Integration of Process Planning and Scheduling of a Manufacturing Systems using Petri nets and Genetic Algorithm

This paper presents a new approach towards the integration of process planning and scheduling functions in the manufacturing systems using Petri nets and genetic Algorithm. The modelling and cost estimation technique is based on a new Petri net model: the PP-net (Process Planning net) which represents manufacturing knowledge in the form of precedence constraints and incorporates the cost of machining operations in each operation transition. Using this model as the base, the process plan for the part is developed taking into account the manufacturing costs caused by the machine, setup and tool changing in addition to the pure operation cost. The method proceeds in the cost calculation by attaching a specific data structure to each PP-net transition which describes the associated machine, setup and the tool for the operation modelled by the transition. After the model is created, it is analyzed for the cost and the minimum time of processing of the part. Scheduling is done using Genetic Algorithms to find the minimum tardiness as the objective on three parts which use the same machines and setups.