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Related Experiment Videos

Cloud model improved TOPSIS for comprehensive evaluation of system evolvability.

Zhiming Guo1,2, Long Guo3, Wenzhong Lou4

  • 1School of Mechatronical Engineering, Beijing Institute of Technology, Beijing, 100081, China. 3220235031@bit.edu.cn.

Scientific Reports
|June 17, 2026
PubMed
Summary

This study introduces a new framework for evaluating automobile door stamping processes, improving adaptability to dynamic information and providing systematic support. The methodology enhances performance ranking for complex manufacturing scenarios.

Keywords:
DivergenceEvolutionaryInformation cloud modelJS divergencePDCA cycle

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Area of Science:

  • Manufacturing Engineering
  • Industrial Engineering
  • Operations Research

Background:

  • Existing methods for evaluating automobile door stamping processes lack adaptation to dynamic information and systematic support.
  • Bottlenecks in evolutionary performance evaluation hinder optimization in complex manufacturing.

Purpose of the Study:

  • To establish a comprehensive methodological framework for the evolutionary performance evaluation of automobile door stamping processes.
  • To address limitations in dynamic information adaptation and systematic evaluation support.

Main Methods:

  • A multi-stage indicator system based on PDCA cycle logic was designed, incorporating static and dynamic dimensions.
  • An entropy weight-information cloud coupled weighting algorithm was developed for robust weight allocation.
  • The traditional TOPSIS method was improved using JS divergence for accurate performance ranking.

Main Results:

  • A case study evaluated five typical door stamping process schemes, yielding comprehensive performance scores from 0.1765 to 0.8689.
  • The proposed methodology demonstrated high consistency between performance ranking and actual production logic.
  • Effectiveness and industrial adaptability were verified through case validation.

Conclusions:

  • The study provides a systematic quantitative tool for evolutionary performance evaluation in complex manufacturing.
  • The developed framework offers significant theoretical reference and engineering application value for process optimization.
  • The methodology enhances decision-making for automobile door stamping processes.