This research focus on to presents of the MQL parameters optimization approach in which the multi-response outputs based on Taguchi's L9 orthogonal array method is used. During the turning AISI-1045 steel, the cutting temperature, the maximum of tool wear, and the surface roughness were measured. The MQL parameters which are ratio of soluble lubricant and water, pressure of spray head, flow volume of emulsion was simultaneously optimized by taking the multi-response outputs using Taguchi based grey relational analysis (GRA) into consideration. In turning experiments, three different flow volume of emulsion Q (40, 60, 80 ml/h), three different levels pressure of spray head P (3, 5, 7 bar) and three different levels ratio of soluble lubricant and water R (4, 6, 8%) were used. Beside, three mathematical models were created using response surface regression methodology. |
