Modelling and Analysis of UV Laser Micromachining of Copper

UV laser micromachining of metallic materials has been used in microelectronic and other industries. Knowledge and data about the process vary with feature size, material, laser wave-length and pulse duration. This paper reports on experimental and numerical investigation of micromachining of copper using a frequency tripled Nd:YAG laser with 50 ns pulse duration. An axisymmetric model is developed which allows consideration of laser beam distribution and its coupling with the target material. This is important for the process where the removal extent is in the same order of the removal depth. The model uses an enthalpy method to track the solid/liquid interface. Stefan and kinetic boundary conditions are applied at the liquid–vapour interface, and property discontinuity across the Knudsen layer is considered. Relevant experimental results are also presented and compared with the model predicted results. The range of thermal vaporisation dominated machining of copper using nanosecond time scale lasers was studied, and optimum laser intensity for micromachining of copper was suggested.     

Development and investigations on a hybrid tooling concept for coaxial and concurrent application of electrochemical and laser micromachining processes

In hybrid laser-electrochemical micromachining, both laser and electrochemical process energies act along the same machining axis and thus both influence material removal by their interaction. The traditional nozzle based laser assisted jet-ECM concepts require laser to be focused on workpiece surface in an electrochemical environment and are limited in aspect ratios as the nozzle stays above the workpiece surface. In this work, a hybrid tooling concept is proposed for a novel process scheme of precision hybrid laser-electrochemical micromachining. The tool serves the function of both an ECM electrode as well as a leaky-type multimode waveguide for the laser and delivers laser homogeneously together with the electrolyte on the workpiece surface without requiring laser to be focused on the workpiece surface. A precision prototype hybrid machine-tool is developed which employs short pulsed nano-second laser and micro-second pulsed voltage source for precision micromachining. For this system, ray tracing and detailed multiphysics electrochemical micromachining process simulations are carried out to demonstrate the applicability of this hybrid tooling concept and explain the shape evolution. Successful experimental realization of coaxial and concurrent application of electrochemical and laser processes is presented. Prototype tool electrodes are fabricated and experiments are carried out on an in-house developed prototype hybrid machine tool. The results reveal that the proposed hybrid tool is successfully capable of concentrating laser and electrochemical process energies simultaneously in the same machining zone. However, with the initial design of this hybrid tool, a maximum of 30–40% of laser power is available in the machining zone. Some suggestions for further research will be presented.     

Drilling of micro-holes on copper using electrochemical micromachining

Electrochemical micromachining (EMM) is one of the best micromachining techniques for machining electrically conducting, tough, and difficult-to-machine materials with suitable machining parameter combinations. For the micro-fabrication of components like nozzle plate for ink jet printer head and delicate 3D electronic circuit board components, EMM is predominantly used. In this paper, the effect of process parameters such as such as electrolyte concentration, machining voltage, frequency, and duty cycle on the material removal rate (MRR) and overcut were studied using copper workpiece. According to Taguchi’s quality design concepts, an L₁₈ orthogonal array is used. ANOVA is also performed to determine the most significant parameter that influences the EMM process. The optimum process parameters for lower overcut and higher MRR are found out and confirmation tests were carried out to validate the prediction. The confirmation test results show 19 and 20.78?% improvements of overcut and MRR, respectively, with respect to the initial parametric setting.     

Investigation into electrochemical micromachining (EMM) through response surface methodology based approach

Electrochemical micromachining (EMM) could be used as one the best micromachining technique for machining electrically conducting, tough and difficult to machine material with appropriate machining parameters combination. This paper attempts to establish a comprehensive mathematical model for correlating the interactive and higher-order influences of various machining parameters, i.e. machining voltage pulse on/off ratio, machining voltage, electrolyte concentration, voltage frequency and tool vibration frequency on the predominant micromachining criteria, i.e. the material removal rate and the radial overcut through response surface methodology (RSM), utilizing relevant experimental data as obtained through experimentation. Validity and correctiveness of the developed mathematical models have also been tested through analysis of variance. Optimal combination of these predominant micromachining process parameters is obtained from these mathematical models for higher machining rate with acuuracy. Considering MRR and ROC simultaneously optimum values of predominant process parameters have been obtained as; pulse on/off ratio, 1.0, machining voltage, 3 V, electrolyte concentration, 15 g/l, voltage frequency of 42.118 Hz and tool vibration frequency as 300 Hz. The effects of various process parameters on the machining rate and radial overcut are also highlighted through different response surface graphs. Condition of machined micro-holes are also exhibited through the SEM micrographs in this paper. Pulse voltage pattern during electrochemical micromachining process has been analyzed with the help of voltage graphs. Irregularities in the nature of pulse voltage pattern during electrochemical micromachining have been observed and the causes of these irregularities are further investigated.     

A study on copper micromachining using microorganisms

Biomachining using microorganisms to remove metal from a workpiece is an alternative technology for machining processes that may have environmental advantages. Studies of the characteristics of micromachining using microorganisms such as Acidithiobacillus ferrooxidans will explore and improve the capabilities of this alternative machining process. The objective of this study is to investigate the surface roughness and the material removal rate characteristics in biomachining of copper for various machining times. We present the biomachining of copper using A. ferrooxidans, including bacterial culturing and workpiece preparation, and a comparison of the surface roughness, visible surface appearance of the workpiece, and material removal rate before and after biomachining process.     

The influence of organobentonite clay on CO2 laser grooving of nylon 6 composites

The popular polycaprolactam (polyamide PA6), commonly referred to as nylon 6, widely used as a construction plastic, is not a typical material for micromachining by CO₂ laser vaporization. In this paper, we describe investigations of the pulsed CO₂ laser grooving of both the chemically pure and the organobentonite clay modified nylon 6. Our results indicate that doping of nylon 6 with nanoparticles of organophilized bentonite significantly improves the grooving ability, predictability of the process, and its quality. In order to determine the nature of the changes in the depth and width of the grooves as a function of the laser process parameters, theoretical modeling of the laser grooving of nylon was carried out. The basic parameters of the laser grooving process versus laser beam intensity, pulse repetition rate, scanning speed of the material and various compositions of the organophilized bentonite dopant are presented. Additionally, an example of a three-dimensional engraving/milling of tested materials as well as the impact of doping on the channel profile are examined. The modification of nylon 6 by appropriate doping with bentonite clay radically improves the quality of micromachining with a CO₂ laser.     

Analysis and predictive modeling of performance parameters in electrochemical drilling process

In this paper, the effect of feed rate, voltage, and flow rate of electrolyte on some performance parameters such as surface roughness, material removal rate, and over-cut of SAE-XEV-F valve-steel during electrochemical drilling in NaCl and NaNo₃ electrolytic solutions have been studied using the main effect plot, the interaction plot and the ANOVA analysis. In continuation, in this case which the training dataset was small, an investigation has been done on the capability of the optimum presented regression analysis (RA), artificial neural network (ANN), and co-active neuro-fuzzy inference system (CANFIS) to predict the surface roughness, material removal rate and over-cut. The predicted parameters by the employed models have been compared with the experimental data. The comparison of results indicated that in electrochemical drilling using different electrolytic solutions, CANFIS gives the best results to predict the surface roughness and over-cut as well, while ANN is the best for predicting the material removal rate.     

Recast layer removal using ultrafast laser in titanium alloy

Recast layer, which has undesirable effects on the fatigue resistance and service life of components and microstructures, has been observed and analyzed from the points of surface morphology and internal microstructure by three test methods including scanning electron microscopy, metallographic corrosion analysis, and transmission electron microscopy in this study. In order to reduce the harms of these unwanted recast layers, taking ultrafast laser as a post-machining method for recast material removal is proposed based on the advantages of ultrafast laser micromachining technology, which include the wide material applicability and absence of the recast layer during processing. The feasibility of this new recast layer removal method was verified by experiments on Ti-6Al-4V. With a series of optimized processing parameters, horizontally bedded scanning processing was adopted ultimately in final recast layer removal experiment because of its higher material removal rate and better machined surface quality compared with vertically shifting scanning processing. Based on the theoretical analysis and experimental results, ultrafast laser could be widely applied in more fields of microstructures finish machining.     

Characterization of a heat flux sensor using short pulse laser calibration

A method to calibrate classical heat flux sensors is presented. The classical approach to measure the temperature inside a known material by using a thermocouple fails when the measurement time is very short. In this work the surface heat flux is determined by solving the inverse heat conduction problem using a noninteger identified system as a direct model for the estimation process. Using short pulse laser calibration measurements the crucial design aspects of the sensor that play a significant role when assuming one-dimensional, semi-infinite heat transfer have been accounted for. The theoretical approach as well as the calibration results are presented and comparisons to the classical approach and results from finite element modeling are shown. It is concluded that the new method ameliorate the heat flux sensor significantly and extend its application to very short measurement times.     

Ultrafast laser micromachining of 3C-SiC thin films for MEMS device fabrication

Femtosecond pulsed laser (800 nm, 120 fs) micromachining of thin films of 3C-SiC (β-SiC) semiconductor deposited on silicon substrate was investigated as a function of pulse energy (0.5 μJ to 750 μJ). The purpose is to establish suitable laser parametric regime for the fabrication of high accuracy, high spatial resolution and thin diaphragms for high-temperature MEMS pressure sensor applications. Etch rate, ablation threshold and quality of micromachined features were evaluated. The governing ablation mechanisms, such as thermal vaporization, phase explosion, Coulomb explosion and photomechanical fragmentation, were correlated with the effects of pulse energy. The results show that the etch rate is higher and the ablation threshold is lower than those obtained with nanosecond pulsed excimer laser ablation, suggesting femtosecond laser’s potential for rapid manufacturing. In addition, the etch rates were substantially higher than those achievable in various reactive ion and electrochemical etching methods. Excellent quality of machined features with little collateral thermal damage was obtained in the pulse energy range (1–10 μJ). The leading material removal mechanisms under these conditions were photomechanical fragmentation, ultrafast melting and vaporization. At very low pulse energies (<1 μJ), nanoscale material removal has occurred with the formation of nanoparticles that is attributed to Coulomb explosion mechanism. The effect of assist gas on the process performance at low and high energy fluences is also presented.     

基于UKF的机器人末端执行器位姿实时估算方法

为了能在工业机器人运动过程中快速准确地估算出末端执行器的位姿,提出了一种基于unscented卡尔曼滤波器（UKF）的末端执行器位姿实时估算方法,并将该方法应用于以激光跟踪仪作为反馈系统的工业机器人中。首先,在工业机器人运动过程中实时获取各个关节运动参数,并结合工业机器人的结构参数计算末端执行器的位姿初值,然后借助于激光跟踪仪实时跟踪测量固定在机器人末端执行器上的一个测量点,运用UKF融合以上两类数据,估算出末端执行器的实时位姿。计算机仿真验证了该方法的有效性与实时性,同时表明该方法具有易于实现、计算速度快和精度高等优点。     

Modelling and multi-response optimization of hole sinking electrical discharge micromachining of titanium alloy thin sheet

Thin sheets of titanium alloys are widely used in aerospace and automotive industries for specific applications. The creation of micro holes with requisite hole quality in thin sheets of these alloys using energy of electric discharge is a challenging task for manufacturing engineers. Hole sinking electrical discharge micromachining (HS-EDMM) is one of the most promising micromachining processes to create symmetrical and non-symmetrical micro holes. The present paper is related to selection of optimum parameter settings for obtaining maximum material removal, minimum tool wear and minimum hole taper in HS-EDMM. In this paper an attempt has been made to develop an integrated model (ANN-GRA-PCA) of single hidden layer back propagation neural network (BPNN) for prediction and grey relational analysis (GRA) coupled with principal component analysis (PCA) hybrid optimization strategy with multiple responses of HSEDMM of Ti-6Al-4V. Experiments have been conducted to generate dataset for training and testing of the network where input parameters consist of gap voltage, capacitance of capacitor and the resulting performance parameters are represented by material removal rate (MRR), tool wear rate (TWR), and hole taper (T_a). The results indicate that the integrated model is capable to predict and optimize process performance with reasonable accuracy under varied operating conditions of HS-EDMM. The proposed approach would be extendable to other configurations of EDMM processes for different materials.     

Development of an inversion model for establishing EDM input parameters to satisfy material removal rate, electrode wear ratio and surface roughness

Electro-discharge machining (EDM) has grown tremendously over the last few decades. Due to its extensive capabilities, this technique has been increasingly adapted to new industrial applications within the field of aerospace, medical, die and mould production, precision tooling, etc. The novelty of the research presented in this paper lies in solving an inversion model, based on the least squares theory, which involves establishing the values of the EDM input parameters (peak current level, pulse-on time and pulse-off time) to ensure the simultaneous fulfilment of material removal rate (MRR), electrode wear ratio (EWR) and surface roughness (SR). The inversion model was constructed from a set of experiments and the equations formulated in the forward model described in the first part of this paper. In the forward model, the well-known ANOVA and regression models were used to predict the EDM output performance characteristics, such as MRR, EWR and SR in the EDM process for AISI 1045 steel with respect to a set of EDM input parameters.     

Variogram-based fault diagnosis in an interconnected tank system

We consider in this paper the fault diagnosis problem of a three tank system DTS-200 pilot plant. The presented approach is based on the analysis of the variogram, which is a graphical variance representation that characterizes the distribution of a measured dataset, and is used to extract the sensor fault parameters. These parameters are obtained by determining the best mathematical model that fits the empirical data. Nonlinear regression techniques are used to estimate the model coefficients. Experimental study is provided to illustrate the potential applicability of this method in process monitoring.     

Investigation of damage generation process by stress waves during femtosecond laser drilling of SiC

Femtosecond laser processing has garnered significant attention as a method for micromachining silicon carbide (SiC), which is expected to be used in next-generation power semiconductors. However, a significant amount of damage is generated around the processing area during the femtosecond laser processing of SiC. In this study, high-speed phenomena during the femtosecond laser drilling of SiC are observed with high temporal and spatial resolutions by combining pump-probe imaging and a high-speed camera. In addition, a stress wave propagation simulation based on experimental results is conducted. Based on the experimental and simulation results, the mechanism of damage generation by the stress wave generated during material removal is elucidated. The damage generation mechanism elucidated in this study will facilitate the development of damage suppression methods and the expansion of industrial applications of SiC.     

Experimental investigation and analytical modelling of the effects of process parameters on material removal rate for bonnet polishing of cobalt chrome alloy

Cobalt chrome alloys are the most extensively used material in the field of total hip and total knee implants, both of which need highly accurate form and low surface roughness for longevity in vivo. In order to achieve the desired form, it is extremely important to understand how process parameters of the final finishing process affect the material removal rate. This paper reports a modified Preston equation model combining process parameters to allow prediction of the material removal rate during bonnet polishing of a medical grade cobalt chrome alloy. The model created is based on experiments which were carried out on a bonnet polishing machine to investigate the effects of process parameters, including precess angle, head speed, tool offset and tool pressure, on material removal rate. The characteristic of material removal is termed influence function and assessed in terms of width, maximal depth and material removal rate. Experimental results show that the width of the influence function increases significantly with the increase of the precess angle and the tool offset; the depth of the influence function increases with the increase of the head speed, increases first and then decrease with the increase of the tool offset; the material removal rate increases with the increase of the precess angle non-linearly, with the increase of the head speed linearly, and increases first then decreases with the increase of the tool offset because of the bonnet distortion; the tool pressure has a slight effect on the influence function. The proposed model has been verified experimentally by using different Preston coefficients from literature. The close values of the experimental data and predicted data indicate that the model is viable when applied to the prediction of the material removal rate in bonnet polishing.     

Multi-objective parametric optimization on machining with wire electric discharge machining

The selection of optimum machining conditions, during wire electric discharge machining process, is of great concern in manufacturing industries these days. The increasing quality demands, at higher productivity levels, require the wire electric discharge machining process to be executed more efficiently. Specifically, the material removal rate needs to be maximized while controlling the surface quality. Despite extensive research on wire electric discharge machining process, determining the desirable operating conditions in industrial setting still relies on the skill of the operators and trial-and-error methods. In the present work, an attempt has been made to optimize the machining conditions for maximum material removal rate and maximum surface finish based on multi-objective genetic algorithm. Experiments, based on Taguchi’s parameter design, were carried out to study the effect of various parameters, viz. pulse peak current, pulse-on time, pulse-off time, wire feed, wire tension and flushing pressure, on the material removal rate and surface finish. It has been observed that a combination of factors for optimization of each performance measure is different. So, mathematical models were developed between machining parameters and responses like metal removal rate and surface finish by using nonlinear regression analysis. These mathematical models were then optimized by using multi-objective optimisation technique based on Non-dominated Sorting Genetic Algorithm-II to obtain a Pareto-optimal solution set.     

A simulation platform for optimal selection of robotic belt grinding system parameters

Robotic belt grinding is an effective process for removing material from geometrically complex workpieces. However, due to the relatively low stiffness of the system, the grinding quality is prone to inaccuracies caused by system dynamics. In order to control the quality of the grinding process, a profound understanding of the system is required. This paper presents a platform for comprehensive modeling and simulation of the robotic belt grinding system. The system kinematics model is based on the CAD model of the workpiece in composition with robot kinematics. The dynamics model is a comprehensive combination of the dynamics of the robot, the grinder, and the interaction between the grinder and the workpiece. A material removal model of the grinding process, which can adapt to workpieces with complicated shapes, is also developed and presented. The system simulation shows that optimal selection of key control parameters of the grinder and proper selection of robot control strategies can efficiently suppress chatter in the grinding process. Furthermore, having the ability to predict material removal rate, the comprehensive simulation platform is also demonstrated to be a strong tool in selecting the grinding process key parameters, namely, robotic velocity and contact force, for the control of material removal to meet dimensional accuracy requirements on workpieces.     

Simulation of abrasive flow machining process for 2D and 3D mixture models

Improvement of surface finish and material removal has been quite a challenge in a finishing operation such as abrasive flow machining (AFM). Factors that affect the surface finish and material removal are media viscosity, extrusion pressure, piston velocity, and particle size in abrasive flow machining process. Performing experiments for all the parameters and accurately obtaining an optimized parameter in a short time are difficult to accomplish because the operation requires a precise finish. Computational fluid dynamics (CFD) simulation was employed to accurately determine optimum parameters. In the current work, a 2D model was designed, and the flow analysis, force calculation, and material removal prediction were performed and compared with the available experimental data. Another 3D model for a swaging die finishing using AFM was simulated at different viscosities of the media to study the effects on the controlling parameters. A CFD simulation was performed by using commercially available ANSYS FLUENT. Two phases were considered for the flow analysis, and multiphase mixture model was taken into account. The fluid was considered to be a Newtonian fluid and the flow laminar with no wall slip.     

Theoretical and experimental investigation of pulsed laser grooving process

A theoretical model has been developed for simulating the laser grooving process. It takes into account the interaction among subsequent pulses, the required time for the melting temperature to be reached and the subsequent removal of a finite volume of material during each laser pulse. The model predicts the maximum groove depth that can be achieved for a specified set of process parameters, such as laser power, pulsing frequency, and scanning velocity. The theoretical predictions have been experimentally tested with a medium-power laser beam.