Research on Identification of Critical Quality Features of Machining Processes Based on Complex Networks and Entropy-CRITIC Methods

Author:

Qu Dongyue1,Liang Wenchao1ORCID,Zhang Yuting2,Gu Chaoyun1ORCID,Zhou Guangyu1,Zhan Yong1

Affiliation:

1. College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, China

2. Institute of Advanced Technology, Heilongjiang Academy of Sciences, Harbin 150080, China

Abstract

Aiming at the difficulty in effectively identifying critical quality features in the complex machining process, this paper proposes a critical quality feature recognition method based on a machining process network. Firstly, the machining process network model is constructed based on the complex network theory. The LeaderRank algorithm is used to identify the critical processes in the machining process. Secondly, the Entropy-CRITIC method is used to calculate the weight of the quality features of the critical processes, and the critical quality features of the critical processes are determined according to weight ranking results. Finally, the feasibility and effectiveness of the method are verified by taking the medium-speed marine diesel engine coupling rod machining as an example. The results show that the method can still effectively identify the critical quality features in the case of small sample data and provide support for machining process optimization and quality control, thus improving product consistency, reliability, and machining efficiency.

Funder

designing and verifying key technologies of marine engines’ high reliability in the major special project ship research program of MIIT

Publisher

MDPI AG

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