Operational reliability and quality loss of diversely configurated manufacturing cells with heterogeneous feedstocks

Zhenggeng Ye, Zhiqiang Cai, Shubin Si, Fuli Zhou

Research output: Contribution to journalArticlepeer-review

7 Scopus citations

Abstract

Machine reliability in cellular manufacturing is a challenging engineering problem in the formation and design of manufacturing cells. The heterogeneity of feedstock quality is also common in manufacturing industry. However, so far, no work has been done to investigate the performance of diversely configurated manufacturing cells under the heterogeneous feedstocks. In this paper, considering the actual engineering condition, the uniformly random arrival and the clustered arrival of low-quality feedstocks are proposed and modeled by the homogeneous Poisson process and Hawkes process, respectively. Also, to study the mixed reliability of a machine under the impact of heterogeneous feedstocks, a mixed failure-rate model is constructed by the mixture of exponential and Weibull distributions, and the processing quality is modeled by a non-homogeneous Poisson process with a dynamic intensity function. Then, we achieve a contrastive analysis for operational reliability and quality loss of manufacturing cells with basic serial and parallel configurations under the impact of heterogeneous feedstocks. At last, the designed simulation illustrates the effectiveness of our proposed models, and some results are concluded to provide some guidelines for the design of manufacturing cells.

Original languageEnglish
Pages (from-to)955-967
Number of pages13
JournalProceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability
Volume236
Issue number6
DOIs
StatePublished - Dec 2022

Keywords

  • cell configuration
  • heterogeneous feedstocks
  • Manufacturing cell
  • quality
  • reliability

Fingerprint

Dive into the research topics of 'Operational reliability and quality loss of diversely configurated manufacturing cells with heterogeneous feedstocks'. Together they form a unique fingerprint.

Cite this