Manufacturing process similarity measurement model and application based on process constituent elements

Abstract

Planners and designers of production systems must frequently evaluate the similarities in the manufacturing process of various products to achieve efficient and economical production. The purpose is to reasonably arrange mixed production. The similarity of manufacturing technique processes is an important basis for classifying product manufacturing processes. This study proposes an innovative method based on process constituent elements model to objectively calculate the similarity of product manufacturing processes. Firstly, the similarity model of the manufacturing technique process is established on the basis of six dimensions of process constituent elements, namely, input, output, resource, environment, value-added processing activity and quality control & inspection. Secondly, the characteristics of the six dimensions of the process constituent elements are determined. Corresponding methods are applied to solve the similarity of process constituent elements in each dimension on the basis of the characteristic attributes of process constituent elements of different dimensions. Thirdly, extended interval analytic hierarchy process and quantitative calculation method based on angle information entropy are integrated to determine the weights of dimensions of the six elements. Lastly, the proposed method is applied to the process classification of a group of product manufacturing technique processes, and the feasibility and effectiveness of the method are proven.

Keywords:

• manufacturing technique process
• similarity
• process constituent elements
• angle information entropy
• process classification

Acknowledgements

The authors express their gratitude to an aviation company that provided historical data and to the design experts who participated in the analysis and evaluation. In additions, the authors would like to thank all of the anonymous referees and editors for the comments and suggestions, which have helped to improve the paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research is supported by the National Natural Science Foundation of China [grant numbers 71661023 and 71161018].