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Title: An equivalent conversion method for dual-armed multi-cluster tool scheduling problems with multi-wafer types

Authors: Zhu Wang; Binghai Zhou; Zhiqiang Lu; Damien Trentesaux; Abdelghani Bekrar

Addresses: Logistics Engineering College, Shanghai Maritime University, Shanghai 201306, China ' School of Mechanical Engineering, Tongji University, Shanghai 201804, China ' School of Mechanical Engineering, Tongji University, Shanghai 201804, China ' LAMIH, UMR CNRS 8201, University of Valenciennes and Hainaut-Cambrésis, Valenciennes, 59313, France ' LAMIH, UMR CNRS 8201, University of Valenciennes and Hainaut-Cambrésis, Valenciennes, 59313, France

Abstract: Due to the trend towards 450 mm diameter wafers and customisation, an increase in wafer diversity and transient operation are anticipated for multi-cluster tools in wafer fabrication. While most previous studies focus on steady state scheduling problem of cluster tools, research on multi-cluster tools scheduling problems with transient operations is still at early stage. This article addresses the dual-armed multi-cluster tools scheduling problem with transient operations and multiple wafer types. The problem is subject to residency constraints and makespan is adopted as the performance metrics. A non-linear mathematical model of the problem is established. To solve this problem, a time constraint sets-based heuristic algorithm, called the TB algorithm, is proposed in this article. Based on SWAP strategy, this article proposed the conception of virtual buffer modules, thus the TB algorithm converts the dual-armed multi-cluster tool scheduling problem into single-armed multi-cluster tools scheduling problem equivalently. Experimental results indicate that the proposed algorithm is feasible and efficient.

Keywords: scheduling; algorithm; residency constraints; multi-wafer types; semiconductor manufacturing.

DOI: 10.1504/IJMTM.2019.100157

International Journal of Manufacturing Technology and Management, 2019 Vol.33 No.1/2, pp.14 - 36

Received: 23 May 2016
Accepted: 11 May 2017

Published online: 11 Jun 2019 *

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