This paper discusses the effect of laser-assisted process parameters on cutting forces and surface temperature during laser assisted machining (LAM) of Inconel 718. The heat source used for pre-heating the surface is Nd:YAG laser source. Cutting speed, feed rate and laser power are the process parameter assessor for cutting force and cutting temperature. The experiments are planned and results are collected based on Taguchi's L27 orthogonal design. The factor effect on output responses are analysed using a main effect plots (2D) and its significance is perceived from analysis of variance (ANOVA). Results reveal that cutting speed bags a maximum contribution of 56%, followed by cutting speed feed rate as 24%, feed rate laser power as 10.5% and feed rate as 10%. Finally, the benefit of LAM was shown by 55% decrease in feed force (Fx), 50% decrease in thrust force (Fy) and 60% decrease in cutting force (Fz), as compared to those of the conventional machining. Additionally, it is also recommended to employ a work surface temperature in the range of 750°C-887°C during LAM of this Inconel 718 alloy to have maximum process benefits. The developed regression model reveals the goodness of fit with experimental data has high determination coefficient i.e. R2 = 0.91 for tangential force and 0.71 for surface temperature. © 2017 Elsevier Ltd.

Venkatesan K

Department of Design and Automation

School of Mechanical Engineering

Vellore Campus

Kalyan P

Kumar P

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

Materials Today: Proceedings

Laser assisted machining (LAM) is one of the innovative methods to machine difficult to cut materials to obtain maximum benefits of machinability. In this method, the influence of both the laser and cutting parameters affects the quality of machining. Hence it is required to identify the optimal levels of the parameters in order to maximize benefits. The present study focused on optimization of laser beam approach angle, laser power and cutting parameters during LAM of Inconel 718 alloy using chemical vapour deposition (CVD) coated carbide tool. The experimental trials are planned in accordance with central composite design (CCD) in response surface methodology. The ranges for selected parameters are as follows as: cutting speed (50 &lt; Vc &lt; 100 m/min), feed rate (0.05 &lt; f &lt; 0.1 mm/rev), laser power (1.25 &lt; PL &lt; 1.75 kW), and approach angle (60° &lt; θ &lt; 90°). Cutting force and workpiece temperature, the two responses which are measured using Kistler force dynamometer and infra-red pyrometer respectively. The effects of each parameter were analysed using 3D surface plot and analysis of variance (ANOVA). A second order regression equation has been developed and model shows good agreement with experimental and predicted results. Desirability function analysis (DFA) is used to determine the optimal operating conditions. Finally, the results were validated using confirmation experiments. © 2016 Elsevier Ltd.

Measurement

Statistical approach for optimization of influencing parameters in laser assisted machining (LAM) of Inconel alloy

This paper presents a parametric effect, microstructure, micro-hardness and optimization of laser scanning parameters (LSP) on heating experiments during laser assisted machining of Inconel 718 alloy. The laser source used for experiments is a continuous wave Nd:YAG laser with maximum power of 2 kW. The experimental parameters in the present study are cutting speed in the range of 50-100 m/min, feed rate of 0.05-0.1 mm/rev, laser power of 1.25-1.75 kW and approach angle of 60-90°of laser beam axis to tool. The plan of experiments are based on central composite rotatable design L31 (43) orthogonal array. The surface temperature is measured via on-line measurement using infrared pyrometer. Parametric significance on surface temperature is analysed using response surface methodology (RSM), analysis of variance (ANOVA) and 3D surface graphs. The structural change of the material surface is observed using optical microscope and quantitative measurement of heat affected depth that are analysed by Vicker's hardness test. The results indicate that the laser power and approach angle are the most significant parameters to affect the surface temperature. The optimum ranges of laser power and approach angle was identified as 1.25-1.5 kW and 60-65° using overlaid contour plot. The developed second order regression model is found to be in good agreement with experimental values with R2 values of 0.96 and 0.94 respectively for surface temperature and heat affected depth. © 2015 Elsevier Ltd.

Optics & Laser Technology

Parametric modeling and optimization of laser scanning parameters during laser assisted machining of Inconel 718

Hybrid machining is an emerging technique for difficult-to-cut materials to overcome the problems associated with conventional machining (CM). Inconel 718, a super alloy of nickel, is a high-temperature alloy commonly used in aircraft and thermal industries and categorized as one among the difficult-to-cut materials. In this study, the influence of cutting conditions of Inconel 718 alloy during laser-assisted hybrid machining (LAHM) is investigated and the results are compared with CM. During LAHM, the process parameters of cutting speed, feed rate, approach angle, and laser power are varied. The present work is carried out in two phases: (i) determination of effective heat-affected depth (HAD) during laser preheating (using central composite design (CCD) in response surface methodology); (ii) optimization of cutting conditions during machining (using Taguchi's method). Compared with CM, the LAHM shows the following reduction benefits: (i) 33% in feed force (Fx), 42% in thrust force (Fy), and 28% in cutting force; (ii) improved surface finish (surface roughness, Ra) of 28%; and (iii) reduction in tool wear by 50%. The chip morphology reveals the decrease in shear angle and increase in chip thickness during LAHM. No change in the hardness value of the machined surface after LAHM indicates the absence of subsurface damage. © 2016, Copyright © Taylor & Francis Group, LLC.

Materials and Manufacturing Processes

Improvement of Machinability using Laser-Aided Hybrid Machining for Inconel 718 Alloy

High strength alloys such as nickel and titanium and advanced engineering materials such as ceramics, composites are being developed and widely used in aerospace, automotive, medical and nuclear industries due its inherent physical-mechanical properties. However conversion these new materials into engineering products are always associated with machining. The machinability characteristics such as higher cutting force, higher cutting temperature, poor surface integrity and shorter tool life associated with these materials posing many challenges to the researchers, and hence considered as difficult to cut materials. Conventional methods of machining these materials are found to be uneconomical. In recent days, many attempts have been made to improve the machinability of these materials more effectively via use of external energy assisted machining. Among the various external energy assisted machining methods, laser assisted machining (LAM) has received the attention of researchers in the metal cutting domain and a few research was carried during the recent years. This paper is aimed to review and summarize the potential use of LAM for difficult to cut materials, current progress, benefits and challenges in laser assisted machining. In addition an optimization frame work to study the effect of laser parameters and machining process parameters on machinability performance is not reported which is applicable to industrial processes It is concluded that further experimental modeling and empirical techniques are required to create a predictive based models that gives good agreement with reliable experiments, while explaining the effects of many parameters, for machining of these difficult-to-cut materials. © 2014 Published by Elsevier Ltd.

Journal	Data powered by TypesetMaterials Today: Proceedings
Publisher	Data powered by TypesetElsevier BV
ISSN	2214-7853
Open Access	No