Strategy for optimising cutting parameters in the dry turning of 6061-T6 aluminium alloy based on design of experiments and the generalised pattern search algorithm

Abstract

This paper proposes a strategy for optimising cutting parameters in the dry turning process to improve surface roughness and machining time and minimise machining cost. Based on this strategy, average surface roughness is expressed using design of experiments and regression analysis in terms of the investigated process parameters: cutting speed, feed rate and depth of cut. Machining time is expressed analytically as a function of cutting speed and feed rate. Machining cost per unit is then derived and minimised subject to the relevant set of constraints using the generalised pattern search (GPS) algorithm. The proposed strategy is presented through a case study using the widely used aluminium alloy 6061-T6. An optimal solution was achieved at values for cutting speed, feed rate and depth of cut of 142.8 m/min, 0.05 mm/rev and 0.05 mm, respectively, corresponding to a machining cost of 0.211 $/unit. Results obtained showed that the optimal solution was efficiently reached by the GPS algorithm.