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

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

In this study, a selective laser melting experiment was carried out with Ti6Al4V alloy powders. To produce samples with maximum density, selective laser melting parameters of laser power, scanning speed, powder thickness, hatching space and scanning strategy were carefully selected. As a statistical design of experimental technique, the Taguchi method was used to optimize the selected parameters. The results were analyzed using analyses of variance (ANOVA) and the signal-to-noise (S/N) ratios by design-expert software for the optimal parameters, and a regression model was established. The regression equation revealed a linear relationship among the density, laser power, scanning speed, powder thickness and scanning strategy. From the experiments, sample with density higher than 95% was obtained. The microstructure of obtained sample was mainly composed of acicular martensite, α phase and β phase. The micro-hardness was 492 HV0.2.

Parametric optimization of selective laser melting for forming Ti6Al4V samples by Taguchi method

Multi-objective optimization of Nd:YAG laser cutting of nickel-based superalloy sheet using orthogonal array with principal component analysis

This paper reports the study of optimal laser parameters for cutting QFN (Quad Flat No-lead) packages by using a diode pumped solid-state laser system (DPSSL). The QFN cutting path includes two different materials, which are the encapsulated epoxy and a copper lead frame substrate. The Taguchi's experimental method with orthogonal array of L 9 (3 4 ) is employed to obtain optimal combinatorial parameters. A quantified mechanism was proposed for examining the laser cutting quality of a QFN package. The influences of the various factors such as laser current, laser frequency, and cutting speed on the laser cutting quality is also examined. From the experimental results, the factors on the cutting quality in the order of decreasing significance are found to be (a) laser frequency, (b) cutting speed, and (c) laser driving current. The optimal parameters were obtained at the laser frequency of 2 kHz, the cutting speed of 2 mm/s, and the driving current of 29 A. Besides identifying this sequence of dominance, matrix experiment also determines the best level for each control factor. The verification experiment confirms that the application of laser cutting technology to QFN is very successfully by using the optimal laser parameters predicted from matrix experiments.

Study of optimal laser parameters for cutting QFN packages by Taguchi's matrix method

This paper reports an application of the grey relational analysis (GRA) to directly optimize laser cutting of a quad flat non-lead (QFN) strip using six performance characteristics. The most important performance characteristics include the cutting depth, the width of heat affected zone (HAZ), and the width of cutting line for both epoxy and Cu+epoxy materials along the cutting path. During the GRA, higher grades are obtained from any of the deeper (more complete) cutting depth, reduced widths of the HAZ and reduced widths of the cutting line. From nine experiments based on the orthogonal array of L9(34), a current of 29 A, a frequency of 2 kHz, and a cutting speed of 2 mm/s were found to be the best parameters for laser cutting of a QFN strip with a thickness of 0.9 mm. Moreover, the analysis of variance (ANOVA) is also employed to determine the contribution of each control parameter on the cutting quality characteristics. The three largest measured contributions on the cutting quality in decreasing order are the frequency, the current, and the cutting speed. Compared with the Taguchi optimization method, the GRA approach is significantly simpler because it directly assigns appropriate weighting factors to the required qualities. Finally, confirmation experiments are performed to ensure the robustness of the GRA predicted optimal configuration for laser cutting a QFN strip.

Chen-Hao Li

Papers

Study of optimal laser parameters for cutting QFN packages by Taguchi's matrix method

The use of grey relational analysis to determine laser cutting parameters for QFN packages with multiple performance characteristics