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DESIGNING FOR HUMAN FACTORS: DEVELOPMENT AND EVALUATION OF A HARMONISTIC KNOWLEDGE-BASED DESIGN DECISION SUPPORT TOOL

Published online by Cambridge University Press:  19 June 2023

Sean Agius ,
Philip Farrugia  and
Emmanuel Francalanza
Sean Agius*
Affiliation:
University of Malta
Philip Farrugia
Affiliation:
University of Malta
Emmanuel Francalanza
Affiliation:
University of Malta
*
Agius, Sean, University of Malta, Malta, ing.s.agius@gmail.com

Abstract

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Dual ontological products are a physical construction and an emotional construction. Multitude of human factors must be considering when designing dual ontological products. To increase the product's impact and reach, designers should also understand the requirements of potential users. A design stage conflict exists between the emotional construction and the physical construction of a product when considering human factors. Designers find it difficult to achieve the right compromise between these constructions and hence, the balancing of the two is crucial. This research therefore contributes a novel harmonistic knowledge-based framework which makes designers aware of design stage conflicts and consequences of commitments made on human factors in the use-phase of the artefact. This approach was implemented in a machine learning based computational tool which exploits harmonistic knowledge and information collected from potential users to proactively assist, guide, and motivate product designers. This paper also presents a descriptive study for the evaluation of the framework and its implementation as a computer-based prototype tool. Results show the necessity and beneficial use of the tool for design engineering practice.

Keywords

Computational design methodsMachine learningUser centred designConcurrent Engineering (CE)Design synthesis
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 1367 - 1376
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

References

Adèr, H. J. (2008) ‘Modelling’, in Adèr, H. J. and Mellenbergh, G. J. (eds) Advising on Research Methods: A Consultant's Companion. Johannes van Kessel Publishing, Huizen, pp. 271–304. https://dx.doi.org/10.1080/02664763.2011.559375Google Scholar
Agius, S., Farrugia, P. and Francalanza, E. (2020) ‘A Framework for a Motorcycle Design Computer-Based Intelligent Tool’, Proceedings of the ASME 2020 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. St. Louis, USA. https://dx.doi.org/10.1115/DETC2020-22356CrossRefGoogle Scholar
Agius, S., Farrugia, P. and Francalanza, E. (2021) ‘A decision consequence-based model to understand the phenomena in motorcycle engineering design from a human factor's perspective’, International Journal of Design Engineering. Inderscience Publishers, 10(1), pp. 72–96. https://dx.doi.org/10.1504/IJDE.2021.113268.CrossRefGoogle Scholar
Bakshi, R. and Gupta, S. (2014) ‘Empirical Evaluation of Human Factors that Affect Design of the Product’, International Journal of Computer Applications, 100(9), pp. 15–21. https://dx.doi.org/10.5120/17553-8152.CrossRefGoogle Scholar
Barone, S. and Curcio, A. (2004) ‘A computer-aided design-based system for posture analyses of motorcycles’, Journal of Engineering Design, 15(6), pp. 581–595. https://dx.doi.org/10.1080/09544820410001731146.CrossRefGoogle Scholar
Blessing, L. and Chakrabarti, A. (2009) DRM, a Design Research Methodology, DRM, a Design Research Methodology. London: Springer. https://dx.doi.org/10.1007/978-1-84882-587-1.CrossRefGoogle Scholar
Borg, J. C., Yan, X. T. and Juster, N. P. (1999) ‘Guiding component form design using decision consequence knowledge support’, Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM, 13(5), pp. 387–403. https://dx.doi.org/10.1017/S0890060499135030.CrossRefGoogle Scholar
Duffy, A. H. B. and O'Donnell, F. J. (1999) ‘A Design Research Approach’, in AID’98 Workshop on Research Methods in AI in Design. Lisbon, Portugal, pp. 20–27. doi: 82-91917-08-6.Google Scholar
Farrugia, L. and Borg, J. (2016) ‘Design for X’ Based on Foreseeing Emotional Impact of Meetings with Evolving Products’, Journal of Integrated Design & Process Science, 20(2), pp. 85–100. https://dx.doi.org/10.3233/jid-2016-0017.CrossRefGoogle Scholar
Farrugia, P., Mamo, J. and Sant, T. (2019) ‘An Intelligent Computer-based Framework for Integrating Emotions and Aerodynamics in Sportsbike Design’, International Journal of Design Engineering (IJDE), 9(1), pp. 1–21. https://dx.doi.org/10.1504/IJDE.2019.104122.CrossRefGoogle Scholar
Hancock, P., Oron-Gilad, T. and Thom, D. (2004) ‘Human Factors Issues in Motorcycle Collisions’, in Karwowski, W. and Noy, I. (eds) Handbook Of Human Factors in Litigation. Boca Raton, FL: CRC Press, pp. 512–536. https://dx.doi.org/10.1201/9780203490297Google Scholar
Hassenzahl, M. (2010) Experience Design: Technology for All the Right Reasons. Edited by Carroll, J. M.. Morgan and Claypool Publishers. https://dx.doi.org/10.2200/S00261ED1V01Y201003HCI008CrossRefGoogle Scholar
Kroes, P. (2001) ‘Technical Functions as Dispositions: A Critical Assessment’, Techne: Research in Philosophy and Technology, 5(3), pp. 105–115. https://dx.doi.org/10.5840/TECHNE2001531Google Scholar
Krzywicki, A. et al. (2016) ‘Data mining for building knowledge bases: techniques, architectures and applications’, The Knowledge Engineering Review, 31(2), pp. 97–123. https://dx.doi.org/10.1017/S0269888916000047.CrossRefGoogle Scholar
Norman, D. (2013) The Design of Everyday Things: Revised and Expanded Edition. New York: Basic Books Publisher. ISBN: 9780465050659Google Scholar
Schmitt, R. et al. (2015) ‘Human Factors in Product Development and Design’, in Brecher, C. (ed.) Advances in Production Technology. Lecture Notes in Production Engineering. Springer, pp. 201–211. https://dx.doi.org/10.4018/978-1-4666-6485-2.Google Scholar