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IDENTIFYING AND COMPARING SUBPROBLEMS IN FACTORY DESIGN PROCESSES

Published online by Cambridge University Press:  19 June 2023

Jeffrey W. Herrmann
Affiliation:
University of Maryland
Erica Gralla
Affiliation:
George Washington University
Mohammad Fazelpour*
Affiliation:
University of Maryland
*
Fazelpour, Mohammad, University of Maryland, United States of America, mfazelp@umd.edu

Abstract

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When a design team faces the problem of designing a complex system, they are required to make several decisions. Because such design problems are difficult to solve all at once, teams often decompose the design problem into several smaller subproblems. This paper discusses the results of a study designed to understand how design teams decompose a factory redesign problem into sets of related subproblems and compare the subproblems obtained for each design team. This exploratory study analyzed the design activities of eight teams of professionals and used clustering to group the variables that the design teams considered. We found that the design teams used different decomposition strategies and different subproblems, but they more often considered subproblems with design variables of the same type, and some teams followed a top-down design process.

Type
Article
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

Chaudhari, A.M., Bilionis, I. and Panchal, J.H. (2020), “Descriptive models of sequential decisions in engineering design: An experimental study”, Journal of Mechanical Design, Vol. 142 No. 8.CrossRefGoogle Scholar
Colfer, L.J. and Baldwin, C.Y. (2016), “The mirroring hypothesis: Theory, evidence, and exceptions”, Industrial and Corporate Change, Vol. 25 No. 5, pp. 709738, http://doi.org/10.1093/icc/dtw027.CrossRefGoogle Scholar
Corbin, J. and Strauss, A. (2014), Basics of qualitative research: Techniques and procedures for developing grounded theory, Sage publications.Google Scholar
Gero, J.S. and Mc Neill, T. (1998), “An approach to the analysis of design protocols”, Design studies, Vol. 19 No. 1, pp. 2161.CrossRefGoogle Scholar
Glaser, B.G. and Strauss, A.L. (2017), The discovery of grounded theory: Strategies for qualitative research, Routledge.CrossRefGoogle Scholar
Gralla, E. and Herrmann, J.W. (2014), “Team design processes and decompositions in facility design”, in: Industrial and Systems Engineering Research Conference.Google Scholar
Guindon, R. (1990), “Designing the design process: Exploiting opportunistic thoughts”, Human-Computer Interaction, Vol. 5 No. 2-3, pp. 305344.CrossRefGoogle Scholar
Ho, C.H. (2001), “Some phenomena of problem decomposition strategy for design thinking: differences between novices and experts”, Design Studies, Vol. 22 No. 1, pp. 2745.CrossRefGoogle Scholar
Langley, A. (1999), “Strategies for theorizing from process data”, Academy of Management review, Vol. 24 No. 4, pp. 691710.CrossRefGoogle Scholar
Lee, J.H. and Ostwald, M.J. (2020), “Creative decision-making processes in parametric design”, Buildings, Vol. 10 No. 12, p. 242.CrossRefGoogle Scholar
Liikkanen, L.A. and Perttula, M. (2009), “Exploring problem decomposition in conceptual design among novice designers”, Design studies, Vol. 30 No. 1, pp. 3859.CrossRefGoogle Scholar
Milovanovic, J., Gero, J. and Becker, K. (2021), “Decomposition and recomposition strategies of professional engineering design teams”, in: Proceedings of the International Conference on Engineering Design (ICED21), pp. 871880.Google Scholar
Morency, M. (2017), Evaluating clustering algorithms to identify subproblems in design processes, Master's thesis, University of Maryland, College Park.Google Scholar
Morency, M., Anparasan, A., Herrmann, J., Gralla, E. et al. (2017), “Using clustering algorithms to identify sub- problems in design processes”, in: Proceedings of the 21st International Conference on Engineering Design, pp. 061070.Google Scholar
Renzi, C., Leali, F. and Di Angelo, L. (2017), “A review on decision-making methods in engineering design for the automotive industry”, Journal of Engineering Design, Vol. 28 No. 2, pp. 118143.CrossRefGoogle Scholar
Sarkar, S., Dong, A. and Gero, J.S. (2009), “Design optimization problem reformulation using singular value decomposition”, Journal of Mechanical Design, Vol. 131 No. 8.CrossRefGoogle Scholar
Sarkar, S., Dong, A., Henderson, J.A. and Robinson, P. (2014), “Spectral characterization of hierarchical modularity in product architectures”, Journal of Mechanical Design, Vol. 136 No. 1, p. 011006.CrossRefGoogle ScholarPubMed
Sosa, M.M.E., Eppinger, S.D.S. and Rowles, C.M.C. (2004), “The Misalignment of Product Architecture and Organizational Structure in Complex Product Development”, Management Science, Vol. 50 No. 12, pp. 16741689, http://doi.org/10.1287/mnsc.1040.0289.CrossRefGoogle Scholar
Tobias, C., Herrmann, J.W., Azhar, A. and Gralla, E. (2016), “Problem decomposition by design teams”, in: Fifth International Engineering Systems Symposium.Google Scholar
Ullman, D.G. (2001), “Robust decision-making for engineering design”, Journal of Engineering Design. Vol. 12 No. 1, pp. 313.CrossRefGoogle Scholar