Performance evaluation of serial-parallel manufacturing systems based on the impact of heterogeneous feedstocks on machine degradation

Zhenggeng Ye, Hui Yang, Zhiqiang Cai, Shubin Si and Fuli Zhou

Reliability Engineering and System Safety, 2021, vol. 207, issue C

Abstract: Heterogeneity of feedstock quality can bring disturbances to machine degradation and product quality. Therefore, machine reliability modeling and machining quality analysis considering the flow of heterogeneous feedstocks are very essential in the performance evaluation of manufacturing systems. This paper presents a new mixture degradation model to evaluate the reliability of manufacturing machines that accounts for the flow and impact of heterogeneous feedstocks in serial-parallel manufacturing systems. Specifically, this mixture model leverages two Weibull distributions to describe machine degradation processes under the conditions of high-quality and low-quality feedstocks. Then, the flow of low-quality feedstocks is modeled by the non-homogeneous Poisson process, so that an interacting chain of quality and reliability is formulated for the serial-parallel manufacturing system. Based on the proposed model, an evaluation framework for the performance of serial-parallel manufacturing systems is provided. Finally, simulation experiments are implemented to analyze the operation status and quality loss of the system. The results showed the effectiveness of the proposed method in performance modeling of serial-parallel manufacturing systems with mixture machine degradation. The proposed approach shows strong potentials for general applications in the performance analysis of complex-structure manufacturing systems.

Keywords: Serial-parallel manufacturing system; Reliability; Feedstock; Quality; Mixture degradation; Non-homogeneous poisson process (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (7)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:207:y:2021:i:c:s0951832020308127

DOI: 10.1016/j.ress.2020.107319

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