The basic management problems in today's manufacturing organizations are integration of strategic and tactical decision making, developing the capability for plans and schedules reconfiguration and synchronization in a very short cycle as well as handling supply, operational and demand exceptions. This is reason why many firms have proceeded to the adoption of modern technological solution such as Enterprise Resource Planning (ERP) and Advanced Planning and Scheduling (APS) technologies. The final goal is a purposeful scheduling system that guide in the right direction the current, high priority needs of the shop floor while remaining consistent with long-term production plans. Simulation's role in such a system is key due to its ability to faithfully replicate the real production ambiance and quickly react on unpredictable exceptions in the field. Its value is further enhanced when this solution is fully integrated with advanced planning function. It is apparent that there is a lack of a comprehensive, scientifically established design methodology to structure, guide, and improve manufacturing process modeling efforts. The approach presented in the paper gives verbal and mathematical problem description, builds ontology of problem domain, uses Extended Petri Nets and event graphs as activity cycle diagrams as modeling tools in order to obtain faithful model which can easily be replicated in object oriented class and object hierarchy. With proposed approach it is possible to focus, comprehensive but static ERP knowledge in dynamic simulation models and to fully utilize prediction power of simulation for effective and integrated strategic and tactical decision making.
[1]
Massimo Pacella,et al.
Object-oriented modeling and simulation of flexible manufacturing systems: a rule-based procedure
,
2002,
Simul. Model. Pract. Theory.
[2]
Stephen F. Smith,et al.
An Ontology for Constructing Scheduling Systems
,
1997
.
[3]
Kostas S. Metaxiotis,et al.
Production scheduling in ERP systems: An AI-based approach to face the gap
,
2003,
Bus. Process. Manag. J..
[4]
Young Nam Kim,et al.
An object oriented production planning system development in ERP environment
,
1998
.
[5]
Reha Uzsoy,et al.
Advanced Planning and Scheduling for Manufacturing
,
2007
.
[6]
Kostas S. Metaxiotis,et al.
Building ontologies for production scheduling systems: towards a unified methodology
,
2001,
Inf. Manag. Comput. Secur..