Multi-Objective Optimization of Minimum Quantity Lubrication in end Milling of Aluminum Alloy AA6061T6 - Najiha, M. S.; M. M., Rahman; K., Kadirgama; M. M., Noor; D., Ramasamy (Universiti Malaysia Pahang, 2015)
The purpose of this research is to optimize the process of minimum quantity lubrication (MQL) in the end milling of AA6061T6 using multi-objective genetic algorithm approach. Response surface methodology coupled with a central composite design of experiments is used for modeling. Data is collected from a vertical CNC milling center and the input parameters are cutting speed, table feed rate, axial depth of cut and the minimum quantity lubrication flow rate. Analysis of variance at a 95% confidence level is implemented to identify the most significant input variables on the CNC end milling process. Optimization of the responses is done using a multi-objective genetic algorithm. A multi-criteria decision making utility is used to find among the feasible range of optimum designs for the operating parameters and the responses. An iterative multi-criteria decision making algorithm is used to find the best design among those obtained from multi- objective optimization with respect to the given conditions. The best design obtained for the equal weightage case is the design at 5252 rpm, with a feed rate of 311 mm/min, a depth of cut of 3.47 mm and MQL flow rate at 0.44 ml/min.