Laser Trepan Drilling of Monel k-500 Superalloy in Low Power Laser Beam Machining

2021 ◽  
pp. 137-159
Author(s):  
D. Pramanik ◽  
N. Roy ◽  
A. S. Kuar ◽  
S. Sarkar ◽  
S. Mitra ◽  
...  
Keyword(s):  
Laser Beam ◽  
Process Parameters ◽  
Focal Point ◽  
Average Power ◽  
Cutting Speed ◽  
Pulse Frequency ◽  
Laser Beam Machining ◽  
Proposed Model ◽  
Laser Trepan Drilling ◽  
Point Distance

In the field of micro processing of materials, laser has great importance as a source of heat and for its ability to deliver a coherent beam. The use of 50-watt average power for through-hole is impossible to achieve good quality drilling of the metal sheet upto 2 mm thickness. But the use of unique parameter sawing angle and constant focal point distance plays a significant role on hole diameter and circularity in laser trepan drilling. In the present research study, laser trepan drilling is investigated through multi diode pulsed fiber laser beam machining. Experimental analysis based on central composite design (CCD) of response surface methodology (RSM) has been fulfilled to find out the mathematical model. A study of the effect of sawing angle with other process parameters such as cutting speed, power, duty cycle, and pulse frequency on overcut bottom diameter and circularity at bottom for a monel k-500 has been conducted. Experimental validation of the proposed model shows that desired hole quality can be obtained by optimization of controllable of suitable process parameters.

Intelligent Modelling and Multi-Objective Optimisation of Laser Beam Cutting of Nickel Based Superalloy Sheet

2013 ◽  
Vol 3 (2) ◽  
pp. 1-16 ◽  
Author(s):  
Amit Sharma ◽  
Vinod Yadava ◽  
K. B. Judal
Keyword(s):  
Laser Beam ◽  
Process Parameters ◽  
Pulse Width ◽  
Thin Sheet ◽  
Cutting Speed ◽  
Pulse Frequency ◽  
Good Prediction ◽  
Ann Model ◽  
Nsga Ii ◽  
Nickel Based Superalloy

In the present study, a novel technique, namely, evolutionary non-dominated sorting genetic algorithm-II (NSGA-II) was used in conjunction with developed artificial neural network (ANN) model to select optimal process parameters for achieving the better process performance in LBC. First, ANN with backpropagation algorithm was used to model the LBC of nickel based superalloy sheets. The input process parameters taken were oxygen pressure, pulse width, pulse frequency and cutting speed. The performance characteristics of interest in nickel based superalloy thin sheet cutting are average kerf taper and surface roughness. The ANN model was trained and tested using the experimental data obtained through experimentation on pulsed Nd-YAG laser beam machining system. The 4-10-11-2 backpropagation architecture was found more accurate and generalized for given problem with good prediction capability. The results show that the developed modelling and optimization tool is effective for process parameter optimization in LBC process. The optimization of the process suggests that for achieving high cut quality characteristics the pulse width, pulse frequency and cutting speed are set to lower limit within the available range and gas pressure is set to a level which is sufficient to remove the molten metal from the kerf.

Experimental Determination of the Focal Length of a Laser Beam from the Output Nozzle of a Laser Cutting Head

2017 ◽  
Vol 756 ◽  
pp. 71-79
Author(s):  
Martin Lachman ◽  
Jiří Šafka
Keyword(s):  
Laser Beam ◽  
Laser Cutting ◽  
Focal Point ◽  
Focal Length ◽  
Cutting Speed ◽  
Vital Role ◽  
Fibre Laser ◽  
Cutting Head ◽  
Industrial Operations

Laser technologies are considered to be unconventional technologies. Laser cutting is one of the most popular industrial operations that use a laser beam. Fibre lasers are most commonly used for cutting metallic materials. The aim of this paper is to experimentally demonstrate a procedure for determining the focal length of a laser beam from the output of the cutting head of a JK400FL fibre laser. Along with other factors, the correct position of the focal point of a laser beam cutting materials, plays a vital role in the quality of the cut and also in determining the cutting speed. It is possible to use a higher cutting speed of the laser machine, without compromising the quality of the cut.

scholarly journals Multi-objective optimization and analysis for laser beam cutting of stainless steel (SS304) using hybrid statistical tools GA-RSM

2021 ◽  
Vol 1201 (1) ◽  
pp. 012030
Author(s):  
A D Tura ◽  
H B Mamo ◽  
D G Desisa
Keyword(s):  
Genetic Algorithm ◽  
Surface Roughness ◽  
Stainless Steel ◽  
Laser Beam ◽  
Response Surface ◽  
Focal Point ◽  
Cutting Speed ◽  
Machining Parameters ◽  
Multi Objective ◽  
The Impact

Abstract A laser beam machine is a non-traditional manufacturing technique that uses thermal energy to cut nearly all types of materials. The quality of laser cutting is significantly affected by process parameters. The purpose of this study is to use a genetic algorithm (GA) in conjunction with response surface approaches to improve surface roughness in laser beam cutting CO2 with a continuous wave of SS 304 stainless steel. The effects of the machining parameters, such as cutting speed, nitrogen gas pressure, and focal point location, were investigated quantitatively and optimized. The tests were carried out using the Taguchi L9 orthogonal mesh approach. Analysis of variance, main effect plots, and 3D surface plots were used to evaluate the impact of cutting settings on surface roughness. A multi-objective genetic algorithm in MATLAB was used to achieve a minimum surface roughness of 0.93746 μm, with the input parameters being 2028.712 mm/m cutting speed, 11.389 bar nitrogen pressure, and a focal point position of - 2.499 mm. The optimum results of each method were compared, as the results the response surface approach is less promising than the genetic algorithm method.

scholarly journals Parametric Optimization of Nd:YAG Laser Beam Machining Process Using Artificial Bee Colony Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Rajarshi Mukherjee ◽  
Debkalpa Goswami ◽  
Shankar Chakraborty
Keyword(s):  
Genetic Algorithm ◽  
Laser Beam ◽  
Process Parameters ◽  
Nd:Yag Laser ◽  
Artificial Bee Colony ◽  
Parametric Optimization ◽  
Machining Process ◽  
Laser Beam Machining ◽  
Abc Algorithm ◽  
Bee Colony

Nd:YAG laser beam machining (LBM) process has a great potential to manufacture intricate shaped microproducts with its unique characteristics. In practical applications, such as drilling, grooving, cutting, or scribing, the optimal combination of Nd:YAG LBM process parameters needs to be sought out to provide the desired machining performance. Several mathematical techniques, like Taguchi method, desirability function, grey relational analysis, and genetic algorithm, have already been applied for parametric optimization of Nd:YAG LBM processes, but in most of the cases, suboptimal or near optimal solutions have been reached. This paper focuses on the application of artificial bee colony (ABC) algorithm to determine the optimal Nd:YAG LBM process parameters while considering both single and multiobjective optimization of the responses. A comparative study with other population-based algorithms, like genetic algorithm, particle swarm optimization, and ant colony optimization algorithm, proves the global applicability and acceptability of ABC algorithm for parametric optimization. In this algorithm, exchange of information amongst the onlooker bees minimizes the search iteration for the global optimal and avoids generation of suboptimal solutions. The results of two sample paired t-tests also demonstrate its superiority over the other optimization algorithms.

Influence of process parameters on dimensional accuracy of machined Titanium (Ti-6Al-4V) alloy in Laser Beam Machining Process

2020 ◽  
Vol 132 ◽  
pp. 106494 ◽  
Author(s):  
T. Muthuramalingam ◽  
Khaja Moiduddin ◽  
Ravi Akash ◽  
Shravan Krishnan ◽  
Syed Hammad Mian ◽  
...  
Keyword(s):  
Laser Beam ◽  
Process Parameters ◽  
Dimensional Accuracy ◽  
Machining Process ◽  
Influence Of Process Parameters ◽  
Laser Beam Machining

scholarly journals Modeling of hole geometrical features in laser drilling of AISI316L sheet

2021 ◽  
Author(s):  
Satish Namdev ◽  
◽  
Anand Pandey ◽  
Arun Kumar Pandey ◽  
◽  
...  
Keyword(s):  
Laser Beam ◽  
Cutting Speed ◽  
Pulse Frequency ◽  
Machining Process ◽  
Geometrical Features ◽  
Input Parameters ◽  
Micro Drilling ◽  
Bottom Side ◽  
Experimental Trials

Micro-drilling of AISI316L is very challenging task. Unconventional machining process may be used for such type of operation. Laser beam drilling is a best for micro drilling. High thermal energy and converging-diverging property of laser beam affects the quality of laser drilled holes. In present work Nd:YAG laser beam has been used and investigate effects of laser input parameters on responses. To minimize number of experiments, get extreme information for experimental trials. Central composite rotatable design approach has been adopted. Analysis of variance is used to find reliable input parameters, are affecting responses. From this paper, it is found that current and gas pressure are significant for hole circularity at top. Current and pulse frequency are significant for bottom side circularity. Current and cutting speed are significant parameter for hole taper.

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

2014 ◽  
Vol 2 (1) ◽  
pp. 15-46 ◽  
Author(s):  
G. Kibria ◽  
B. Doloi ◽  
B. Bhattacharyya
Keyword(s):  
Surface Roughness ◽  
Process Parameters ◽  
Average Power ◽  
Pulse Frequency ◽  
Optimum Process ◽  
Taguchi Methodology ◽  
Alumina Ceramics ◽  
Turning Process ◽  
Micro Turning ◽  
Cylindrical Workpiece

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.

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