Metaheuristics for optimizing tool path in cnc machining operations

Abstract

The highly flexible CNC machines are used extensively by manufacturing industries for producing a variety of components By minimizing the tool in airtime the machining cycle time can be reduced Also the cost of energy in operating the CNC machines is about one fifth of the total operating cost and this cost is increasing steadily The reduction of the machining cycle time and energy consumption is necessary to achieve higher productivity These objectives are achievable by an intelligent selection of tool path Among the popular computational methods the metaheuristic algorithms are found to provide the best solutions for this NP hard problem In the present research work Particle Swarm Optimization PSO Genetic Algorithm GA and Ant Colony Optimization ACO are used for their ability to generate quality solutions to optimization problems which are having huge search space The selection of parameters for the algorithm was studied for optimum results by selecting a range of values and the results are discussed This work utilizes the application of MATLAB computing environment for its flexibility and simple coding method. newline