Application of compressed cold air cooling: achieving multiple performance characteristics in end milling process

This paper applies Taguchi's design of experiment methodology and grey relational analysis for multi objective optimization of process parameters and cutting environments during machining operation. In addition to the machining using cutting fluid, this research includes machining with compressed cold air cooling and dry machining. These environment-friendly cutting techniques are considered to be two practical ways to the cleaner manufacturing in the context of the sustainable production since the reduction of environmental harmful impact is an important topic in sustainable production. Experiments were performed based on L18 standard orthogonal array design by five input process parameters, namely cutting speed, feed per tooth, radial depth of cut, cutting time and cutting environment. Cutting environment is considered as machining using cutting fluid, machining with compressed cold air cooling and dry machining. The objective of process parameters optimization is to achieve at the same time the maximum volume of removed material and minimum surface roughness, minimum flank wear and minimum cutting force components. Based on grey relational analysis, the optimal setting of process parameters were identified and analysis of variance indicated that cutting time, feed per tooth and cutting environment are the most influential parameters on machining performances.