Laser-assisted machining (LAM) is a new hybrid method and widely used in various difficult to machine materials as it improves the productivity (reduces energy efficiency) and surface quality. In LAM, machining in the workpiece is carried after reaching the preheating temperature using a laser. Among the various difficult-to-cut materials, Inconel 718, nickel-based super alloys, is difficult to machine due high strength at elevated temperature and low thermal conductivity. In the present study, the effect of machining conditions on cutting forces, cutting temperature, stress, has been studied using finite element modeling in laser assisted machining operation of Inconel 718. Three values of cutting speed are taken (50, 75 and 100 m/min). Cutting force, feed force, stress, and cutting temperature is predicted using commercial Abaqus/CAE at different machining conditions in laser heated conditions. With the increase of cutting speed in laser-assisted machining conditions the cutting force and feed force increased. In order to validate the numerical results an experimental analysis is performed and a result in good agreement between them is observed. © 2017 Elsevier Ltd. All rights reserved.

Venkatesan K

Department of Design and Automation

School of Mechanical Engineering

Vellore Campus

Kanubhai J

Raval G.V

Vipulkumar S.H.

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

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.

Fulltext

Procedia Engineering

Laser Assisted Machining of Difficult to Cut Materials: Research Opportunities and Future Directions - A Comprehensive Review

Laser Assisted Machining (LAM) involves machining the workpiece after softening it with laser emitted heat. This paper includes the study of temperature distribution across depth of the workpiece. A finite element model of transient temperature distribution problem is developed. The variation of thermal properties of the Ti-6Al-4V titanium alloy is considered. The Gaussian beam profile of the laser spot is selected for analysis. The effect of various input parameters like spot radius, laser power and scanning speed is studied. The parametric studies showed that the temperature of the workpiece increases with laser power and decreases with increase in spot radius and scanning speed. © 2014 Published by Elsevier Ltd.

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