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Towards comprehensive digital evaluation of low-carbon machining process planning

Published online by Cambridge University Press:  25 July 2022

Zhaoming Chen Open the ORCID record for Zhaoming Chen [Opens in a new window] ,
Jinsong Zou  and
Wei Wang
Zhaoming Chen*
Affiliation:
Chongqing University, Chongqing 400044, China Chongqing School, University of Chinese Academy of Sciences, Chongqing 400714, China
Jinsong Zou
Affiliation:
Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China
Wei Wang
Affiliation:
College of Computer Science and Engineering, Chongqing University of Technology, Chongqing 400054, China
*
Author for correspondence: Zhaoming Chen, E-mail: zhaomingc_sc@163.com
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Abstract

Low-carbon process planning is the basis for the implementation of low-carbon manufacturing technology. And it is of profound significance to improve process executability, reduce environmental pollution, decrease manufacturing cost, and improve product quality. In this paper, based on the perceptual data of parts machining process, considering the diversity of process planning schemes and factors affecting the green manufacturing, a multi-level evaluation criteria system is established from the aspects of processing time, manufacturing cost and processing quality, resource utilization, and environmental protection. An integrated evaluation method of low-carbon process planning schemes based on digital twins is constructed. Each index value is normalized by the polarized data processing method, its membership is determined by the fuzzy statistical method, and the combination weight of each index is determined by the hierarchical entropy weight method to realize the organic combination of theoretical analysis, practical experience, evaluation index, and process factors. The comprehensive evaluation of multi-process planning schemes is realized according to the improved fuzzy operation rules, and the best process planning solution is finally determined. Finally, taking the low-carbon process planning of an automobile part as an example, the feasibility and effectiveness of this method are verified by the evaluation of three alternative process planning schemes. The results show that the method adopted in this paper is more in line with the actual production and can provide enterprises with the optimal processing scheme with economic and environmental benefits, which may be helpful for more data-driven manufacturing process optimization in the future.

Keywords

Combined weightcomprehensive evaluationdigital twinlow-carbon manufacturingprocess planning
Type
Research Article
Information
AI EDAM , Volume 36 , 2022 , e21
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Copyright
Copyright © The Author(s), 2022. Published by Cambridge University Press

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