An integrated job shop scheduling and assembly sequence planning approach for discrete manufacturing. (October 2021)

• Record Type: Journal Article
• Authors: Wang, Zi-Yue; Lu, Cong
• Is Part Of: Journal of manufacturing systems. Volume 61(2021)
• Page Start: 27
• Page End: 44
• Publication Date: 2021-10
• Subjects: Job shop scheduling -- Assembly sequence planning -- Discrete manufacturing -- Optimization; Manufacturing processes -- Periodicals; Production engineering -- Data processing -- Periodicals; Robots, Industrial -- Periodicals; Production, Technique de la -- Informatique -- Périodiques; Robots industriels -- Périodiques; Electronic journals; 670.42
• DOI: 10.1016/j.jmsy.2021.08.003
• Languages: English
• ISSNs: 0278-6125

Abstract

Highlights: Job shop schedule and assembly sequence plan have interaction effects in discrete manufacturing. An approach is proposed to optimize part processing sequence and assembly sequence simultaneously. A NSGA-Ⅱ with a hybrid chromosome coding mechanism is applied. Proposed approach can save total production completion time and total inventory time effectively. Proposed approach becomes more superior when the scale of the problem increases. Abstract: This paper proposes an integrated job shop scheduling and assembly sequence planning (IJSSASP) approach for discrete manufacturing, enabling the part processing sequence and assembly sequence to be optimized simultaneously. The optimization objectives are to minimize the total production completion time and the total inventory time of parts during production. The interaction effects between the job shop schedule and the assembly sequence plan in discrete manufacturing are analyzed, and the mathematical models including the objective functions and the constraints are established for IJSSASP. Based on the above, a non-dominated sorting genetic algorithm-II (NSGA-Ⅱ) with a hybrid chromosome coding mechanism is applied to solve the IJSSASP problem. Through the case studies and comparison tests for different scale problems, the proposed IJSSASP approach is verified to be able to improve the production efficiency and save the manufacturing cost of the discrete manufacturing enterprise more effectively.