Implementation of an automated operation planning and optimum operation sequencing and tool selection algorithms

Low volume and high product mix characterize a job shop manufacturing. The CAM software in generating NC programs needs to reduce dependence on human judgment in operation planning in order to be used in low repetitive and high product mix production environments. In this research, a procedure for extracting machining methods for automated operation planning is proposed. Furthermore, an optimum operation sequencing and tool selection algorithm is developed for a CAM system. Practical examples have been provided and comparisons made with a known algorithm. Results indicate that the algorithms proposed in this research establish automated operation planning with reduced dependence on human judgment. They achieved considerable flexibility and adaptability, allowing users to implement particular manufacturing knowledge of both their own and resources available at individual shop sites.