Laser Micro-turning Research Articles

Pulsed Nd:YAG Laser Micro-turning of Alumina to Study the Effect of Overlap Factors on Surface Roughness Performance

Laser micro-turning is one of the latest micromachining technologies for processing cylindrical shaped work material. Utilizing this novel micromachining process, micron size depth of desired length along the cylindrical axis of the workpiece can be micro-turned using highly intense laser beam. In this process, there are two important overlap factors i.e. spot overlap and circumferential overlap play important role for achieving the desired quality of micro-turning surface. The present paper deals with the effect of overlap factors on roughness of laser micro-turning surface. By varying the pulse frequency, workpiece rotating speed and workpiece axial feed rate, a range of spot overlap and circumferential overlap can be achieved and experiments have been conducted at different process parametric combinations. Parametric effects and detailed analysis have been carried out using different graphical plots. Scanning electron microscopic (SEM) images of the machined surface were also analysed for the qualitative assessment and parametric effects of the process.

Optimization of Surface Roughness during Nd:YAG Laser Micro-Turning Process of Alumina

Laser micro-turning process is one of the newly developed laser material processing technologies to generate micro-turned groove or surface on cylindrical workpiece. In the present paper, an attempt has been made to investigate the laser micro-turning operation on cylindrical shaped aluminium oxide (Al 2 O 3 ) ceramic to study the influence of different laser micro-turning process parameters namely, laser average power, pulse frequency, workpiece rotational speed, assist air pressure and Y feed rate using response surface methodology (RSM) experimental plan. The mathematical model for surface roughness (Ra) has been developed and the adequacy of the model has been tested through analysis of variance (ANOVA) results. Average power and pulse frequency are the most significant process parameters. Optimal parametric combination for minimum value of surface roughness has been achieved as 5.23μm at parametric setting of average power of 9.04 W, pulse frequency of 4108.18 Hz, workpiece rotational speed of 451.16 rpm, air pressure of 1.44 kgf/cm 2 and Y feed rate of 0.37 mm/s. Confirmation experimental results show a good agreement between RSM based optimal and experimental value of response criterion.

Investigation into the effect of overlap factors and process parameters on surface roughness and machined depth during micro-turning process with Nd:YAG laser

Abstract One of the emerging laser material processing technologies to process cylindrical shaped materials is the laser micro-turning process. This process is used to machine micro-turned groove or surface on the difficult-to-process materials for a specific length of turn along its axis. The present experimental study investigates the laser micro-turning operation of a cylindrical shaped aluminum oxide (Al2O3) ceramic to explore the effect of successive spot overlap and circumferential overlap on the surface roughness (Ra) criterion. Moreover, depth of machining has also been studied by varying various process parameters such as pulse frequency, workpiece rotating speed and laser beam average power. Various amounts of spot overlap have been accomplished by different combined settings of related parameters i.e. workpiece rotating speed and pulse frequency. In contrast, various circumferential overlap between successive rotational scan widths have been achieved by varying the rotational speed and also axial feed rate of the workpiece. Surface roughness (Ra) and machined depth have been measured as output response for machining at various parametric combinations. Analyses have been made through different plots of surface roughness (Ra) and machined depth to study the influence of these overlaps and different process parameters. The experimental results revealed that surface roughness decreases with the increase of both the overlap factors. It is observed from the results that with the increase in circumferential overlap, roughness of the machined surface decreases for each workpiece rotating speed setting. Further, wide spot crater is achieved at a higher value of average power. Minimum surface roughness is achieved as 5.25 µm at average power 10 W, pulse frequency 3000 Hz, workpiece rotating speed 400 rpm and Y feed rate 0.3 mm/s. The achieved machined depth is high at a low speed of rotation and pulse frequency settings. With the increase of average power of laser beam, the machined depth is found to increase linearly. The maximum micro-turning depth is achieved as 0.146 mm at parametric combination of average power of 10 W, pulse frequency of 3000 Hz, workpiece rotating speed of 400 rpm and Y feed rate of 0.3 mm/s.

Modelling and optimization of Nd:YAG laser micro-turning process during machining of aluminum oxide (Al2O3) ceramics using response surface methodology and artificial neural network

Pulsed Nd:YAG laser has high intensity and high quality beam characteristics, which can be used to produce micro-grooves and micro-turning surface on advanced engineering ceramics. The present research attempts to develop mathematical models by using response surface methodology approach for correlating the machining process parameters and the process responses during laser micro-turning of aluminum oxide (Al2 O3 ) ceramics. The process parameters such as laser average power, pulse frequency, workpiece rotating speed, assist air pressure and Y feed rate were varied during experimentation. The rotatable central composite design experimental planning has been used to design the experimentation. The performance measures considered are surface roughness (Ra ) and micro-turning depth deviation. Multi-objective optimization has been carried out for achieving the desired surface roughness as well as minimum depth deviation during laser micro-turning operation. Further, an artificial neural network (ANN) model has been developed to predict the process criteria. Levenberg-Marquadt training algorithm is used for multilayer feed forward backpropagation neural network. The developed ANN model has 5-10-2 feed forward network. There are 5 neurons in the input layer, 10 neurons in the hidden layer and 2 neurons in the output layers corresponding to two output responses, respectively. The developed ANN model has been validated using data obtained by conducting additional set of experiments. It was found that the developed ANN model can predict the process criteria more accurately than response surface methodology (RSM) based developed models.

Parametric Study and Optimization of Nd: YAG Laser Micro-Turning Process of Different Grade of Alumina Ceramics Based on Taguchi Methodology

The present paper addresses an investigation on the effect of process parameters during Nd:YAG laser micro-turning operation of different grade of alumina (Al2O3) ceramic materials. Considering different levels of various process parameters i.e. laser beam average power, pulse frequency, workpiece rotational speed and Y feed rate, Taguchi method based experimental design has been used to construct the set of experiments. The same set of experiments has been utilized to machine 10 mm diameter cylindrical workpiece made of different grades of Alumina ceramics i.e. K60 and K80. Surface roughness (Ra) and micro-turning depth deviation were considered as the process characteristics. Analysis of variance (ANOVA) test was performed for each grade of alumina ceramic to find out the significant process parameters during laser micro-turning process. The optimum process parameters settings for individual responses were obtained by analyzing the signal-to-noise (S/N) ratio. Mathematical models, which correlate the response and process variables, have been developed for all the grades of ceramics. Multi-objective optimization i.e. simultaneous minimization of surface roughness (Ra) and micro-turning depth deviation has been done through combined approach of Taguchi methodology and Grey Relational Analysis.

Investigation and analysis on pulsed Nd:YAG laser micro-turning process of aluminium oxide (Al2O3) ceramic at various laser defocusing conditions

Laser micro-turning process is one of the latest promising laser material processing techniques which can be employed for generation of micro-turning surface of particular surface profile and dimensional accuracy on cylindrical workpiece. The present paper addresses the laser micro-turning process of cylindrical shaped 99 % pure aluminium oxide (Al2O3) ceramics of size 10 mm in diameter and 40 mm in length. The experiments have been conducted using response surface methodology design of experiments. The targeted depth was set at 100 μm. Laser average power, pulse frequency, workpiece rotating speed, air pressure and Y feed rate were considered as process variables. After each experiment, surface roughness (Ra) and micro-turning depth deviation have been measured. Empirical models of the responses have been developed based on the test results achieved during measurements of surface roughness and machined depth deviation. Analysis of variance was conducted. Multi-objective optimal parametric combination of process variables has been obtained for achieving least values of responses, i.e. surface roughness and depth deviation. To achieve further high-quality machined surface, machining was done at various defocusing conditions of laser beam and also by varying the number of laser scan passes. Other process parameters were kept constant at optimal parametric combination obtained in multi-objective optimization. From the experimental results, it was revealed that surface roughness decreases with increase in defocusing positions. With increase in number of passes up to a certain limit, surface roughness decreases. However, depth deviation increases with number of laser scan passes at all levels of defocus planes.

Experimental investigation and multi-objective optimization of Nd:YAG laser micro-turning process of alumina ceramic using orthogonal array and grey relational analysis

The present paper addresses an experimental investigation on the effect of process parameters during Nd:YAG laser micro-turning operation of 99% of alumina (Al2O3) ceramic materials. Taguchi methodology based experimental design was adopted for carrying out experimentations. The process parameters considered during machining are laser beam average power, pulse frequency, workpiece rotational speed and Y feed rate. Surface roughness (Ra) and micro-turning depth deviation were considered as the performance criteria for the present experimentation. Analysis of Variance (ANOVA) was performed to find out the significant process parameters during laser micro-turning process. The optimum process parametric settings were obtained by analyzing the signal-to-noise (S/N) ratio values. Experiments on optimal process parametric settings of the responses have been carried out and overall error percentage in S/N ratio calculated is 3.59%. The mathematical model for each of the responses has been developed to predict the mentioned response criteria. Validity of the models have been checked through experiments and the overall error percentages of surface roughness (Ra) and micro-turning depth deviation for validation experiments are 2.83 and 2.96%, respectively. Further experiments have been conducted to study and analyse of the most contributing parameters on respective process criteria.

Predictive model and process parameters optimization of Nd:YAG laser micro-turning of ceramics

The present work highlights laser micro-turning operation of 10-mm diameter cylindrical-shaped alumina (Al2O3) ceramic using pulsed Nd:YAG laser. The paper also addresses development of mathematical models for correlating the various micro-machining parameters such as laser beam average power, pulse frequency, workpiece rotational speed, assist air pressure, and Y feed rate with the response criteria such as surface roughness and deviation in turned depth for achieving desired surface quality as well as dimensional accuracy during micro-turning operation using Nd:YAG laser system. Response surface methodology-based design of experiments has been adopted for the experimentation. This investigation also highlights the various test results that confirm the validity and correctiveness of the developed mathematical models through analysis of variance test. The test results were analyzed through various response surface plots to study the effect of the process parameters on the aforementioned responses. The results of validation experimentation show a good agreement for the developed empirical models. Sensitivity analyses of the developed models have been done to find out the variation in the output with respect to variations in the significant input process parameters. Moreover, multi-performance optimization has been done to find out the optimal parametric setting for achieving the desired process performances. Analysis also has been made based on scanning electron microscopy micrographs of the laser micro-turned surface achieved during machining at multi-criteria optimization setting.

Optimisation of Nd:YAG laser micro-turning process using response surface methodology

The present paper investigates the laser micro–turning operation on cylindrical aluminium oxide (Al2O3) ceramic to study the influence of different process parameters namely, laser average power, pulse frequency, workpiece rotational speed, assist air pressure and Y feed rate on surface roughness (Ra and Rt) and micro–turning depth deviation. The mathematical models for the responses have been developed based on response surface methodology (RSM). Through different surface plots, analyses have been made to study the influences of process parameters on responses. The adequacy of the developed models has been tested through analysis of variance (ANOVA). To investigate into the variation in the output for small variations in significant process parameters, sensitivity analyses (SA) have been done of the models developed for each response. Multi–objective optimisation has also been performed for searching out the optimal parametric condition for achieving minimum surface roughness and minimum depth deviation during laser micro–turning process.

Experimental Investigation into Pulsed Nd:YAG Laser Micro-Turning of Engineering Ceramics

Laser beam machining (LBM) is the most exciting thermal energy based non-contact type advanced material machining method to process almost whole range of materials. The laser microturning of ceramics are highly demanded in the present industries because of its wide and potential uses in various engineering fields such as automobile, electronics, aerospace, biomedical applications etc. The present paper addresses the basic experimental study of Nd:YAG laser microturning of advanced engineering cylindrical shaped ceramic material to explore the desired laser output responses i.e. depth of cut and surface roughness by varying laser micro-turning process parameters such as lamp current, pulse frequency and rotational speed of workpiece etc.

Experimental analysis on Nd:YAG laser micro-turning of alumina ceramic

Laser micro-turning is a micro-machining strategy to machine cylindrical workpiece of hard-to-process materials such as ceramics. Laser micro-turning method is in high demand in the present high-precision manufacturing industries because of its wide and potential uses in various engineering fields such as automobile, electronics, aerospace, and biomedical applications, etc. In the present research, the experimental analysis of Nd:YAG laser micro-turning of cylindrical-shaped ceramic material has been made to explore the desired laser output responses, i.e., depth of cut and surface roughness by varying laser micro-turning process parameters such as lamp current, pulse frequency, and laser beam scanning speed. Single laser beam has been utilized for successful micro-turning operation. Experimental results revealed that the laser machining process parameters have great influences for achieving desired laser micro-turned depth and surface roughness characteristics during laser micro-turning of alumina ceramics. SEM and optical photographs have also been analyzed for better understanding of the laser micro-turning process for different parametric settings.