A soft computing based approach to integrated process planning and scheduling with setup and machine capacity considerations

Rapidly developing technology turned the manufacturing environments into a more and more flexible, computerized world of ?complex products and requirements?. In such an environment, using the traditional practice of sequential process planning and scheduling remains insufficient and generates problems. In order to overcome this situation, integrated process planning & scheduling has posed a great challenge to researchers.The study presents a literature survey on integrated process planning and scheduling (IPPS) and investigates a new approach which makes use of Baykasoglu?s grammatical representation of generic process plans and Clonal Selection Algorithm (CLONALG) in order to integrate process planning and job shop scheduling. In the proposed integration approach, Giffler & Thompson Algorithm (used to generate active schedules) and VIKOR Method (used to handle multiple objectives) are employed considering setup times and machine capacity constraints.A computer program in C# programming language is developed for finding optimal or near-optimal schedules for IPPS problems. Proposed approach is also applied to case studies in order to analyze its performance.