Modeling process planning problems in an optimization perspective

Abstract

A problem in traditional computer-aided process planning (CAPP) is that the multiple planning tasks are treated in a linear manner. This leads to an over-constrained overall solution space and the final solution is normally far from optimal or even non-feasible. This paper presents a novel CAPP model for machined parts in a job shop environment that contains customer-specified machine tools and cutters. The approach models process planning problems in a concurrent manner to generate the entire solution space by considering the multiple planning tasks, i.e., operations (machine, tool, and tool approach direction) selection and operations sequencing simultaneously. Precedence relationships among all the operations required for a given part are used as the constraints for the solution space. The relationship between an actual sequence and the feasibility of applying an operation is also considered. An algorithm based on simulated annealing (SA) has been developed to find the optimal solution. It is expected that such a planning tool can be used in different job shops for optimal process plan generation.