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Multi-objective Evolutionary Optimisation for Product Design and Manufacturing pp 137–159Cite as

Many-Objective Evolutionary Optimisation and Visual Analytics for Product Family Design

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Abstract

Product family design involves the development of multiple products that share common components, modules and subsystems, yet target different market segments and groups of customers. The key to a successful product family is the product platform—the common components, modules and subsystems—around which the family is derived. The fundamental challenge when designing a family of products is resolving the inherent trade-off between commonality and performance. If there is too much commonality, then individual products may not meet their performance targets; however, too little sharing restricts the economies of scale that can be achieved during manufacturing and production. Multi-objective evolutionary optimisation algorithms have been used extensively to address this trade-off and determine which variables should be common (i.e., part of the platform) and which should be unique in a product family. In this chapter, we present a novel approach based on many-objective evolutionary optimisation and visual analytics to resolve trade-offs between commonality and many performance objectives. We provide a detailed example involving a family of aircraft that demonstrates the challenges of solving a 10-objective trade-off between commonality and the nine performance objectives in the family. Future research directions involving the use of multi-objective optimisation and visual analytics for product family design are also discussed.

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Acknowledgments

The first and second authors were partially supported by the National Science Foundation (NSF) under CAREER Grant No. CBET-0640443, and the third author acknowledges support from NSF Grant No. CMMI-0620948. The computational experiments in this work were supported in part through instrumentation funded by NSF Grant No. OCI-0821527. Any opinions, findings and conclusions or recommendations in this chapter are those of the authors and do not necessarily reflect the views of the National Science Foundation.

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Authors and Affiliations

  1. Industrial & Manufacturing Engineering, Pennsylvania State University, University Park, USA

    Ruchit A. Shah & Timothy W. Simpson

  2. Civil & Environmental Engineering, Pennsylvania State University, University Park, USA

    Patrick M. Reed

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  1. Ruchit A. Shah
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  2. Patrick M. Reed
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  3. Timothy W. Simpson
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Correspondence to Timothy W. Simpson .

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Editors and Affiliations

  1. , Virtual Systems Research Centre, University of Skövde, Skövde, 541 28, Sweden

    Lihui Wang

  2. , Virtual Systems Research Centre, University of Skövde, Skövde, 541 28, Sweden

    Amos H. C. Ng

  3. , Department of Mechanical Engineering, Indian Institute of Technology, Kanpur, 208016, Uttar Pradesh, India

    Kalyanmoy Deb

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Shah, R.A., Reed, P.M., Simpson, T.W. (2011). Many-Objective Evolutionary Optimisation and Visual Analytics for Product Family Design. In: Wang, L., Ng, A., Deb, K. (eds) Multi-objective Evolutionary Optimisation for Product Design and Manufacturing. Springer, London. https://doi.org/10.1007/978-0-85729-652-8_4

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  • DOI: https://doi.org/10.1007/978-0-85729-652-8_4

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