Abstract
This paper outlines a fuzzy cognitive mapping (FCM) approach for engaging users in constructing a model for engineering design system analysis. The model’s scope is drawn in reference to a socio-technical system and demonstrated with an assembly production system (a socio-technical system archetype). In particular, this paper focuses on modeling an existing assembly production system that needs to be re-designed, then analyzing the system models to inform the re-design task. The modeling approach engages users as participants (18 in this research) in observation and interviews, and these data are coded into adjacency matrices and fuzzy cognitive maps separately then integrated. The ability to model multiple users and technical entities together in breadth and detail, qualitatively and quantitatively, enables designers to zoom in to see the detail and zoom out to see a holistic perspective. The models are analyzed for overall cause, effect, and central variables. Through the FCM analysis of these variables, the elements of the existing design solution are made explicit, including inputs, external and boundary constraints, design principles, outcomes and outputs, function, and operations and structure. This is particularly useful in re-design, as demonstrated in the industrial re-design project here, where the FCM models make the current system design explicit and their analyses inform re-design intent by being synthesized into re-design foci and tasks.
Similar content being viewed by others
References
Achiche S, Appio FP, McAloone TC, Di Minin A (2013) Fuzzy decision support for tools selection in the core front end activities of new product development. Res Eng Des 24:1–18. https://doi.org/10.1007/s00163-012-0130-4
Augustine M, Yadav OP, Jain R, Rathore A (2012) Cognitive map-based system modeling for identifying interaction failure modes. Res Eng Des 23:105–124. https://doi.org/10.1007/s00163-011-0117-6
Baxter D, Gao J, Case K et al (2007) An engineering design knowledge reuse methodology using process modelling. Res Eng Des 18:37–48. https://doi.org/10.1007/s00163-007-0028-8
Borri D, Camarda D, Pluchinotta I, Esposito D (2015) Supporting environmental planning: knowledge management through fuzzy cognitive mapping. In: Luo Y (ed) Cooperative design, visualization and engineering. Springer, Switzerland, pp 228–235
Brissaud D, Garro O, Poveda O (2003) Design process rationale capture and support by abstraction of criteria. Res Eng Des 14:162–172. https://doi.org/10.1007/s00163-003-0038-0
Cardin M-A, Kolfschoten GL, Frey DD et al (2013) Empirical evaluation of procedures to generate flexibility in engineering systems and improve lifecycle performance. Res Eng Des 24:277–295. https://doi.org/10.1007/s00163-012-0145-x
Carley K, Palmquist M (1992) Extracting representing and analyzing mental models. Soc Forces 70:601–636. https://doi.org/10.1093/sf/70.3.575
Chakrabarti A, Blessing LTM (2014) Theories and models of design: a summary of findings. In: Chakrabarti A, Blessing LTM (eds) An anthology of theories and models of design. Springer, London, pp 1–45
Cherns A (1989) The social engagement of social science: a tavistock anthology. The Tavistock Institute of Human Relations, London
Clancey WJ (1993) The knowledge level reinterpreted: modeling socio-technical systems. Int J Intell Syst 8:33–49. https://doi.org/10.1002/int.4550080104
Dieter G, Schmidt L (2008) Engineering design, 4th edn. McGraw-Hill, New York
Dixon LA, Colton JS (2000) A process management strategy for re-design: an anchoring adjustment approach. J Eng Des 11:159–173. https://doi.org/10.1080/09544820050034259
Eckert C, Stacey M (2010) What is a process model? Reflections on the epistemology of process models. In: Heisig P, Clarkson P, Vajna S (eds) Modelling and management of engineering processes. Springer, New York, pp 3–14
Emery F (1989) The assembly line: its logic and our future. In: Trist E, Hugh M (eds) The socio-technical systems perspective. The Tavistock Institute of Human Relations, London, pp 1–19
FCMapper [Computer software] (2018) Retrieved from http://www.fcmappers.net/joomla/
Fernandes J, Henriques E, Silva A, Moss MA (2014) A method for imprecision management in complex product development. Res Eng Des 25:309–324. https://doi.org/10.1007/s00163-014-0178-4
Gavankar PS, Rao SK (1995) Manufacturability analysis using fuzzy cognitive maps. In: Computers in engineering and proceedings of the 1995 database symposium. ASME, Boston, pp 1211–1222
Gish L, Hansen CT (2013) A socio-technical analysis of work with ideas in NPD: an industrial case study. Res Eng Des 24:411–427. https://doi.org/10.1007/s00163-013-0159-z
Goel A, Helms M (2013) Theories, models, programs and tools of design: views from artificial intelligence, cognitive science and human-centered computing. In: Chakrabarti A, Blessing L (eds) An anthology of theories and models of design. Springer, Switzerland, pp 415–430
Hayes JR (1989) The complete problem solver, 2nd edn. Routledge, New Jersey
Hu J, Cardin M-A (2015) Generating flexibility in the design of engineering systems to enable better sustainability and lifecycle performance. Res Eng Des 26:121–143. https://doi.org/10.1007/s00163-015-0189-9
Jing N, Lu S (2011) Modeling co-construction processes in a socio-technical framework to support collaborative engineering design. IEEE Trans Syst Man Cybern 41:297–305. https://doi.org/10.1109/TSMCC.2010.2092426
Jones A, Artikis A, Pitt J (2013) The design of intelligent socio-technical systems. Artif Intell Rev 39:5–20. https://doi.org/10.1007/s10462-012-9387-2
Kember P, Murray H (1988) Towards socio-technical prototyping of work systems. Int J Prod Res 26:133. https://doi.org/10.1080/00207548808947846
Kim K-Y, Lee K-C, Kwon O (2008) The role of the fuzzy cognitive map in hierarchical semantic net-based assembly design decision making. Int J Comput Integr Manuf 21:803–824. https://doi.org/10.1080/09511920701756969
Koren Y (2010) The global manufacturing revolution: product-process-business integration and reconfigurable systems. Wiley, New Jersey
Krefting L (1991) Rigor in qualitative research: the assessment of trustworthiness. Am J Occup Ther 45(3):214–222. https://doi.org/10.5014/ajot.45.3.214
Laing A, Frazer M, Cole D et al (2005) Study of the effectiveness of a participatory ergonomics intervention in reducing worker pain severity through physical exposure pathways. Ergonomics 48:150–170. https://doi.org/10.1080/00140130512331325727
Laing A, Cole D, Theberge N et al (2007) Effectiveness of a participatory ergonomics intervention in improving communication and psychosocial exposures. Ergonomics 50:1092–1109. https://doi.org/10.1080/00140130701308708
Legardeur J, Boujut JF, Tiger H (2010) Lessons learned from an empirical study of the early design phases of an unfulfilled innovation. Res Eng Des 21:249–262. https://doi.org/10.1007/s00163-010-0090-5
Lin Y, Zhang WJ (2004) Towards a novel interface design framework: function–behavior–state paradigm. Int J Hum Comput St 61:259–297. https://doi.org/10.1016/j.ijhcs.2003.11.008
Lu SC-Y, Cai J (2001) A collaborative design process model in the sociotechnical engineering design framework. AI EDAM 15:3–20
Malak R, Paredis CJJ (2007) Validating behavioral models for reuse. Res Eng Des 18:111–128. https://doi.org/10.1007/s00163-007-0031-0
Naumann T, Tuttass I, Kallenborn O, Königs SF (2011) Social systems engineering—an approach for efficient systems development. In: Proceedings of the 18th international conference on engineering design (ICED 11). Denmark, pp 357–368
Ostrosi E, Haxhiaj L, Fukuda S (2011) Fuzzy modelling of consensus during design conflict resolution. Res Eng Des 23:53–70. https://doi.org/10.1007/s00163-011-0114-9
Özesmi U, Özesmi SL (2004) Ecological models based on people’s knowledge: a multi-step fuzzy cognitive mapping approach. Ecol Model 176:43–64. https://doi.org/10.1016/j.ecolmodel.2003.10.027
Pahl G, Beitz W, Feldhusen J, Grote K-H (2007) Engineering design: a systematic approach. Springer, London
Pajek [Computer software] (2018) Retrieved from http://mrvar.fdv.uni-lj.si/pajek/
Panebianco S, Pahl-Wostl C (2006) Modelling socio-technical transformations in wastewater treatment—a methodological proposal. Technovation 26:1090–1100. https://doi.org/10.1016/j.technovation.2005.09.017
Papageorgiou EI (ed) (2014) Fuzzy cognitive maps for applied sciences and engineering. Springer, Berlin
Papageorgiou EI, Salmeron JL (2014) Methods and algorithms for fuzzy cognitive map-based modeling. Fuzzy cognitive maps for applied sciences and engineering. Springer, Berlin, pp 1–28
Piela P, Katzenberg B, McKelvey R (1992) Integrating the user into research on engineering design systems. Res Eng Des 3:211–221. https://doi.org/10.1007/BF01580843
Roberts FS (1976) The questionnaire method. Structure of decision: the cognitive maps of political elites. Princeton University Press, New Jersey, pp 333–342
Römer A, Leinert S, Sachse P (2000) External support of problem analysis in design problem solving. Res Eng Des 12:144–151. https://doi.org/10.1007/s001630050029
Schneider M, Shnaider E, Kandel A, Chew G (1998) Automatic construction of FCMs. Fuzzy Set Syst 93:161–172. https://doi.org/10.1016/S0165-0114(96)00218-7
Shenton AK (2004) Strategies for ensuring trustworthiness in qualitative research projects. Educ Inform 22(2):63–75. https://doi.org/10.3233/EFI-20014-22201
Silva (1996) Networked virtual worlds by using fuzzy cognitive maps in the industrial design of automobiles. In: Proceedings of the conference on supercomputer applications in the transportation industries. Automotive Automation, Croydon, UK, pp 157–164
Stappers PJ, Visser FS, et al (2007) Bringing participatory design techniques to industrial design engineers. In: Proceedings of the 9th international conference on engineering and product design education. Design Society, New Castle, UK, pp 1–6
Stevenson S, Dooley KJ, Anderson JC (1994) The use of best design practices: an analysis of US navy contractors. Res Eng Des 6:14–24. https://doi.org/10.1007/BF01588088
Sundin A (2003) Computer visualization and participatory ergonomics as methods in workplace design. Hum Factor Ergon Manuf 13:1–17
Sundin A, Christmanssona M, Larsson M (2004) A different perspective in participatory ergonomics in product development improves assembly work in the automotive industry. Int J Ind Ergon 33:1–14
Sutcliffe AG (2000) Requirements analysis for socio-technical system design. Inform Syst 25:213–233. https://doi.org/10.1016/S0306-4379(00)00016-8
Topcu TG, Mesmer BL (2018) Incorporating end-user models and associated uncertainties to investigate multiple stakeholder preferences in system design. Res Eng Des 29:411–431. https://doi.org/10.1007/s00163-017-0276-1
Townsend V (2015) From participation to differentiation: a framework for re-designing a socio-technical system. Dissertation, University of Windsor
Townsend V, Urbanic J (2015) A case study measuring the impact of a participatory design intervention on system complexity and cycle time in an assemble-to-order system. Procedia Manuf 1:134–145. https://doi.org/10.1016/j.promfg.2015.09.076
Vermaas PE, Kroes P, Van de Poel I et al (2011) A philosophy of technology: from technical artefacts to sociotechnical systems. Morgan & Claypool, California
Vink P, Koningsveld EAP, Molenbroek JF (2006) Positive outcomes of participatory ergonomics in terms of greater comfort and higher productivity. Appl Ergon 37:537–546. https://doi.org/10.1016/j.apergo.2006.04.012
Wrightson MT (1976) The documentary coding method. Structure of decision: the cognitive maps of political elites. Princeton University Press, New Jersey, pp 291–332
Wynn DC, Clarkson PJ (2018) Process models in design and development. Res Eng Des 29:161–202. https://doi.org/10.1007/s00163-017-0262-7
Zhang WJ, Lin Y, Sinha N (2011) On the function-behavior-structure model for design. In: Proceedings of the Canadian Engineering Education Association. Canadian Engineering Education Association. St John’s, Newfoundland, pp 1–8
Zhao B, Steier F (1993) Effective CIM implementation using socio-technical principles. Ind Manag 35:27
Zhao B, Verma A, Kapp B (1992) Implementing advanced manufacturing technology in organizations: a socio-technical systems analysis. IEEE Engineering management conference, managing in a global environment. IEEE International, Eatontown, NJ, pp 9–13
Acknowledgements
Funding for this research was provided by the Natural Sciences and Engineering Research Council of Canada (Grant no. EGP/460894-2013). The authors also thank the research participants and industrial company for their participation in this research study.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Appendices
Appendix A: Transcript excerpt and FCM coding
Interviewer: How would you describe the current assembly process?
Participant: Umm… simplified.
Interviewer: Ok
Participant: You know, we’ve, over the years we’ve gone from doing a few hundred now to probably [XX] …so, and, um, we’re currently struggling with space and personnel. So we’ve, it’s grown into its own type of department within a department now and we’re struggling to staff it accordingly and be efficient at it. Now that we don’t have a lot of room in our building we’re unable to bring everything down and lay it all out ahead of the run. Usually what you’d like to do is bring everything down, let’s say you are going to do 200 [assemblies], you want to bring every piece of that [assembly]…all the [X], all the [Y], all the componentry, bring it down, make sure it’s all accurate, check it over, sign off on it, and then say “ok… let’s build.” That’s the efficient way. Now, we currently have to bring it in pieces, so at multiple times our material handlers are going to gather the pieces rather than doing it once due to our lack of space…. [interview continues]
See Table 11.
Appendix B: Integrated interview plots (interviews 1, 2 and 3)
Appendix C: Codes from participant interviews
See Table 12.
Rights and permissions
About this article
Cite this article
Townsend, V., Urbanic, J. Fuzzy cognitive modeling with users for design system analysis. Res Eng Design 30, 509–537 (2019). https://doi.org/10.1007/s00163-019-00318-4
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00163-019-00318-4