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The Use of a Complexity Model to Facilitate in the Selection of a Fuel Cell Assembly Sequence

  • Mussawar Ahmad*
  • , Bugra Alkan
  • , Bilal Ahmad
  • , Daniel Vera
  • , Robert Harrison
  • , James Meredith
  • , Axel Bindel
  • *Corresponding author for this work

    Research output: Contribution to conferenceConference Paperpeer-review

    8 Citations (Scopus)

    Abstract

    Various tools and methods exists for arriving at an optimised assembly sequence with most using a soft computing approach. However, these methods have issues including susceptibly to early convergence and high computational time. The typical objectives for these methods are to minimise the number of assembly change directions, orientation changes or the number of tool changes. This research proposes an alternative approach whereby an assembly sequence is measured based on its complexity. The complexity value is generated using design for assembly metrics and coupled with considerations for product performance, component precedence and material handling challenges to arrive at a sequence solution which is likely to be closest to the optimum for cost and product quality. The case presented in this study is of the assembly of a single proton exchange membrane fuel cell. This research demonstrates a practical approach for determining assembly sequence using data and tools that are used and available in the wider industry. Further work includes automating the sequence generation process and extending the work by considering additional factors such as ergonomics.

    Original languageEnglish
    Pages169-174
    Number of pages6
    DOIs
    Publication statusPublished - 1 Jan 2016
    Event6th CIRP Conference on Assembly Technologies and Systems, CATS 2016 - Gothenburg, Sweden
    Duration: 16 May 201618 May 2016

    Conference

    Conference6th CIRP Conference on Assembly Technologies and Systems, CATS 2016
    Country/TerritorySweden
    CityGothenburg
    Period16/05/1618/05/16

    Keywords

    • Assembly sequence planning
    • complexity management
    • proton exchange membrane fuel cell

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