Adapting Virtual Training Systems for Industrial Procedures to the Needs of Older People

Integration of older employees into the workforce is critical for a successful manufacturing industry due to demographic change. However, technological developments to create more flexible manufacturing environments are leading to increasingly complex machinery that has to be operated by an aging workforce. Virtual training systems prepare operators for the interaction with industrial machines. Current virtual training systems do not address the perceptive and cognitive abilities of older users to enable a satisfying and efficient training. This article develops adaptations of the visualization and the interaction techniques of a virtual training system to address the abilities of older operators. The results of a between-subjects study indicate that the adaptations improve the subjective perception of the training system and decrease the training time. The paper concludes that adaptive training systems can support the participation of diverse user groups in the manufacturing industry by providing more effective and satisfying training.

[1]  Jiang Yu Zheng,et al.  A training system using virtual machines for teaching assembling/disassembling operation to novices , 1996, 1996 IEEE International Conference on Systems, Man and Cybernetics. Information Intelligence and Systems (Cat. No.96CH35929).

[2]  W. Buxton Human-Computer Interaction , 1988, Springer Berlin Heidelberg.

[3]  Birgit Vogel-Heuser,et al.  A virtual training system for aging employees in machine operation , 2017, 2017 IEEE 15th International Conference on Industrial Informatics (INDIN).

[4]  S. Voelpel,et al.  Analyzing the Effectiveness of Contemporary Aging Workforce Management: The Case of Daimler AG , 2009 .

[5]  Kerstin E. E. Schroder,et al.  The assessment of optimistic self-beliefs : Comparison of the German, Spanish, and Chinese versions of the general self-efficacy scale , 1997 .

[6]  Aaas News,et al.  Book Reviews , 1893, Buffalo Medical and Surgical Journal.

[7]  J. B. Brooke,et al.  SUS: A 'Quick and Dirty' Usability Scale , 1996 .

[8]  Michael J. Singer,et al.  Measuring Presence in Virtual Environments: A Presence Questionnaire , 1998, Presence.

[9]  Satyandra K. Gupta,et al.  Towards the development of a virtual environment-based training system for mechanical assembly operations , 2007, Virtual Reality.

[10]  Malte Brettel,et al.  How Virtualization, Decentralization and Network Building Change the Manufacturing Landscape: An Industry 4.0 Perspective , 2014 .

[11]  Molly Follette Story,et al.  The Universal Design File: Designing for People of All Ages and Abilities. Revised Edition. , 1998 .

[12]  Thomas Olzak,et al.  What is virtualization , 2009 .

[13]  A. Chan,et al.  A review of technology acceptance by older adults , 2011 .

[14]  Teresa Gutiérrez,et al.  IMA-VR: A multimodal virtual training system for skills transfer in Industrial Maintenance and Assembly tasks , 2010, 19th International Symposium in Robot and Human Interactive Communication.

[15]  George Papagiannakis,et al.  Immersive VR decision training: telling interactive stories featuring advanced virtual human simulation technologies , 2003 .

[16]  M. Lepper,et al.  Intrinsic motivation and the process of learning: Beneficial effects of contextualization, personalization, and choice. , 1996 .