Bi-objective optimization for scheduling of single-arm cluster tools with activity time variation

• Published in: Expert systems with applications p. 129213
• Main Authors: Zeng, Shan, Wu, NaiQi, Qiao, Yan
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.08.2025
• Subjects: Cluster tool; Metaheuristics; Multi-objective optimization; Scheduling; Semiconductor manufacturing; Cluster tool; Scheduling; Multi-objective optimization; Semiconductor manufacturing; Metaheuristics
• ISSN: 0957-4174
• DOI: 10.1016/j.eswa.2025.129213

Single-arm cluster tools (SACTs) are widely used in wafer manufacturing, where efficient scheduling is crucial for maximizing productivity and minimizing wafer delay time. However, activity time in practical operations is subject to random variations, making it challenging to simultaneously minimize cycle time and total delay time. To address this issue, we propose a two-stage multi-criteria decision framework, named Bi-objective Mandatory Waiting Time Optimization Method (BMWTOM). Firstly, mandatory robot waiting time before wafer loading is set for some steps using the Mandatory Waiting Method (MWM), while the Earliest Starting Strategy (ESS) is applied to the remaining robot tasks. Secondly, several state-of-the-art multi-objective optimization meta-heuristic algorithms are employed to determine the optimal waiting time, generating a Pareto set of non-dominated solutions. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is then used to rank these solutions according to decision-maker preferences and select the ideal schedule. Finally, numerical experiments on industrial SACT scenarios demonstrate that BMWTOM can effectively optimize both productivity and total wafer delay time under activity time variations, outperforming traditional scheduling methods.