TY - GEN
T1 - Multi-Batch Production Scheduling for Distributed Serial Lines with Unreliable Machines and Finite Buffers
AU - Huang, Longzhu
AU - Jia, Zhiyang
AU - Wang, Xiaohan
AU - Chen, Jingchuan
N1 - Publisher Copyright:
© 2021 Technical Committee on Control Theory, Chinese Association of Automation.
PY - 2021/7/26
Y1 - 2021/7/26
N2 - In the modern manufacturing environment, the production systems develop towards a flexible direction due to the market demands of multiple varieties and small batch-based customized products. To make better use of the existing resources and to improve production efficiency, distributed manufacturing mode begins to appear. This paper concentrates on a multi-type production scheduling problem for distributed serial lines. Specifically, unreliable machines and finite buffers are considered, which are more realistic in the practical production. The mathematical model for the production system with two Bernoulli machines is formulated first. Then, under the hypothetical model mentioned above, the main work of this article is to propose the exact and approximate analyses to calculate the performance indicators. Based on the analysis of the model, the genetic algorithm is applied to optimize the maximum completion time on the distributed serial lines for multi-batch-based production tasks. Finally, the feasibility and effectiveness of the mathematical model and the proposed algorithm are verified through numerical experiments.
AB - In the modern manufacturing environment, the production systems develop towards a flexible direction due to the market demands of multiple varieties and small batch-based customized products. To make better use of the existing resources and to improve production efficiency, distributed manufacturing mode begins to appear. This paper concentrates on a multi-type production scheduling problem for distributed serial lines. Specifically, unreliable machines and finite buffers are considered, which are more realistic in the practical production. The mathematical model for the production system with two Bernoulli machines is formulated first. Then, under the hypothetical model mentioned above, the main work of this article is to propose the exact and approximate analyses to calculate the performance indicators. Based on the analysis of the model, the genetic algorithm is applied to optimize the maximum completion time on the distributed serial lines for multi-batch-based production tasks. Finally, the feasibility and effectiveness of the mathematical model and the proposed algorithm are verified through numerical experiments.
KW - Bernoulli machine
KW - Intelligent manufacturing
KW - Production scheduling
KW - Transient analysis
UR - https://www.scopus.com/pages/publications/85117289121
U2 - 10.23919/CCC52363.2021.9550700
DO - 10.23919/CCC52363.2021.9550700
M3 - Conference contribution
AN - SCOPUS:85117289121
T3 - Chinese Control Conference, CCC
SP - 6436
EP - 6441
BT - Proceedings of the 40th Chinese Control Conference, CCC 2021
A2 - Peng, Chen
A2 - Sun, Jian
PB - IEEE Computer Society
T2 - 40th Chinese Control Conference, CCC 2021
Y2 - 26 July 2021 through 28 July 2021
ER -