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A model for assessment of the impact of configuration changes in complex products

Author

Listed:
  • Yu-jie Zheng

    (Shandong University of Science and Technology)

  • Yu Yang

    (Chongqing University)

  • Na Zhang

    (Chongqing University)

Abstract

An assessment of the impact of configuration changes in complex products is significant for improving the accuracy of change decision-making. Most related studies lack objectivity, systematicness and applicability. For this reason, a four-phase model for the assessment of this impact is proposed. In Phase I, a network model for parameter relationships of complex products is built to accurately express the complex product structures. In Phase II, an assessment method for the change propagation probability based on the gray comprehensive relation analysis and an assessment method for the propagation impact probability via the analysis of configuration change values are proposed to compute the two probabilities objectively. In Phase III, the change propagation method is introduced to precisely assess the impact of the configuration changes between two parameters. In Phase IV, a method for assessing the overall impact of configuration changes via the division of the parameters into stages is put forward to systematically assess the impact of configuration changes on the whole complex products. The methods in the four-phase model are easy to program and could further improve the assessment efficiency. Besides, a practical application of the proposed assessment model is suggested to verify the validity and applicability of this research.

Suggested Citation

  • Yu-jie Zheng & Yu Yang & Na Zhang, 2020. "A model for assessment of the impact of configuration changes in complex products," Journal of Intelligent Manufacturing, Springer, vol. 31(2), pages 501-527, February.
    • Handle: RePEc:spr:joinma:v:31:y:2020:i:2:d:10.1007_s10845-018-01461-w
    DOI: 10.1007/s10845-018-01461-w
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    References listed on IDEAS

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    1. Eckert, Claudia M. & Keller, René & Earl, Chris & Clarkson, P. John, 2006. "Supporting change processes in design: Complexity, prediction and reliability," Reliability Engineering and System Safety, Elsevier, vol. 91(12), pages 1521-1534.
    2. Ni Li & Xiang Li & Yuzhong Shen & Zhuming Bi & Minghui Sun, 2015. "Risk assessment model based on multi-agent systems for complex product design," Information Systems Frontiers, Springer, vol. 17(2), pages 363-385, April.
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    Cited by:

    1. Yuming Guo, 2023. "Towards the efficient generation of variant design in product development networks: network nodes importance based product configuration evaluation approach," Journal of Intelligent Manufacturing, Springer, vol. 34(2), pages 615-631, February.

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