Prediction Model for CNC Turning on AISI316 with Single and Multilayered Cutting tool Using Box Behnken Design

Austenitic stainless steel (AISI316) is used for many commercial and industrial applications owing to its high resistance to corrosion. It is too hard to machine due to its high strength and high work hardening property. Tool wear (TW) and surface roughness (SR) are broadly considered as most challenging phases, and thus causing poor results in machining. Optimization of cutting parameter is more essential at this condition for improving the results. The existing method response surface methodology (RSM) incorporating statistics as tool in design and executing experiments is proved as a standard one. In this study of modeling and optimization of a CNC turning process, RSM is adopted as an alternative methodology to replace existing conventional methods; particularly, Box Benken design (BBD) is used to build the model. This methodology not only reduces the cost and time, but also provides adequate information pertaining to the main and interaction effects with a limited attempt of experiments. SR and TW of the coated cutting tool for CNC turning of AISI 316 are taken as responses for analysis. Statistical check proves that this methodology for modeling is sufficient, lack of fit test for model is insignificant, and residual analysis and normal probability plots are also satisfied.