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

Polymers for additive manufacturing and 4D-printing: Materials, methodologies, and biomedical applications

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

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 presents a novel effective method for optimizing laser cutting of specially shaped electronic printed circuit board (PCB) carrier substrates of advanced integrated circuit (IC) back-end packages that have multiple performance characteristics identified using grey relational analysis (GRA) Laser cutting parameters, including laser beam parameters (average laser power and Q-switch frequency), focusing parameters (laser beam focusing spot size), and machine parameters (laser cutting speed), were optimized based on multiple performance characteristics Some characteristics of the specially shaped flash memory module for IC packages, such as smart disk (SD) cards are verified The characteristics of interest are the average surface roughness on a PCB substrate cross-section, and the maximum width of the heat-affected zone (HAZ) Eight experiments were conducted using GRA to optimize the settings for laser beam cutting parameters to generate various quality characteristics Analysis of the grey relational grade indicates that parameter significance and the optimal parameter combination for the laser cutting process are identified The analytical results from two confirmation experiments using the optimal parameters confirm that laser cutting technology can be effectively applied to cut substrates into special shapes

Multi-objective optimization of laser cutting for flash memory modules with special shapes using grey relational analysis

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.

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

A traditional addictive manufacturing (AM) system is composed of 3D digital design technology, chromatics, material jetting, material science, digital manufacturing and intelligent control of a mechatronics system. However, there are plenty of disadvantages in such a system such as uneven size of droplet, unstable printing process and low quality of end product, which may even cause the piezoelectric head and module damage. The main purpose of this study is to develop a Material Jetting (MJ)-based color 3D manufacturing system by using multiple piezoelectric heads, optimizing sub-system parameter and designing a stable module. First of all, capability of printing with five different colors (CMYKW) and ultraviolet (UV) curable support material were developed. The waveform editing and printing program planning were integrated to maximize the performance of print modules. So far, the integration of color mixing, piezo material process, CMYKWS curable process and multi-inkjet head control has been carried out in the system. The purpose of this paper is to provide a powerful approach for colorful 3D object printing. The experimental results show that this color based 3D printing system could achieve both high resolution of 600dpi and more than 256 colors. This study conforms to the future development trend and market demand on color 3D additive manufacturing.

A study of a material jetting based color 3d printing system by using multiple piezoelectric heads

The 3D printing, also called additive manufacturing, is a combination of three-dimensional digital design technology, material science, digital manufacturing and intelligent control of a mechatronics system etc. The main purpose of this study is to develop a color photo-curable 3D manufacturing system by using multiple Piezoelectric heads. Four different colors (CMYW) of curable materials (UV resin) were developed first. This study has finished system integration of color mixing, piezo material process, CMYW curable process of and multi-inkjet head control etc. The proposed system can provide colorful 3D object printing solutions. From the experimental results with multiple piezo-heads (150dpi each), the developed color 3D printing technique can achieve the resolution of 300 dpi and 256 colors. This study also complies with the future development trend and market's requirements of color 3D additive manufacturing product.

Ming-Jong Tsai

Papers

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

Multi-objective optimization of laser cutting for flash memory modules with special shapes using grey relational analysis

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

A study of a material jetting based color 3d printing system by using multiple piezoelectric heads

Development of a color photo-curable 3D printing mechatronics system by using multiple piezoelectric heads