HEURISTIC BASED PARTS SCHEDULING USING PETRI NET MODELS

Abstract

The present day manufacturing industries consist of complex systems and apply various approaches to make best use of the available resources. In this regard production, planning and control activities play an important role and ensure the effective conversion of raw material into finished goods in such a way that high productivity goals are reached. Scheduling is the most important activity of production control determining the efficient flow of inventory from raw material stage to end product. Even though flexible manufacturing systems and computer integrated manufacturing approaches appear more frequently in many research agendas, scheduling still receives ample attention from both researchers and practitioners, especially dynamic job shop scheduling problems which still exist in most of the advanced manufacturing systems in different forms. In a dynamic job shop environment there will be certain amount of uncertainty about the arrival of new jobs for which application of heuristics are found to be suitable rather than analytical approaches. There is a need to study the performance of different heuristics under different conditions for the dynamic job shop. Further it is found that various approaches have been used for modelling a system for job shop situations but very little work has been carried out to model the systems with Petri nets. The characteristics of Petri nets show that they are well suited to model the dynamics of manufacturing systems. They can concisely represent the activities, resources and constraints of a system in the single coherent formulation.