Integrated Approach for Flexible Mixed Model Assembly Lines Balancing and Model Sequencing Problem

Abstract

The manufacturers nowadays are forced to respond very quickly to changes in the market conditions. To adopt flexible mixed model assembly lines (MMAL) is a preferred way for manufacturers to improve competitiveness. Managing a mixed model assembly line involves two problems: assigning assembly tasks to stations (balancing problem) and determining the sequence of products at each station (sequencing problem). In order to solve both balancing and sequencing problem in MMAL simultaneously, an integrated mathematical model based on mixed integer programming (MIP) is developed to describe the problem. In the model, general type precedence relations and task duplications are considered. Due to the NP-hardness of the balancing and sequencing problem of MMAL, GA is designed to search the optimal solution. The efficiency of the GA is demonstrated by a case study.

A Mathematical Model for an Integrated Assembly Line Regarding Learning and Fatigue Effects

“…Kucukkoc and Zhang 29 considered balancing and sequencing problems simultaneously in a mixed-model parallel two-sided assembly line and presented an ant colony optimization algorithm to solve the proposed problem. Nie et al 30 developed an integrated approach for flexible mixed-model assembly lines in which both balancing and sequencing problems are regarded with respect to the precedence relations and task duplications. Maurizio Faccio et al 31 employed a supplementary flexible workforce as a balancing and sequencing hierarchical approach to deal with paced mixed-model assembly lines.…”

“…Furthermore, the Japanese mechanism is regarded to handle the overloads at the stations, while to the best of authors' knowledge, no research on this issue has been published before. Mamun et al 7 Ramezanian and Ezzatpanah 10 Zheng-mei Jie et al 11 Zahiri et al 10 Masoud Rabbani et al 8 Yılmaz Delice et al 13 Zixiang Li et al 14 Zeynel Abidin Cil et al 9 Li et al 16 Scholl et al 20 Xiaobo and Ohno 22 Sarker and Pan 21 Chutima and Naruemitwong 4 Lee 23 Salehi et al 24 Torres et al 25 Rauf et al 24 Zhan and Zhang 26 Kucukkoc and Zhang 27 Jietao Dong et al 3 Li Nie et al 28 Manavizadeh et al 30 Maurizio Faccio et al 29…”