Optimization of machining parameters during end milling of super alloys using grey based taguchi method coupled with entropy measurement technique

High-quality products include those with better surface quality and texture, close dimensional tolerances and form accuracies at precise level, increase fatigue life and burr-free. Burr formation is one of the most common inevitable facts occurring in all material removal processes, reduces assembly and machined part quality. But, burr formation during milling is a more complex mechanism compare to remaining machining burrs and leads to numerous difficulties during the deburring process. To prevent this, one should optimize the combination of cutting parameters during machining itself. In order to build up a link between quality and productivity and to attain the same in the cost-effective way, the present work concentrate on multi objective optimization of CNC end milling process parameters. Multiple performance characteristics with respect to surface quality and performance index like assembly work have been put up, to assess an equivalent single quality index (called grey relational grade) has been optimized finally by Grey based Taguchi method. After that priority weight of individual quality and performance attributes has been estimated by entropy measurement technique on the basis of relative significance and check the feasibility of the proposed technique has been demonstrated in this context.