Machining scheme selection of digital manufacturing based on genetic algorithm and AHP
The selection of machining scheme for a part is an important and strategic problem. It involves multiple and conflicting objectives such as cost, time, quality, service level, resource utilization, etc. The selection is always affected by subjective factors such as the knowledge and experiences of decision maker in conventional machining. This paper proposes a method based on genetic algorithms (GA) to find out the set of Pareto-optimal solutions for multi-objective digital machining scheme selection. To deal with multi-objective and enable the engineer to make decision on different demands, an analytic hierarchy process (AHP) is implemented in the proposed procedure to determine the weight value of evaluation indexes. Three conflicting objectives: cost, quality and operation time are simultaneously optimized. An application sample is developed and its results are analyzed. The optimization results show that the hybrid algorithm is reliable and robust.
machining scheme genetic algorithm analytic hierarchy process multi-objective optimization