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- Title
Reliability allocation method of comprehensive weight computer numerical control machine tool based on failure correlation and factor correlation.
- Authors
Gu, Dongwei; Xu, Zhen; Zhong, Yuhong; Li, Qihan; Long, Zhe
- Abstract
According to the shortage of independent hypothesis allocation models between influence factors and subsystems, a reliability allocation method considering influence factor correlation and subsystem failure correlation is proposed. The CNC (Computer Numerical Control) machine tool is taken as the research object. Using Copula function to analyze failure correlation analysis between subsystems, establish subsystem complete reliability model and integrated importance measure model under failure correlation. The four factors of influencing reliability allocation are subsystem complexity, integrated importance measure of subsystem based on failure correlation, failure frequency, and specific gravity ratio of failure downtime. The correlation analysis among the influencing factors was carried out by using gray correlation theory, and the subjective weight of the subsystem was determined. The IEW‐VIKOR (Information Entropy Weight‐Vlsekriterijumska Optimizacija I Kompromisno Resenje) method is used to determine the objective weights of subsystems. The comprehensive weight of the subsystem is also obtained through combinatorial empowerment. The reliability allocation of the CNC machine tool subsystem was carried out according to the failure correlation reliability model, and the results of failure independence and failure correlation hypothesis allocation were compared and analyzed. When the reliability index is the same, the reliability allocation method proposed in this paper can assign lower reliability to each subsystem, which is of great significance to improve the reliability of CNC machine tools and reduce the difficulty of reliability design
- Subjects
NUMERICAL control of machine tools; AUTOMATION; REDUNDANCY in engineering; COPULA functions; SPECIFIC gravity
- Publication
Quality & Reliability Engineering International, 2023, Vol 39, Issue 8, p3285
- ISSN
0748-8017
- Publication type
Article
- DOI
10.1002/qre.3124