Multi-objective optimization of mqlc turning process parameters using grey-fuzzy approach
In this paper the influence of different machining parameters on the surface roughness, cutting force and material removal rate during turning process using MQLC (minimum quantity lubrication and cooling) system was investigated. The experimental plan was defined using Taguchi’s method. Orthogonal array L9 (34) was selected for four input parameters varied on three levels. Parameters that were varied in experiments are: cutting speed (vc), depth of cut (ap), feed rate (f) as well as workpiece steel material. The grey relational analysis in combination with fuzzy logic technique was used to find out the input parameters levels that lead to optimal process responses values.
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