Abstract

The manufacturing of the components through the machining process considering the higher production rate and desired quality is always a matter of concern for the industrial field. Also, achieving this with a green machining process using near-dry cooling strategies such as minimum quantity lubrication (MQL), cryogenic cooling etc. is a challenging task. In this work, an attempt has been made to implement the MQL for the machining of the aluminium alloy Al-6061 workpiece. The outputs such as temperature and surface roughness have been focused under the controlled machining environment. As there are two output responses, a multi-response optimization technique system desirability functional analysis (DFA) has been exploited. The experimental array was created using the Taguchi approach. A total of eighteen try-outs were executed and the best setting achieved in terms of the input factor levels is CFR = 150 ml/hr, Speed = 1000 rpm, 175 ml/hr, feed of tool = 60 mm/min and cutting depth = 0.2 mm. The values of temperature and surface roughness are noted at optimal settings as 60 °C and 0.32 µm respectively with an enlargement of 2.67 % in the multi-response factor.

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