An investigation on integration of aggregate production planning, master production scheduling and short-term production scheduling of batch process operations through a common data model

Citation
Bp. Das et al., An investigation on integration of aggregate production planning, master production scheduling and short-term production scheduling of batch process operations through a common data model, COMPUT CH E, 24(2-7), 2000, pp. 1625-1631
Citations number
14
Categorie Soggetti
Chemical Engineering
Journal title
COMPUTERS & CHEMICAL ENGINEERING
ISSN journal
00981354 → ACNP
Volume
24
Issue
2-7
Year of publication
2000
Pages
1625 - 1631
Database
ISI
SICI code
0098-1354(20000715)24:2-7<1625:AIOIOA>2.0.ZU;2-K
Abstract
A prototype system has been developed by integrating two higher-level hiera rchical production planning application programs (aggregate production plan (APP), master production schedule (MPS)) using a common data model integra tion approach into an existing planning system for short-term scheduling an d supervisory batch management which was originally proposed and developed by Rickard, J. G., Macchietto, S. & Shah, N. (1999). Integrated decision su pport in flexible multipurpose plants. Computers & Chemical Engineering, 23 , S539-S542. The hierarchical production planning system has been modelled and validated around an industrial scenario concerning multi-site, multipur pose batch process operations making household chemicals from start to tran sportation to regional warehouses. This preliminary work suggests that the idea of integrating software applications through a common data model, whic h was originally described by Stanley, G. M. (1994). The emerging trend tow ards knowledge-based frameworks for computer-integrated manufacturing. Adva nces in Instrumentation & Control, 49, 1121-1133 and further developed by R ickard, J. G., Macchietto, S. & Shah, N. (1999). Integrated decision suppor t in flexible multipurpose plants. Computers & Chemical Engineering, 23, S5 39-S542 is feasible. However further research work, improvements and valida tions are required using varieties of industrial batch process operations a nd distribution problems to prove its viability. (C) 2000 Elsevier Science Ltd. All rights reserved.