A general tool-based multi-product model for high-mixed production in semiconductor manufacturing

Liang Chen, Liuxing Chu, Cuicui Ge and Yueyuan Zhang

International Journal of Production Research, 2023, vol. 61, issue 23, 8062-8079

Abstract: Concerning the high-mixed nature in modern semiconductor manufacturing, the original ‘tool-based’ exponentially weighted moving average (EWMA) controller is proved to be unstable when the plant-model mismatches are diverse for different products, leading to large variations and lots of wastes. Hence, this paper proposes a general multi-product model for ‘tool-based’ EWMA control. The core of the model lies in the algorithm on how to estimate the noise disturbance accurately, i.e. the noise is considered as the sum of the following two parts: the estimated noise after the thread has been processed in the last cycle and the cumulative noise during the period when the thread is not on production between the two cycles. In this way, the production for a particular thread is isolated from that of others to avoid instability existing in the traditional tool-based EWMA control. Superiorities of the proposed model are demonstrated through theoretical analysis, simulation experiment and industrial case study.

Date: 2023
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DOI: 10.1080/00207543.2022.2164088

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