Assignment of weightage to machining characteristics to improve overall performance of machining using GTMA and utility concept

In an automated manufacturing system, performance of machining is an important characteristic that affects the production cost especially in machining processes like milling and boring. Boring is one of critical machining processes, and therefore, it is very difficult to determine overall performance of the process. In the present work, an attempt was made to maximize overall performance of the process in order to reduce reworking and production cost. Three different performance characteristics like surface roughness, tool wear and root mean square of workpiece vibration velocity are considered to determine overall performance for boring of AISI 1040 steel with carbide tool inserts. According to User's Preference Rating, weights for the three performance characteristics are calculated using graph theory and matrix approach (GTMA). Overall performance or utility value of the machining process is calculated using utility concept. A response surface methodology (RSM) is used to optimize the process parameters for maximization of performance of the process. Weights of surface roughness, tool wear and root mean square of workpiece vibration velocity are calculated as 0.489, 0.367 and 0.184 respectively. Optimum process parameters were found to be 0.4 mm of nose radius, 170 m/min of cutting speed and 0.1358 mm/rev of feed rate.