Optimal Tool Selection Based on Genetic Algorithm in a Geometric Cutting Simulation.

This paper presents a new method of optimal selection of cutting tools in a geometric cutting simulation. Firstly an area to be cut by an end-milling tool is calculated according to each different tool. The shape of the workpiece is represented in a hierarchical lattice space model, Enhanced Z-map model. Secondly a tool set prepared is coded as a binary bit string, i. e. gene. Each bit corresponds with a certain tool and 1 indicates its use and 0 is not. Thirdly a fundamental Genetic Algorithm consisting of selection, crossover and mutation is applied based on the index which takes account of total cutting time, uncut area, the number of tools used etc. Here it is assumed that the selected tools would be used in descent order of diameter and it would cut its corresponding area as entirely as possible. Some simulations are illustrated and the conclusions are briefly mentioned too.