Professor of School of Engineering, Design and Built Environment, Western Sydney University, Australia. His research interests cover Industry 4.0, Additive Manufacturing, Advanced Engineering Materials and Structures (Metals and Composites), Multi-scale Modelling of Materials and Structures, Metal Forming and Metal Surface Treatment.
Abstract—This study highlights optimization of CNC high speed milling process parameters to provide better surface finish as well as high material removal rate. The surface finish and material removal rate have been identified as quality attributes and are assumed to be directly related to productivity. In order to build up a bridge between quality and productivity, and attempt made to optimize aforesaid quality attributes in small and medium size companies involved with heterogenic product demand. This invites a multi-objective optimization problem which has been solved by DOE based genetic algorithm optimization procedure. The response surface method of Box- Benkhen method has been adapted to get multi objective optimization problem. The methodology found to be useful in simultaneous optimization of more number of responses.
Index Terms—CNC milling, Optimization, Surface finish, DOE, ANOVA, Material removal rate, Box-benkhen method, Stainless steel
Cite: V S Thangarasu and R Sivasubramanian, "High Speed CNC Machining of AIsI 304 Stainless Steel; Optimization of Process Parameters," International Journal of Mechanical Engineering and Robotics Research, Vol.1, No.3, pp. 9-21, October 2012.
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