TY - GEN
T1 - Scheduling for semiconductor assembly and test manufacturing enterprise
AU - Hu, Yaoguang
AU - Ke, Jiawei
AU - Yan, Jiawei
AU - Wen, Jingqian
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/11/20
Y1 - 2015/11/20
N2 - Semiconductor assembly and test manufacturing enterprise belong to the model of multi-specification and small-batch. It's a great challenge to make a production planning under uncertainty product categories and batches. Furthermore, product delivery time is very strict in the enterprise. Consequently, it's a key issue to develop a reasonable production planning to ensure the timely completion of the production tasks in the actual production environment. With the analysis of the production process, burn-in process is the common process from different production lines. Burn-in process has several different devices for the burn-in of different products. This paper focuses on the key process batch scheduling problem. The problem is formulated into Integer Linear Programming (ILP), considering the constraints of devices, production capacity and delivery time. The optimization goal of the model is to minimize the production time. Firstly, heuristics is used to solve the order batching and the batch sorting. And then the adaptable genetic algorithm is put forward to solve the ILP. The proposed method is demonstrated by an experimental case within acceptable computational time. Result analysis verifies the validity of the algorithm and implements production planning optimization.
AB - Semiconductor assembly and test manufacturing enterprise belong to the model of multi-specification and small-batch. It's a great challenge to make a production planning under uncertainty product categories and batches. Furthermore, product delivery time is very strict in the enterprise. Consequently, it's a key issue to develop a reasonable production planning to ensure the timely completion of the production tasks in the actual production environment. With the analysis of the production process, burn-in process is the common process from different production lines. Burn-in process has several different devices for the burn-in of different products. This paper focuses on the key process batch scheduling problem. The problem is formulated into Integer Linear Programming (ILP), considering the constraints of devices, production capacity and delivery time. The optimization goal of the model is to minimize the production time. Firstly, heuristics is used to solve the order batching and the batch sorting. And then the adaptable genetic algorithm is put forward to solve the ILP. The proposed method is demonstrated by an experimental case within acceptable computational time. Result analysis verifies the validity of the algorithm and implements production planning optimization.
KW - genetic algorithm
KW - multi-specification and small-batch
KW - production scheduling
KW - semiconductor assembly and test manufacturing
UR - http://www.scopus.com/inward/record.url?scp=84960878505&partnerID=8YFLogxK
U2 - 10.1109/ICIEA.2015.7334236
DO - 10.1109/ICIEA.2015.7334236
M3 - Conference contribution
AN - SCOPUS:84960878505
T3 - Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
SP - 891
EP - 896
BT - Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015
Y2 - 15 June 2015 through 17 June 2015
ER -