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A Matter of Factor: A Proposed Method for Identifying Factors that Influence Design Effort Levels in Product Design

Published online by Cambridge University Press:  26 July 2019

Abstract

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Design effort, the amount of time required to complete a project or task (Salam et al., 2009; Salam and Bhuiyan, 2016), is a required resource for any design project which can be influenced by a number of factors. Estimating design effort is a significant challenge that can be mitigated through an understanding of these influential factors. This understanding is held as tacit knowledge by experts, earned through experience; yet, although these factors vary in type and impact, understanding their details can provide insight and improve future estimations. Some previous methods to estimate design effort identify these factors, either from: expert opinion, or historical data analysis with each approach has advantages and disadvantages.

This paper is comprised of three parts:

A review of published methods and tools for estimating product design effort and whether they consider and identify influential factors; an analysis of possible trends in the identification of factors influencing product design project length; and a new method for identifying the influential factors of product design project length.

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) 2019

References

Andersson, J., Pohl, J. and Eppinger, S.D. (1998), “A design process modelling approach incorporating nonlinear elements”, Proceedings of 1998 DETC: ASME Design Theory and Methodology Conference, Atlanta, Georgia.Google Scholar
Bashir, H.A. and Thomson, V. (1999), “Metrics for design projects: a review”, Design Studies, Vol. 20 No. 3, pp. 263277.Google Scholar
Bashir, H.A. and Thomson, V. (2001a), “Models for estimating design effort and time”, Design Studies, Vol. 22 No. 2, pp. 141155.Google Scholar
Bashir, H.A. and Thomson, V. (2001b), “An analogy-based model for estimating design effort”, Design Studies, Vol. 22 No. 2, pp. 157167.Google Scholar
Bashir, H.A. and Thomson, V. (2004), “Estimating design effort for GE hydro projects”, Computers & Industrial Engineering, Vol. 46 No. 2, pp. 195204.Google Scholar
Benedetto, H., Bernardes, M.M.eS. and Vieira, D. (2018), “Proposed framework for estimating effort in design projects, International Journal of Managing Projects in Business”, Emerald, Vol. 11 No. 2, pp. 257274.Google Scholar
Carrascosa, M., Eppinger, S. and Whitney, D.E. (1998), “Using the Design Structure Matrix to Estimate Product Development Time”.Google Scholar
Cho, S.-H. and Eppinger, S.D. (2005), “A simulation-based process model for managing complex design projects”, IEEE Transactions on Engineering Management, Vol. 52 No. 3, pp. 316328.Google Scholar
Dong, C., Horinouchi, T., Nomaguchi, Y. and Fujita, K. (2014), “Design Project Planning Method With Task Option Model and Two-Level Multi-Objective Optimization”.Google Scholar
Eckert, C.M. and Clarkson, P.J. (2010), “Planning development processes for complex products”, Research in Engineering Design, Vol. 21 No. 3, pp. 153171.Google Scholar
Eppinger, S.D., Nukala, M.V and Whitney, D.E. (1997), “Generalised models of design interation using signal flow graphs”, Research in Engineering Design, Vol. 9 No. 2, pp. 112123.Google Scholar
Fisher, R.A. (1949), The Design of Experiments, 5th ed., Oliver and Boyd, Edinburgh.Google Scholar
Griffin, A. (1993), “Metrics for measuring product development cycle time”, Journal of Product Innovation Management, Vol. 10 No. 2, pp. 112125.Google Scholar
Griffin, A. (1997), “Modeling and measuring product development cycle time across industries”, Journal of Engineering and Technology Management, Vol. 14 No. 1, pp. 124.Google Scholar
Harfield, S. (2007), “On design ‘problematization’: Theorising differences in designed outcomes”, Design Studies, Vol. 28 No. 2, pp. 159173.Google Scholar
Hellenbrand, D., Helten, K. and Lindemann, U. (2010), “Approach for development cost estimation in early design phases”, pp. 779788.Google Scholar
Holliman, A., Thomson, A. and Hird, A. (2018), “Planning product design & development: Resource-influencing factors based on experience”, Proceedings of the 25th International European Operations Management Association (EurOMA) Conference, Budapest, Hungary.Google Scholar
Jack, H. (2013), Chapter 1 - An Overview of Design Projects BT - Engineering Design, Planning, and Management, Academic Press, Boston, pp. 132.Google Scholar
Jacome, M.F. and Lapinskii, V. (1997), “NREC: risk assessment and planning of complex designs”, IEEE Design & Test of Computers, Vol. 14 No. 1, pp. 4249.Google Scholar
Krishnan, V., Eppinger, S.D. and Whitney, D.E. (1995), “Accelerating Product Development by the Exchange of Preliminary Product Design Information”, Journal of Mechanical Design, ASME, Vol. 117 No. 4, pp. 491498.Google Scholar
De Lessio, M.P. (2016), “Planning the product design process”, Proceedings of International Design Conference, DESIGN, Vol. DS 84, New York University, 5 MetroTech Center, Brooklyn, NY, United States, pp. 14751486.Google Scholar
O'Donovan, B., Eckert, C., Clarkson, J. and Browning, T.R. (2005), “Design planning and modelling”, in Clarkson, J. and Eckert, C. (Eds.), Design Process Improvement: A Review of Current Practice, Springer London, London, pp. 6087.Google Scholar
Pich, M.T., Loch, C.H. and De Meyer, A. (2002), “On Uncertainty, Ambiguity, and Complexity in Project Management”, Management Science, INFORMS, Vol. 48 No. 8, pp. 10081023.Google Scholar
Pollmanns, J., Hohnen, T. and Feldhusen, J. (2013), “An Information Model of the Design Process for the Estimation of Product Development Effort BT - Smart Product Engineering”, in Abramovici, M. and Stark, R. (Eds.), Springer Berlin Heidelberg, Berlin, Heidelberg, pp. 885894.Google Scholar
Saaty, T.L. (1980), The Analytic Hierarchy Process: Planning, Priority Setting, Resource Allocation, McGraw-Hill International Book Co., New York; London.Google Scholar
Salam, A. and Bhuiyan, N. (2016), “Estimating design effort using parametric models: A case study at Pratt & Whitney Canada”, Concurrent Engineering, SAGE Publications Ltd STM, Vol. 24 No. 2, pp. 129138.Google Scholar
Salam, A., Bhuiyan, N., Gouw, G.J. and Raza, S.A. (2009), “Estimating design effort for the compressor design department: a case study at Pratt & Whitney Canada”, Design Studies, Vol. 30 No. 3, pp. 303319.Google Scholar
Serrat, J., Lumbreras, F. and López, A.M. (2013), “Cost estimation of custom hoses from STL files and CAD drawings”, Computers in Industry, Vol. 64 No. 3, pp. 299309.Google Scholar
Shang, Z.-G. and Yan, H.-S. (2016), “Product Design Time Forecasting by Kernel-Based Regression with Gaussian Distribution Weights”, Entropy, available at: https://dx.doi.org/10.3390/e18060231.Google Scholar
Smith, R.P. and Eppinger, S.D. (1997), “A Predictive Model of Sequential Iteration in Engineering Design, Sloan School of Management”, Massachusetts Institute of Technology.Google Scholar
Steward, D.V. (1981), “The design structure system: A method for managing the design of complex systems”, IEEE Transactions on Engineering Management.Google Scholar
Vapnik, V.N. (1995), The Nature of Statistical Learning Theory, Springer-Verlag New York, Inc.Google Scholar
Wang, Z., Tong, S. and Huang, L. (2015), “Research on the time prediction model of product variant design”, 2015 IEEE International Conference on Mechatronics and Automation (ICMA), pp. 572576.Google Scholar
Xu, D. and Yan, H.-S. (2006), “An intelligent estimation method for product design time”, The International Journal of Advanced Manufacturing Technology, Vol. 30 No. 7, pp. 601613.Google Scholar
Xu, D. and Yan, H.S. (2004), “Research on intelligent estimation method for product design time (in Chinese)”, Control Decision, Vol. 19 No. 2, pp. 314318.Google Scholar
Yan, H.-S. and Shang, Z.-G. (2015), “Method for Product Design Time Forecasting Based on Support Vector Regression with Probabilistic Constraints”, Applied Artificial Intelligence, Taylor & Francis, Vol. 29 No. 3, pp. 297312.Google Scholar
Yan, H., Wang, B., Xu, D. and Wang, Z. (2010), “Computing Completion Time and Optimal Scheduling of Design Activities in Concurrent Product Development Process”, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans, Vol. 40 No. 1, pp. 7689.Google Scholar
Yan, H.S. and Xu, D. (2007), “An Approach to Estimating Product Design Time Based on Fuzzy -nu-Support Vector Machine”, IEEE Transactions on Neural Networks, Vol. 18 No. 3, pp. 721731.Google Scholar
Yuan, Y.X. and Sun, W.Y. (1997), Optimal Theories and Methods, Science Press, Beijing, China.Google Scholar
Zhigen, S. and Yan, H. (2011), “Forecasting product design time based on Gaussian Margin Regression”, IEEE 2011 10th International Conference on Electronic Measurement & Instruments, Vol. 4, pp. 8689.Google Scholar