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Sustainability-oriented product modular design using kernel-based fuzzy c-means clustering and genetic algorithm

  • Jihong Yan*
  • , Chunhua Feng
  • , Kai Cheng
  • *Corresponding author for this work
  • School of Mechatronics Engineering, Harbin Institute of Technology
  • Brunel University London

Research output: Contribution to journalArticlepeer-review

Abstract

With increasing sustainable development consciousness, sustainable design plays an important role, not only in the design phase, but also in the manufacturing process. Existing design methods, including life cycle design and environmental design, have not fully considered sustainability requirements. A modular design methodology is proposed for achieving sustainable design as well as fulfilling functional requirements. Factors related to function and sustainability of a product, such as material, manufacturability, component life, and so on, are defined as modular drivers. A design structure matrix, with great advantages on analyzing the correlation between product system elements, is employed to establish a correlation matrix between components. A kernel-based fuzzy c-means algorithm is used to integrate components of a product into different modules based on their correlation distance. Meanwhile, a genetic algorithm is employed to determine the optimal clustering number on account of its efficiency in coming up with the global solutions. In addition, an assessment model for product sustainability is established considering economic, social, and environmental factors. Finally, a reduction gear is used as a case study example to show the effectiveness of the proposed sustainability-oriented modular design method.

Original languageEnglish
Pages (from-to)1635-1647
Number of pages13
JournalProceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture
Volume226
Issue number10
DOIs
StatePublished - Oct 2012
Externally publishedYes

Keywords

  • Sustainability
  • kernel-based fuzzy c-means clustering
  • modular design
  • modular drivers
  • optimization clustering number

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