To economize cutting process used in component manufacturing number of procedures are used. Typical parameters which are optimized are feed rate, spindle speed, depth of cut, machining time etc. Almost no consideration is given to non-productive machining time, which is an important parameter on modern computer numerical control machine tools. Its importance is further augmented in the area of numerically controlled cutting where surface area to thickness ratio is high. The problem is formulated as a large scale traveling salesman problem (TSP). The stochastic search procedure genetic algorithm is used to solve these instances of TSP. This solution allows the optimization of non-productive movement thus reducing the cycle time and increasing the productivity of the process.
">To economize cutting process used in component manufacturing number of procedures are used. Typical parameters which are optimized are feed rate, spindle speed, depth of cut, machining time etc. Almost no consideration is given to non-productive machining time, which is an important parameter on modern computer numerical control machine tools. Its importance is further augmented in the area of numerically controlled cutting where surface area to thickness ratio is high. The problem is formulated as a large scale traveling salesman problem (TSP). The stochastic search procedure genetic algorithm is used to solve these instances of TSP. This solution allows the optimization of non-productive movement thus reducing the cycle time and increasing the productivity of the process.