher F (2015) Effects of data presentation and perceptual speed on speed and accuracy in table reading forinventory control. Occupational Ergonomics 12:119–129. doi: 10.3233/OER-150229

n Brauner P, Ziefle M. How to train employees, identify task-relevant human factors, and improve software systems with Business Simulation Games. Procedings of the International Conference on Competitive Manufacturing 2016, COMA ’16. Stellenbosch, SA; 2016. p. 541–6.

Publications

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Thank you four your attention!Summary

n Human Factors Perspective increasingly important

n Business Simulation Games– Address Millennials – Training environment for onboarding / production ramp-ups– Assessment of personnel & Identification of crucial factors– Identification and quantification of interface costs

Dipl.-Inform. Philipp BraunerHuman-Computer Interaction CenterChair for Communication ScienceRWTH Aachen University, GermanyeMail: [email protected]

Funded by the German Research Foundation (DFG) within the Cluster of Excellence “Integrated Production Technology for High Wage Countries” (EXC 128).

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Education

The many faces of (digital) Game-Based Learning in Manufacturing and Business