A framework model of production planning optimization for make-to-order discrete manufacturing

Authors:
Qing Wang;Shu-An Liu;Bin Gao;Dingwei Wang
Affiliations:
Faculty of Information Science and Engineering, Northeastern University, Shenyang, China;Faculty of Information Science and Engineering, Northeastern University, Shenyang, China;Faculty of Information Science and Engineering, Northeastern University, Shenyang, China;Faculty of Information Science and Engineering, Northeastern University, Shenyang, China
Venue:
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Year:
2009

Citing 5
Cited 0

Material management in decentralized supply chains

Operations Research
Minimizing the number of late jobs for the two-machine unit-time job scheduling problem

Discrete Applied Mathematics
Supply Chain Management with APO Structures, Modeling Peculiarities

Supply Chain Management with APO Structures, Modeling Peculiarities
Simple heuristics for scheduling with limited intermediate storage

Computers and Operations Research
Approximation algorithms for scheduling problems with a modified total weighted tardiness objective

Operations Research Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

To keep competitive edge in the global market manufacturing enterprises have to enhance their information systems such as ERP with production planning optimization. In this paper in terms of make-to-order discrete manufacturing a segregate framework model is proposed to support the production planning optimization and to integrate with ERP system. This model aims to sufficiently utilize the production capacities of working centers by dispatching planning objects at a low level. On the basis of the model the major issues in the system implementation are addressed: timing definition and scheduling algorithm. The practical application shows that the proposed model and its implementation system can improve generate effective and productive planning results for the production.