Background: Now-a-days, newer hardened steel materials are coming rapidly into the market due to its wide applications in various fields of engineering. So the machinability investigation of these steel materials is one of the prime concern for practicing engineers, prior to actual machining. Methods: The present study addresses surface roughness, flank wear and chip morphology during dry hard turning of AISI 4340 steel (49 HRC) using CVD (TiN/TiCN/Al₂O₃/TiN) multilayer coated carbide tool. Three factors (cutting speed, feed and depth of cut) and three-level factorial experiment designs with Taguchi’s L₉ Orthogonal array (OA) and statistical analysis of variance (ANOVA) were performed to investigate the consequent effect of these cutting parameters on the tool and workpiece in terms of flank wear and surface roughness. For better understanding of the cutting process, surface topography of machined workpieces, wear mechanisms of worn coated carbide tool and chip morphology of generated chips were observed by scanning electron microscope (SEM). Consequently, multiple regression analysis was adopted to develop mathematical model for each response, along with various diagnostic tests were performed to check the validity and efficacy of the proposed model. Finally, to justify the economical feasibility of coated carbide tool in hard turning application, a cost analysis was performed based on Gilbert’s approach by evaluating the tool life under optimized cutting condition (suggested by response optimization technique). Results: The results shows that surface roughness and flank wear are statistically significant influenced by feed and cutting speed. In fact, increase in cutting speed resulted in better surface finish as well as increase in flank wear. Tool wear describes the gradual failure of cutting tool, caused grooves by abrasion due to rubbing effect of flank land with hard particles in the machined surface and high cutting temperature. Chip morphology confirms the formation of saw-tooth type of chip with severity of chip serration due to cyclic crack propagation caused by plastic deformation. The total machining cost per part is found to be $0.13 (i.e. in Indian rupees Rs. 8.21) for machining of hardened AISI 4340 steel with coated carbide tool. Conclusions: From the study, the effectiveness and potential of multilayer TiN/TiCN/Al₂O₃/TiN coated carbide tool for hard turning process during dry cutting condition possesses high yielding and cost-effective benefit to substitute the traditional cylindrical grinding operation. Apart, it also contributes reasonable option to costlier CBN and ceramic tools.

This article aims to analyze the tool vibration, surface roughness, and chip morphology in hard turning of hot work AISI H13 steel under multi-walled carbon nanotubes mixed nanofluid with minimum quantity lubrication. Recently developed new-generation nanocomposite AlTiSiN coating deposited on carbide insert via scalable pulsed power plasma (S3P) strategy is used as cutting tool material. The experiments associated with 30 number of trials are performed by considering various machining parameters that includes cutting speed, nose radius, depth of cut, and feed. In perspective of predictive modeling and multi-response optimization, response surface methodology has been engaged as a means to minimize the tool vibration and surface roughness. At last, with the measured tool life and based on the Gilbert’s machining economic model, a distinctive cost analysis has been implemented to demonstrate the cost-effectiveness of coated carbide tool in hard turning. Statistical analysis confirms that nose radius with 36.65% has the highest contribution for surface roughness and cutting speed with 53.88% has the highest contribution for tool vibration. Increased flank wear and tool vibration are responsible for degradation of machined surface finish. Machining under nanofluid-MQL, chip morphology revealed the production of segmented type serrated saw-toothed chips. At higher cutting speed resulted: (a) obvious shape of saw tooth chip, (b) increase of distance among saw tooth, (c) reduction in chip segmentation frequency, (d) decrease of chip thickness. At optimum combination of process variables ( v = 55 m/min, d = 0.2 mm, r = 1.2 mm, f = 0.07 mm/rev), the life of AlTiSiN coated carbide tool is found to be 42 min under nanofluid-MQL and estimated the total machining cost expenditure per finished part of Rs. 153.52. New-generation AlTiSiN coated carbide tools can be competently and productively utilized for machining of hot work tool steel under ecologically cognizant minimum quantity cooling-lubrication, is the most accepted in industrial applications.

The search of finding best vegetable oil based nanofluid from a set of three nanoparticle enriched cutting fluids for machining is core objective of the work. Extensive research has been done to replace conventional cutting fluids by nanofluids, but abundant analysis for vegetable oil based nanofluids is accomplished in this work which was not seen earlier. Also, the study investigated the cutting performance and comparative assessment towards machinability improvement during hard turning of high-strength-low-alloy (HSLA) AISI 4340 steel using four different compositions of nanofluids by minimum quantity lubrication (MQL) technique. Cutting are investigated and analyzed through this article during hard turning using minimum quantity lubrication (MQL). Cutting force, tool wear (flank and crater), surface integrity (surface roughness, residual stress, microhardness, and surface morphology), and chip morphology are considered as technological performance characteristics to evaluate the machinability of hardened AISI 4340 steel. Additionally, the effect of various fluid properties like thermal conductivity, viscosity, surface tension and contact angle were examined for all nanofluids. Three set of nanofluid samples were prepared using Al₂O₃, CuO and Fe₂O₃ with rice bran oil and their various properties are analysed at 0.1% concentration. On comparison among these three nanofluids used, CuO nanofluid exhibited superior behavior followed by Fe₂O₃ nanofluids while Al₂O₃ nanofluid was last in the row.