Parametric Deduction Optimization for Surface Roughness

Abstract

Problem statement: Surface roughness is a major consideration in modern Computer Numerical Control (CNC) turning industry. Most existing optimization researches for CNC finish turning were either accomplished within certain manufacturing circumstances, or achieved through numerous equipment operations. Therefore, a general deduction optimization scheme is deemed to be necessary for the industry. Approach: In this study, four parameters (cutting depth, feed rate, speed, tool nose runoff) with three levels (low, medium, high) were considered to optimize the surface roughness for Computer Numerical Control (CNC) finish turning. Additionally, twenty-seven fuzzy control rules using trapezoid membership function with respective to seventeen linguistic grades for the surface roughness were constructed. Considering thirty input and eighty output intervals, the defuzzification using center of gravity was moreover completed. Through the Taguchi experiment, the optimum general deduction parameters can then be received. Results: The confirmation experiment for optimum deduction parameters was furthermore performed on an ECOCA-3807 CNC lathe. It was shown that the surface roughness from the fuzzy deduction optimization parameters are significantly advanced comparing to those from benchmark. Conclusion: This study not only proposed a parametric deduction optimization scheme using orthogonal array, but also contributed the satisfactory fuzzy approach to the surface roughness for CNC turning with profound insight.