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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
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.
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.
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