Multiple product admission control in semiconductor manufacturing systems with process queue time (PQT) constraints. (September 2016)

• Record Type: Journal Article
• Authors: Wu, Cheng-Hung; Chien, Wen-Chi; Chuang, Ya-Tang; Cheng, Yu-Ching
• Is Part Of: Computers & industrial engineering. Volume 99(2016)
• Page Start: 347
• Page End: 363
• Publication Date: 2016-09
• Subjects: Manufacturing system modeling -- Process time window constraint -- Admission control -- Semiconductor manufacturing -- Resource allocation; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2016.04.003
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: This research develops production control methods for multi-product systems under process queue time (PQT) constraints. A single flexible upstream workstation and multiple dedicated downstream workstations are considered. Under the PQT constraint, jobs are scrapped if the waiting time before a queue is longer than a pre-defined upper limit. An innovative multiple product admission control heuristic is developed using Markov decision processes. The proposed MPAC method reduces production costs and scrap counts by 33.8% and 59.5% in our numerical study. Abstract: In a multi-product manufacture system, the complexity of production control increases. Because multiple products are competing for limited resource, managers need to dynamically adjust production priority based on customer demand and distribution of work-in-processes (WIP). The production control in multi-product system becomes even more complicated when process queue time (PQT) constraints exist. Under PQT constraints, administrators setup upper limits for the waiting time between specific manufacturing steps to ensure quality of products. This upper limit of waiting time makes dynamic production control very challenging. The objective of this paper is to develop production control methods for multi-product systems subject to PQT constraints. However, it is computationally infeasible to solve multiple product problems in a single dynamic optimization model, and we therefore first formulate a single product admission control problems using Markov decision processes (MDP). Based on observations from the single product MDP model, an innovative multiple product admission control (MPAC) heuristic is developed. In simulation study, we compare the performance of MPAC with other popular dispatching methods in literature. Compare to other control methods in literature, the proposed (MPAC) method can reduce production costs by at least 33.8% and reduce scrap count by at least 59.5% in average.