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A Discrete Cooperative Control Method for Production Scheduling Problem of Assembly Manufacturing System

Xiao Wang, Mei Liu, Peisi Zhong (), Chao Zhang and Dawei Zhang
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Xiao Wang: Department of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao 266590, China
Mei Liu: Advanced Manufacturing Technology Center, Shandong University of Science and Technology, Qingdao 266590, China
Peisi Zhong: Department of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao 266590, China
Chao Zhang: Department of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao 266590, China
Dawei Zhang: Department of Mechanical and Electronic Engineering, Shandong University of Science and Technology, Qingdao 266590, China

Sustainability, 2023, vol. 15, issue 18, 1-23

Abstract: With a sharp decrease in resource utilization of the complex production process, integrated scheduling methods are urgently needed in assembly manufacturing industries. To this end, this paper presents an integrated scheduling with jobs processing and assembly sequence (ISJPAS) problem where jobs and assemblies can be processed simultaneously. As the first contribution to this work, we develop a mixed integer nonlinear programming model (MINLP) that aims at minimizing maximum completion time and determining the earliness and tardiness of jobs and resulting inventory time. The structured property of the optimal scheduling solution is analyzed with regard to job sequencing and assembly sequencing. The NP-hard nature of the problem is proved, which provides upper and lower bounds on the optimal solution. Second, an efficient discrete assembly time and arrival time control (DAATC) method is presented based on continuous time variable control models. From a modified set of benchmark problems, the proposed method is tested by comparing four assembly association levels in real applications. The comparisons indicate the potentiality of our method to satisfy the due date. Lastly, relevance of practical applications are discussed, and several future research avenues are emphasized.

Keywords: assembly manufacturing system; production scheduling; assembly sequence planning; discrete assembly time and arrival time control; computational complexity analysis (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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