Modeling, analysis, and improvement of integrated productivity and quality system in battery manufacturing

Feng Ju, Jingshan Li, Guoxian Xiao, Jorge Arinez and Weiwen Deng

IISE Transactions, 2015, vol. 47, issue 12, 1313-1328

Abstract: A battery manufacturing system typically includes a serial production line with multiple inspection stations and repair processes. In such systems, productivity and quality are tightly coupled. Variations in battery quality may add up along the line so that the upstream quality may impact the downstream operations. The repair process after each inspection can also affect downstream quality behavior and may further impose an effect on the throughput of conforming batteries. In this article, an analytical model of such an integrated productivity and quality system is introduced. Analytical methods based on an overlapping decomposition approach are developed to estimate the production rate of conforming batteries. The convergence of the method is analytically proved and the accuracy of the estimation is numerically justified. In addition, bottleneck identification methods based on the probabilities of blockage, starvation, and quality statistics are investigated. Indicators are proposed to identify the downtime and quality bottlenecks that remove the need to calculate throughput and quality performance and their sensitivities. These methods provide a quantitative tool for modeling, analysis, and improvement of productivity and quality in battery manufacturing systems and can be applied to other manufacturing systems ameanable to investigation using integrated productivity and quality models.

Date: 2015
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DOI: 10.1080/0740817X.2015.1005777

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