Laser beam machining (LBM) is one of the most widely used thermal energy based non-contact type advance machining process which can be applied for almost whole range of materials. Laser beam is focussed for melting and vaporizing the unwanted material from the parent material. It is suitable for geometrically complex profile cutting and making miniature holes in sheetmetal. Among various type of lasers used for machining in industries, CO2 and Nd:YAG lasers are most established. In recent years, researchers have explored a number of ways to improve the LBM process performance by analysing the different factors that affect the quality characteristics. The experimental and theoretical studies show that process performance can be improved considerably by proper selection of laser parameters, material parameters and operating parameters. This paper reviews the research work carried out so far in the area of LBM of different materials and shapes. It reports about the experimental and theoretical studies of LBM to improve the process performance. Several modelling and optimization techniques for the determination of optimum laser beam cutting condition have been critically examined. The last part of this paper discusses the LBM developments and outlines the trend for future research.

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Laser beam machining—A review

The CO(2) laser cutting of three polymeric materials namely polypropylene (PP), polycarbonate (PC) and polymethyl methacrylate (PMMA) is investigated with the aim of evaluating the effect of the main input laser cutting parameters (laser power, cutting speed and compressed air pressure) on laser cutting quality of the different polymers and developing model equations relating input process parameters with the output. The output quality characteristics examined were heat affected zone (HAZ), surface roughness and dimensional accuracy. Twelve sets of tests were carried out for each of the polymer based on the central composite design. Predictive models have been developed by response surface methodology (RSM). First-order response models for HAZ and surface roughness were presented and their adequacy was tested by analysis of variance (ANOVA). It was found that the response is well modeled by a linear function of the input parameters. Response surface contours of HAZ and surface roughness were generated. Mathematical model equations have been presented that estimate HAZ and surface roughness for various input laser cutting parameters. Dimensional accuracies of laser cutting on polymers were examined by dimensional deviation of the actual value from the nominal value. From the analysis, it has been observed that PMMA has less HAZ, followed by PC and PP. For surface roughness, PMMA has better cut edge surface quality than PP and PC. The response models developed can be used for practical purposes by the manufacturing industry. However, all three polymeric materials showed similar diameter errors tendency in spite of different material properties. (C) 2009 Elsevier Ltd. All rights reserved.

Laser cutting of polymeric materials: An experimental investigation

This paper presents an effective approach for the optimization of laser cutting process of St-37 steel with multiple performance characteristics based on the grey relational analysis. Sixteen experimental runs based on the Taguchi method of orthogonal arrays were performed to determine the best factor level condition. The response table and response graph for each level of the machining parameters were obtained from the grey relational grade. In this study, the laser cutting parameters such as laser power and cutting speed are optimized with consideration of multiple-performance characteristics, such as workpiece surface roughness, top kerf width and width of heat affected zone (HAZ). By analyzing the grey relational grade, it is observed that the laser power has more effect on responses rather than cutting speed. It is clearly shown that the above performance characteristics in laser cutting process can be improved effectively through this approach.

Use of the grey relational analysis to determine optimum laser cutting parameters with multi-performance characteristics

Experimental study of Nd:YAG laser beam machining—An overview

This article focuses on modeling and optimizing process parameters in pulsed laser micromachining. Use of continuous wave or pulsed lasers to perform micromachining of 3-D geometrical features on difficult-to-cut metals is a feasible option due the advantages offered such as tool-free and high precision material removal over conventional machining processes. Despite these advantages, pulsed laser micromachining is complex, highly dependent upon material absorption reflectivity, and ablation characteristics. Selection of process operational parameters is highly critical for successful laser micromachining. A set of designed experiments is carried out in a pulsed Nd:YAG laser system using AISI H13 hardened tool steel as work material. Several T-shaped deep features with straight and tapered walls have been machining as representative mold cavities on the hardened tool steel. The relation between process parameters and quality characteristics has been modeled with artificial neural networks (ANN). Predictions with ANNs have been compared with experimental work. Multiobjective particle swarm optimization (PSO) of process parameters for minimum surface roughness and minimum volume error is carried out. This result shows that proposed models and swarm optimization approach are suitable to identify optimum process settings.

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Neural Network Modeling and Particle Swarm Optimization (PSO) of Process Parameters in Pulsed Laser Micromachining of Hardened AISI H13 Steel

Cutting of 1.2 mm thick austenitic stainless steel sheet using pulsed and CW Nd:YAG laser

Zinc-coated steel sheets are important materials in the automobile and home appliance industries. Currently, lasers are the preferred tools for metal cutting because of their good cutting quality, flexibility and excellent features and results, as compared to traditional tools. The solid-state Nd:YAG laser has successfully replaced the gaseous CO2 laser for metal cutting; its small size and short wavelength makes it suitable for cutting bright and metal-coated materials, as well as being able to be transmitted via optical fibers and robots to cut complicated three dimensional and curved shapes. In this work, the Nd:YAG laser is used to cut 1 mm zinc coated steel sheets. We demonstrate the effects of different cutting parameters such as laser power, cutting speed, different gas types and pressures, and focus position on the cutting quality characteristics of attached dross, kerf width and cut surface roughness. Using a six axes robot, cutting speed was limited to 6 m/min because of the noticeable vibration at higher speeds. Results showed that the cutting surfaces achieved were very sharp and smooth. In cutting, Nd:YAG required less power and attained higher speeds than the published results of a CO2 laser, which makes Nd:YAG an economical alternative to cut zinc and metal-coated materials. In addition, laser cutting using robots provided efficient and consistent cutting quality, especially in the case of 3D and countered cutting. Apart from using low speed, robots proved to be more economical than costly, specially designed CNC tables.

Using a Nd:YAG laser and six axes robot to cut zinc-coated steel

Attempt was made to improve the surface hardness and wear properties of AISI M2 high speed tool steel. Laser surface melting (LSM) of tool steel was conducted with 2.2 KW Nd:YAG laser as heating source. Conventional hardening of the tool steel was applied. Characterizing the LSM, with optical and field emission scanning electron microscopy and surface hardness technique was used to evaluate the micro-hardness and mechanical behaviour of different regions of melting pool. AISI M2 tool steel is approximately HV 260, hardness after conventional treatment was 850 HV and the hardness after laser surface heat treatment is around 900 HV. It was found that there is a considerable influence of the laser power density and scanning velocity on the melted zone dimensions and the re-solidified structure. Increasing laser energy and reducing the laser scanning rate results in deeper and wider melt pool formation.

M. Newishy

Papers

Cutting of 1.2 mm thick austenitic stainless steel sheet using pulsed and CW Nd:YAG laser

Using a Nd:YAG laser and six axes robot to cut zinc-coated steel

Surface Treatment of AISI M2 Tool Steel by Laser Melting

Metallurgical characterization of a failed A106 Gr-B carbon steel welded condensate pipeline in a petroleum refinery

Metallurgical analysis of ASME SA213 T12 boiler vertical water-wall tubes failure