Design optimization of cutting parameters for turning of AISI 304 austenitic stainless steel using Taguchi method
2013•nopr.niscpr.res.in
In the present work Taguchi method is used to optimize cutting parameters during dry
turning of AISI 304 austenitic stainless steel with AlTiCrN coated tool. The coating was
deposited on fine-grained K-grade (ISO K-20) cemented carbide cutting insert using
physical vapor deposition (PVD) technique. The turning parameters evaluated are cutting
speed of 200 and 260 m/min, feed rate of 0.20 and 0.26 mm/rev, coating thickness of 3.6 µm
and 4.6 µm each at two levels. The analysis of results shows that the optimal combination of …
turning of AISI 304 austenitic stainless steel with AlTiCrN coated tool. The coating was
deposited on fine-grained K-grade (ISO K-20) cemented carbide cutting insert using
physical vapor deposition (PVD) technique. The turning parameters evaluated are cutting
speed of 200 and 260 m/min, feed rate of 0.20 and 0.26 mm/rev, coating thickness of 3.6 µm
and 4.6 µm each at two levels. The analysis of results shows that the optimal combination of …
In the present work Taguchi method is used to optimize cutting parameters during dry turning of AISI 304 austenitic stainless steel with AlTiCrN coated tool. The coating was deposited on fine-grained K-grade (ISO K-20) cemented carbide cutting insert using physical vapor deposition (PVD) technique. The turning parameters evaluated are cutting speed of 200 and 260 m/min, feed rate of 0.20 and 0.26 mm/rev, coating thickness of 3.6 µm and 4.6 µm each at two levels. The analysis of results shows that the optimal combination of process parameters is obtained at 260 m/min cutting speed, 0.20 mm/rev feed and 4.6 µm coating thickness for minimum cutting force. It is observed that cutting speed plays an important role in minimization of cutting force and coating thickness plays an important role in minimizing average flank wear (VB). A multiple linear regression models are developed for cutting force and average flank wear. The correlation coefficient is found to be more than 0.95, which shows that the developed model is reliable and could be used effectively for predicting the cutting force and average flank wear for the given tool and work material pair and within the domain of the cutting parameters.
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