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Reliability Analysis of Multi-state Manufacturing System under Specific Operating Environment

Published: 14 March 2022 Publication History

Abstract

As modern manufacturing systems developed towards larger size, higher automation, more flexible, more efficient and higher precision continuously, the parts and equipment in systems greatly increase. As a result, the probability of system failures will be increased significantly under complex operating environment. Therefore, how to ensure the reliability of manufacturing systems has become a major problem facing the users of manufacturing systems. In order to solve this problem, a reliability analysis method of multi-state manufacturing system (MSMS) under specific operating environment was proposed in this paper. Firstly, the definition of operating environment of MSMS is stated and three aspects factors (machining process, human personnel and environmental condition) affecting the operational reliability are explained. Secondly, the state space model was introduced to describe the state degradation path of manufacturing system and its main equipment units with specific operating factors. Thirdly, an improved universal generating function (UGF) method is employed to analyze the performance state and operational reliability of MSMS. Finally, a case study of manufacturing system for machining double-parts cluster composed of cylinder is taken to prove the validity and usability of this method. It is very significant to enhance reliability and capability of manufacturing equipment by this method.

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cover image ACM Other conferences
AIAM2021: 2021 3rd International Conference on Artificial Intelligence and Advanced Manufacture
October 2021
3136 pages
ISBN:9781450385046
DOI:10.1145/3495018
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 14 March 2022

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