Experimentation on Tool Wear and Surface Roughness in AISI D2 Steel Turning with WC Insert

Abstract

The Taguchi method, based on an orthogonal arrangement (L 9 , 3 3 ), the variance analysis, the signal-to-noise ratios and the response surface methodology have been used to optimize maximum flank wear (VB max ) and surface roughness (Ra) of the cutting tool when turning a hardened steel AISI D2 (65 HRC) with PVD-TiAlN coated WC insert upon dry environment. By employing regression models; cutting speed, cutting depth and feed rate, which optimize maximum flank wear and surface roughness were validated. Results of relation signal-to-noise ratios, showed that with cutting speed of 200 m/min, cutting depth of 0.2 mm and feed rate of 0.20 mm/rev, Ra is optimized. With cutting speed of 150 m/min, cutting depth of 0.4 mm and feed rate of 0.3 mm/rev, VB max is optimized. Through the variance analysis it was concluded that the depth of cut was the main parameter that affected on the surface roughness; whereas, the feed rate was the most influential parameter on the flank wear. Confirmation test results showed that the Taguchi method was very successful in the optimization of machining parameters for minimum surface roughness and flank wear in the turning of the D2 steel.

Parametric Optimization and Modeling for Flank Wear of Tisin-Tialn Nanolaminate Cutting Insert

“…It was seen that as the cutting speed and depth of cut increases, flank wear increases. This concurs with the studies of Gabriel & Milton [37], Dureja et al [38], Lopez-Luiz et al [39], Das et al [40], Singh & Kumar [41], Rajesh Kumar Bhushan [42], Varaprasad et al [43], Suresh et al [44], and Tian-Syung Lan [45], the increment in cutting speed remarkably increases temperature at the interaction of tool tip and work piece and leads to more flank wear.…”

“…ANOVA in Table 4 also confirms that the depth of cut and cutting speed during hard turning greatly influenced the cutting tool flank wear by their contribution i.e 73.38% and 15.77%. This kind of trend was observed in the previous works of López-Luiz et al [39], Singh & Kumar [41], Rajesh Kumar Bhushan [42], Varaprasad et al [43], Nilrudra Mandal et al [46], and Meenu Sahu & Komesh Sahu [47].…”