Preprint Article Version 1 This version is not peer-reviewed

Optimization of Face Milling Parameters Considering Wear and Tool Life of Cutters to Improve the Quality, Cost and Power Consumption

Version 1 : Received: 5 December 2018 / Approved: 6 December 2018 / Online: 6 December 2018 (14:09:34 CET)

How to cite: Pimenov, D.Y.; Gupta, M.K.; Erdakov, I.N.; Abbas, A.T.; Soliman, M.S.; El Rayes, M.M. Optimization of Face Milling Parameters Considering Wear and Tool Life of Cutters to Improve the Quality, Cost and Power Consumption. Preprints 2018, 2018120088 Pimenov, D.Y.; Gupta, M.K.; Erdakov, I.N.; Abbas, A.T.; Soliman, M.S.; El Rayes, M.M. Optimization of Face Milling Parameters Considering Wear and Tool Life of Cutters to Improve the Quality, Cost and Power Consumption. Preprints 2018, 2018120088

Abstract

Face milling is a well known commercial process highly used in heavy industries that consumes high amount of power. Besides power issue, modern manufacturing industries are aiming for per part cost reduction keeping the product quality unimpaired. Unexpectedly if the part is rejected in any stage of manufacturing, the cost of manufacturing dramatically increases. Major cause of part rejection is excessive tool wear that imparts poor surface profile or catastrophic tool failure that causes adherence of broken tool debris onto machined surface. Furthermore, the tool wear is associated with sliding distance (frictional distance) and the tool life quantifies the cost of tools. As such, from the perspective of manufacturing industries it is imperative to optimize the surface quality parameter, cost of part, power consumption, and material removal – this is exactly what is accomplished here. By this work, it is possible to conserve power consumption, produce parts with lower cost, manufacture with uncompromising surface quality and enhanced material removal rate. Moreover, as intermediate factors of interest, the influences of sliding distance, tool life and tool flank wear on the overall machining performance are evaluated. The multi-objective optimization by Grey Relational Analysis (GRA) revealed that for improved product performance and fast manufacturing (case 1) optimum results are: feed per tooth fz = 0.25 mm/tooth, cutting speed vc = 392.6 m/min and cutting length l = 0.5 mm; for resource conservation (case 2) the optimum results are: feed per tooth fz = 0.125 mm/tooth, cutting speed vc = 392.6 m/min, cutting length l = 0.5 mm.

Subject Areas

Face milling; Cost saving; Power consumption; Surface quality; Tool wear

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