PARAMETRIC OPTIMIZATION OF CUTTING PARAMETERS OF LASER ASSISTED CUTTING USING TAGUCHI ANALYSIS AND GENETIC ALGORITHM (original) (raw)

Comparison and Optimization of Machining Parameters by using Taguchi Method

2014

In this study, three different conditions of cutting fluids viz. dry, synthetic oil and vegetable based coconut oil cutting fluids were used to determine optimum conditions for cutting force, tool chip inter face temperature, material removal rate and surface roughness. Taguchi L9 orthogonal array design of experiment was used for the experiment plan. Cutting speed, feed rate, depth of cut and coconut oil based cutting fluid were considered as machining parameters. Response tables and main effects plots ratios were used to analyze the results. The optimum values were calculated by using regression equations and were found to be cutting force (fx)-27.93 kgf, cutting force (fy)-34 kgf, tool inter face temperature-42.28 0 C , material removal rate-0.1175 gms/sec and surface roughness was 29.03 µ .

Surface Roughness Optimization in CO2 Laser Cutting by Using Taguchi Method

Lucrarea se referă la o modalitate de aplicare a metodei Taguchi în vederea optimizării rugozităţii suprafeţei obţinute la tăierea cu laser CO 2 a semifabricatelor din oţel moale. Cercetarea experimentală a fost concepută şi s-a desfăşurat pe baza unui tabel ortogonal standard, de tip L 25 , în cazul căruia principalii parametri de tăiere au fost viteza, puterea fasciculului laser şi presiunea gazului de protecţie, cu valori pe cinci niveluri. Prin analiza valorilor medii şi prin analiza varianţei, au fost identificate valori adecvate pentru parametrii importanţi ai procesului de tăiere. Rezultatele au arătat că viteza de aşchiere şi presiunea gazului ajutător sunt cei mai importanţi factori care afectează rugozitatea suprafeţei, în timp ce influenţa puterii fasciculului laser este mult mai mică. This paper demonstrates the application of Taguchi method for optimization of surface roughness in CO 2 laser cutting of mild steel. The experiment was designed and carried out on the basis of standard L 25 Taguchi's orthogonal array in which three laser cutting parameters such as the cutting speed, laser power and assist gas pressure were arranged at five levels. From the analysis of mean values of variance, the significant laser cutting parameters were identified. The results showed that the cutting speed and assist gas pressure are the most significant parameters affecting the surface roughness, whereas the influence of the laser power is much smaller.

IJERT-Comparison and Optimization of Machining Parameters by using Taguchi Method

International Journal of Engineering Research and Technology (IJERT), 2014

https://www.ijert.org/comparison-and-optimization-of-machining-parameters-by-using-taguchi-method https://www.ijert.org/research/comparison-and-optimization-of-machining-parameters-by-using-taguchi-method-IJERTV3IS081061.pdf In this study, three different conditions of cutting fluids viz. dry, synthetic oil and vegetable based coconut oil cutting fluids were used to determine optimum conditions for cutting force, tool chip inter face temperature, material removal rate and surface roughness. Taguchi L9 orthogonal array design of experiment was used for the experiment plan. Cutting speed, feed rate, depth of cut and coconut oil based cutting fluid were considered as machining parameters. Response tables and main effects plots ratios were used to analyze the results. The optimum values were calculated by using regression equations and were found to be cutting force (fx)-27.93 kgf, cutting force (fy)-34 kgf, tool inter face temperature-42.28 0 C , material removal rate-0.1175 gms/sec and surface roughness was 29.03 µ .

Prediction of optimality and effect of machining parameters on Surface Roughness based on Taguchi Design of Experiments

Quality is the prime requirement for most of the customers and hence it is always a challenging and upcoming task in industries. This work focus on Surface Roughness produced in hard turning process on Lathe. The process of hard turning is done on AISI 1040 Steel material under dry conditions using coated Carbide Inserts and High Speed Steel (HSS) Tools. Spindle Speed and Feed are chosen as control factors. The control factors are adopted to analyze significance and contribution on the Surface Roughness of the machined parts. Taguchi methodology based on Orthogonal Arrays (OA) is used to Design the Experiments. Signal-to-noise Ratio (S/N ratio) of the generated Roughness values is used to evaluate the optimal machining parameter combinations. Later Analysis of Variance (ANOVA) is used to analyze the influences and contribution of the machining parameters on the Roughness values based on F-Statistic Test. Regression Model analysis was developed for predicting the Average Surface Roughness (Ra) as a function of Speed and Feed. Confirmation experiments are yielding an error of max 8.55% and 0.46% in Regression, while machining with Carbide and HSS tools respectively.

Optimization of machining parameters in face milling using multi-objective Taguchi technique

In this research, the effect of machining parameters on the various surface roughness characteristics (arithmetic average roughness (Ra), root mean square average roughness (Rq) and average maximum height of the profile (Rz)) in the milling of AISI 4140 steel were experimentally investigated. Depth of cut, feed rate, cutting speed and the number of insert were considered as control factors; Ra, Rz and Rq were considered as response factors. Experiments were designed considering Taguchi L9 orthogonal array. Multi signal-to-noise ratio was calculated for the response variables simultaneously. Analysis of variance was conducted to detect the significance of control factors on responses. Moreover, the percent contributions of the control factors on the surface roughness were obtained to be the number of insert (71.89 %), feed (19.74 %), cutting speed (5.08%) and depth of cut (3.29 %). Minimum surface roughness values for Ra, Rz and Rq were obtained at 325 m/min cutting speed, 0.08 mm/rev feed rate, 1 number of insert and 1 mm depth of cut by using multi-objective Taguchi technique.

Parametric Analysis of Cutting Parameters for Laser Beam Machining Based on Central Composite Design

Laser beam machining (LBM) is one in all the advanced machining processes that used for shaping virtually whole variety of engineering materials. In LBM, surface roughness is one in all necessary response that affects the product characteristics and quality of the product. During this analysis work, the impact of process parameters like cutting speed, frequency and duty cycle surface roughness (Ra) for steel material in laser cutting mentioned. L 27 orthogonal array was generated for full factorial style to better understanding of interaction among the process parameters. The values of surface roughness for steel were calculated by victimization model equations and Central Composite design of Response Surface Methodology (RSM) employed to parametric analysis of the experimental data. 1. Introduction Emergence of advanced engineering materials, rigorous design needs, and complex form and weird size of work piece prohibit the employment of conventional machining ways. Hence, it absolutely understands to develop some nonconventional machining ways called advanced machining processes. LBM is one among the advanced machining processes that are used for shaping nearly whole vary of engineering materials. There are lot of applications of LASER is in cutting of metals and non-metals, soft and difficult to machine (DTM) materials. The laser directed at the specified surface and wrapped around to cut the materials within the desired form. LBM is a non-conventional machining method, so it needs high investment and offers poor efficiency; therefore high attention needed for higher utilization of resources. The values of process parameters determined to yield the specified product quality and conjointly to maximize the method performances. In LBM, there are several factors like beam parameters, material parameters and machining parameters that affects the assorted quality characteristics, e.g. surface roughness, Heat Affected Zone (HAZ), recast layer, etc. design experimental approach used as superior from alternative approach as a result of it's a systematic and scientific manner of coming up with the experiments, assortment and analysis the info with restricted use of accessible resources. Nd: YAG and CO2 were most generally used for LBM application. Type the first days of the high power laser, Nd: YAG laser were solely accessible inperiodical mode whereas CO 2 laser were accessible each in periodical and continuous (CW) mode. Now a day's each laser varieties accessible as periodical and CW [2, 3]. Sivarao et al. [4] have through an experiment investigated the impact of surface roughness on steel having thickness 6 millimeter with numerous parameters like cutting speed, frequency and duty cycle and he find a RSM based model equation for this experiment. They found that surface roughness was extremely tormented by cutting speed and duty cycle; thus these two are the foremost affecting parameters and concluded that at high cutting speed and low duty cycle, best roughness are very often achieved. Once comparison of the information between the calculated and determined values for surface roughness they found that the deviation error between the expected and determined values isn't over than 15%, it implies that mathematical model obtained for surface roughness is reliable. During this analysis work, the impact of method parameters like cutting speed, frequency and duty cycle surface roughness (Ra) for steel material in optical maser cutting is mentioned. L-27 orthogonal array was selected for full factorial design to higher understanding of interaction

Pareto optimisation of certain quality characteristics in laser cutting by ANN-GA approach

International Journal of Advanced Intelligence Paradigms, 2017

Determining the optimal laser cutting conditions for simultaneous improvement of multiple cut quality characteristics is of great importance. The aim of the present research is to simultaneously optimise three cut quality characteristics such as surface roughness, kerf taper angle and burr height in CO 2 laser cutting of stainless steel. The laser cutting experiment was conducted based on Taguchi's experimental design using L 27 experimental plan by varying four parameters such as laser power, cutting speed, assist gas pressure and focus position at three levels. Using the obtained experimental results three mathematical models for the prediction of cut quality characteristics were developed using artificial neural networks (ANNs). The developed response models for cut quality characteristics were taken as objective functions for the multi-objective optimisation based on the genetic algorithm. The obtained optimal solution sets were used to generate 2-D and 3-D Pareto fronts. The overall improvement of about 16% was registered in multiple cut quality characteristics.

Modeling and optimization of laser cutting operations

Abstract – Laser beam cutting is one important nontraditional machining process. This paper optimizes the param- eters of laser beam cutting parameters of stainless steel (316L) considering the effect of input parameters such as power, oxygen pressure, frequency and cutting speed. Statistical design of experiments is carried in three different levels and process responses such as average kerf taper (Ta), surface roughness (Ra) and heat affected zones are mea- sured accordingly. A response surface model is developed as a function of the process parameters. Responses pre- dicted by the models (as per Taguchi’s L27OA) are employed to search for an optimal combination to achieve desired process yield. Response Surface Models (RSMs) are developed for mean responses, S/N ratio, and standard deviation of responses. Optimization models are formulated as single objective optimization problem subject to pro- cess constraints. Models are formulated based on Analysis of Variance (ANOVA) and optimized using Matlab devel- oped environment. Optimum solutions are compared with Taguchi Methodology results. As such, practicing engineers have means to model, analyze and optimize nontraditional machining processes. Validation experiments are carried to verify the developed models with success. Key words: Optimization, Laser cutting, Kerf width, Taguchi technique, Response surface methodology, Design of experiments

Application of Taguchi Method and ANOVA Analysis for Simultaneous Optimization of Machining Parameters and Tool Geometry in Turning

Abstract— Turning is one of the most important machining processes used in various industrial applications. Usually the quality of finished part in turning operation is measured in terms of surface roughness. In turn, surface quality is determined by machining parameters and tool geometry. The objective of this study is to model and optimize machining parameters and tool geometry in order to improve the surface roughness in turning operation of AISI1045 steel. Machining parameters and tool geometry are considered as input parameters. In turn, the surface roughness is selected as process output measure of performance. A Taguchi approach is employed to gather experimental data. Then, based on signal-to-noise (S/N) ratio, the best sets of cutting parameters and tool geometry specifications have been determined. Using these parameters values, the surface roughness of AISI1045 steel parts may be minimized. Experimental results are provided to illustrate the effectiveness of the proposed approach. Keywords: machining parameters; tool geometry; signal to noise, Taguchi method, analysis of variance