Modeling and optimization of hard turning of X38CrMoV5-1 steel with CBN tool: Machining parameters effects on flank wear and surface roughness

Abstract

The present study, aims to investigate, under turning conditions of hardened AISI H11 (X38CrMoV5-1), the effects of cutting parameters on flank wear (VB) and surface roughness (Ra) using CBN tool. The machining experiments are conducted based on the response surface methodology (RSM). Combined effects of three cutting parameters, namely cutting speed, feed rate and cutting time on the two performance outputs (i.e. VB and Ra), are explored employing the analysis of variance (ANOVA). Optimal cutting conditions for each performance level are established and the relationship between the variables and the technological parameters is determined using a quadratic regression model. The results show that the flank wear is influenced principally by the cutting time and in the second level by the cutting speed. Also, it is that indicated that the feed rate is the dominant factor affecting workpiece surface roughness.

Experimental investigation of surface roughness, flank wear, chip morphology and cost estimation during machining of hardened AISI 4340 steel with coated carbide insert

“…Additionally, their results highlight the cost estimation based on Gilbert's approach of economics in machining to vindicate the economical viability of coated ceramic tool in hard turning process. Aouici et al (2011a) have applied ANOVA and RSM to examine the effects of machining parameters including cutting speed, feed and machining time for modeling and optimization of surface roughness and flank wear in hard turning of AISI H11 (X38CrMoV5-1) steel with CBN tool. Conclusions showed that flank wear is predominantly controlled by machining time followed by cutting speed, while feed in case of surface roughness.…”

Experimental comparison of PVD, CVD and CERAMIC tool inserts in turning of hardened EN 19/AISI 4140 for optimization of surface roughness and material removal rate

“…In order to find out the effect of tool geometry parameters on the surface roughness during turning, response surface methodology (RSM) was used and a prediction model was developed related to average surface roughness (Ra) using experimental data. The results indicated that the tool nose radius was the dominant factor on the surface roughness Hamdi Aouici, Mohamed Athmane Yallese, Brahim Fnides, Kamel Chaoui and Tarek Mabrouki [14] This paper, aims to investigate, under turning conditions of hardened AISI Hll (X38CrMoV5-l), the effects of cutting parameters on flank wear (VB) and surface roughness (Ra) using CBN tool. The machining experiments are conducted based on the response surface methodology (RSM).…”

“…It is primarily seen that many researchers carried out their studies on various cutting parameters (viz. speed , feed , depth of cut) as their input parameters and concluded that Feed is important parameter [5][6][8] [9][12] [14] for optimizing surface roughness and also some researches made clear that depth of cut [2][3][8] [10] affects the response of surface roughness. Researches were also carried out by studying the effect of input parameters like changing the tool inserts and also by changing nose radius of various inserts [6] [13] .…”

Identification of Optimum Parameters for MRR on Hard Turning of AISI H13 Steel by using TAGUCHI ANALYSIS and ANOVA

“…Hamdi aouici et al (2011), [3] the present study, aims to investigate, under turning conditions of hardened AISI H11 (X38CrMoV5-1), the effects of cutting parameters on flank wear (VB) and surface roughness (Ra) using CBN tool. The machining experiments are conducted based on the response surface methodology (RSM).…”