TY - JOUR
T1 - Configuring a seru production system to match supply with volatile demand
AU - Zhan, Rongxin
AU - Li, Dongni
AU - Ma, Tao
AU - Cui, Zihua
AU - Du, Shaofeng
AU - Yin, Yong
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2023/5
Y1 - 2023/5
N2 - In recent years, volatile markets have given rise to a new production system, seru production system, which has been widely utilized in the Asian electronics industry and considered as the next generation of lean production. This paper focuses on the configuration of a seru production system considering that (1) serus are physically reconfigurable rather than fixed and (2) workers have different skill ranges and processing velocities. A mathematical model, whose objectives are to minimize the total completion time and to minimize the total labor cost, is constructed. An improved multiobjective algorithm that combines a multiobjective genetic algorithm, differential evolutionary algorithm and conflict-factor-based mutation operator is proposed in this paper. Computational experiments show that our proposed algorithm outperforms classic scheduling heuristics and well-known algorithms.
AB - In recent years, volatile markets have given rise to a new production system, seru production system, which has been widely utilized in the Asian electronics industry and considered as the next generation of lean production. This paper focuses on the configuration of a seru production system considering that (1) serus are physically reconfigurable rather than fixed and (2) workers have different skill ranges and processing velocities. A mathematical model, whose objectives are to minimize the total completion time and to minimize the total labor cost, is constructed. An improved multiobjective algorithm that combines a multiobjective genetic algorithm, differential evolutionary algorithm and conflict-factor-based mutation operator is proposed in this paper. Computational experiments show that our proposed algorithm outperforms classic scheduling heuristics and well-known algorithms.
KW - Differential evolution
KW - Multiobjective
KW - Reconfigurable manufacturing systems
KW - Resource conflict
KW - Seru production system
UR - http://www.scopus.com/inward/record.url?scp=85139712695&partnerID=8YFLogxK
U2 - 10.1007/s10489-022-04097-9
DO - 10.1007/s10489-022-04097-9
M3 - Article
AN - SCOPUS:85139712695
SN - 0924-669X
VL - 53
SP - 12925
EP - 12936
JO - Applied Intelligence
JF - Applied Intelligence
IS - 10
ER -