Abstract

Computer aided process planning (CAPP) is an important interface between computer aided design (CAD) and computer aided manufacturing (CAM) in computer integrated manufacturing (CIM). Operation sequencing in process planning is concerned with the selection of machining operations in steps that can produce each form feature of the part by satisfying relevant technological constraints specified in the part drawing. A single sequence of operations may not be the best for all the situations in a changing production environment with multiple objectives such as minimizing number of set-ups, maximizing machine utilization and minimizing number of tool changes. This paper demonstrates the application of genetic algorithms as a global search technique for a quick identification of optimal or near optimal operation sequences in a dynamic planning environment. A novel initialization scheme for representing the genetic code and a new crossover operator are designed to retain the local operation precedence for each form feature. Since sequences can be obtained quickly, this approach can actually be used by the process planner to generate alternative feasible sequences for the prevailing operating environment.

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