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

• Published in: CIRP journal of manufacturing science and technology 2017-08, Vol.18, p.152-158
• Main Authors: Rao, K. Venkata, Murthy, P.B.G.S.N., Vidhu, K.P.
• Format: Article
• Language: English
• Subjects: Graph theory and matrix approach (GTMA); Machining performance; Multi response optimization; Tool vibration; Tool wear; Utility value
• ISSN: 1755-5817; 1878-0016
• DOI: 10.1016/j.cirpj.2016.12.001

•Overall machining performance was improved using graph theory and matrix approach (GTMA) and utility concept.•Weights for individual performance characteristics were calculated using User's Preference Rating.•Process parameters were optimized for maximization of machining performance.•Influence of process parameters on overall performance was estimated. 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 0.4mm of nose radius, 170m/min of cutting speed and 0.1358mm/rev of feed rate.