The selection of optimal cutting parameters in turning operation is very important to
achieve high cutting performance. This paper deals with the optimization of performance
characteristics of turning EN-16 steel alloy using tungsten carbide inserts by Taguchi approach. The
experiments were performed on the basis of an L-18 orthogonal array given by Taguchi’s parameter
design approach. The performance characteristics such as thrust force and Material Removal Rate
(MRR) are optimized with the optimal combination of cutting parameters such as nose radius,
cutting speed, feed rate and depth of cut. Analysis of variance (ANOVA) is applied to identify the
most significant factor using MINITAB-16 software. The cutting parameters are varied to observe
the effects on performance characteristics and find the optimal results. Finally, confirmation tests are
performed to verify the experimental results. The results from the confirmation tests proved that the
performance characteristics such as thrust force and MRR are improved simultaneously through
optimal combination of process parameters obtained from Taguchi approach
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Application of taguchi method in optimization of tool flank wear width ...Alexander Decker
1) The document applies Taguchi techniques to optimize tool flank wear width in turning AISI 1045 steel. An L9 orthogonal array is used to experiment with cutting speed, feed rate, and depth of cut as parameters.
2) Analysis of mean responses and S/N ratios found minimum wear at high speed, low feed rate, and shallow depth of cut. ANOVA showed cutting speed most influential.
3) Confirmation experiments verified 23.85% reduction in wear width at the optimal parameter levels of high speed, low feed rate, and shallow depth of cut.
Analysis and Optimization Of Boring Process Parameters By Using Taguchi Metho...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
“Optimization of Cutting Parameters for Turning AISI 316 Stainless Steel Base...IOSRJMCE
The objective of this work is the optimization of the cutting parameters for turning AISI 316 stainless steel to achieve the better surface finish using Taguchi’s methodology. Taguchi Parameter Design is a powerful and efficient method for optimizing quality and performance output of manufacturing processes, thus a powerful tool for meeting this challenge. This work discusses an investigation into the use of Taguchi Parameter Design for optimizing surface roughness generated by a Turning operation. In this method, four control factors viz. cutting speed, feed rate, depth of cut, three different cutting fluids (sherol B, sherol ENF, straight cutting oil) and one work piece material (AISI 316 stainless steel) were investigated at three different levels and the turning operations are done on Banka 1000 lathe machine. Cutting speed followed by cutting fluid has the significant role. The quality characteristic identified is surface roughness. Experiments carried out using L9 (34 ) Orthogonal Array with three different levels of control factors.The test results were analyzed using “smallerthe-better” criteria for Signal-to-Noise ratio in order to optimize the process. The experimental results were analyzed, conformed and successfully used to achieve good surface finish on work piece materials.
IRJET- Multi-Objective Optimization of Machining Parameters by using Response...IRJET Journal
This document summarizes a literature review on optimization of machining parameters for turning operations. Several studies that optimized cutting speed, feed rate, and depth of cut to minimize surface roughness and maximize material removal rate are reviewed. Response surface methodology was used in many of these studies to develop models of the output responses based on the input parameters. The literature showed that feed rate typically had the greatest influence on surface roughness, while cutting speed most influenced material removal rate. This study aims to use response surface methodology to optimize machining time and maximize material removal rate during turning of EN-31 alloy steel.
This document summarizes a study that used Taguchi methodology and Grey Relational Analysis to optimize machining parameters for CNC end milling of stainless steel 304. The goals were to minimize surface roughness (Ra) and maximize material removal rate (MRR). Experiments were conducted using an L9 orthogonal array to test cutting speed, feed rate, and depth of cut at three levels. Response data was normalized and Grey Relational Coefficients were calculated to determine the optimal parameter combination. The analysis found that a cutting speed of 75 m/min, feed rate of 0.15 mm/rev, and depth of cut of 1.5 mm provided the best results for achieving the combined objectives of lower Ra and higher MRR.
Experimental Analysis of Material Removal Rate in Drilling of 41Cr4 by a Tagu...IJERA Editor
In manufacturing industries the largest amount of money spent on drills. Therefore, from the viewpoint of cost and productivity, modeling and optimization of drilling processes parameter are extremely important for the manufacturing industry this paper presents a detailed model for drilling process parameter. The detailed structure includes in the model, are three parameters such as such as Spindle Speed, feed and depth of cut on material removal rate in drilling of 41 Cr 4 material using HSS spiral drill .We an effect of this three parameters on material removal rate .The detailed mathematical model is simulated by Minitab14 and simulation results fit experiment data very well In this investigation, an effective approach based on Taguchi method, analysis of variance (ANOVA), multivariable linear regression (MVLR), has been developed to determine the optimum conditions leading to higher MRR. Experiments were conducted by varying Spindle Speed, feed and depth of cut using L9 orthogonal array of Taguchi method. The present work aims at optimizing process parameters to achieve high MMR. Experimental results from the orthogonal array were used as the training data for the MVLR model to map the relationship between process parameters and MMR the experiment was conducted on drilling machine. From the investigation It concludes that speed is most influencing parameter followed by feed and depth of cut on MRR
Application of taguchi method in the optimization of boring parameters 2IAEME Publication
1. The document describes using the Taguchi method to optimize boring parameters, including cutting speed, feed rate, and depth of cut, to minimize surface roughness.
2. An experiment was conducted using an L27 orthogonal array with 3 factors at 3 levels each, for a total of 27 experiments. Signal-to-noise ratios and analysis of variance were used to analyze the results.
3. The experimental results revealed that depth of cut had the most significant effect on surface roughness, followed by feed rate and then cutting speed, within the specified test ranges. The optimal parameter settings were identified as cutting speed at level 2, feed rate at level 3, and depth of cut at level 1.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Application of taguchi method in optimization of tool flank wear width ...Alexander Decker
1) The document applies Taguchi techniques to optimize tool flank wear width in turning AISI 1045 steel. An L9 orthogonal array is used to experiment with cutting speed, feed rate, and depth of cut as parameters.
2) Analysis of mean responses and S/N ratios found minimum wear at high speed, low feed rate, and shallow depth of cut. ANOVA showed cutting speed most influential.
3) Confirmation experiments verified 23.85% reduction in wear width at the optimal parameter levels of high speed, low feed rate, and shallow depth of cut.
Analysis and Optimization Of Boring Process Parameters By Using Taguchi Metho...inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
“Optimization of Cutting Parameters for Turning AISI 316 Stainless Steel Base...IOSRJMCE
The objective of this work is the optimization of the cutting parameters for turning AISI 316 stainless steel to achieve the better surface finish using Taguchi’s methodology. Taguchi Parameter Design is a powerful and efficient method for optimizing quality and performance output of manufacturing processes, thus a powerful tool for meeting this challenge. This work discusses an investigation into the use of Taguchi Parameter Design for optimizing surface roughness generated by a Turning operation. In this method, four control factors viz. cutting speed, feed rate, depth of cut, three different cutting fluids (sherol B, sherol ENF, straight cutting oil) and one work piece material (AISI 316 stainless steel) were investigated at three different levels and the turning operations are done on Banka 1000 lathe machine. Cutting speed followed by cutting fluid has the significant role. The quality characteristic identified is surface roughness. Experiments carried out using L9 (34 ) Orthogonal Array with three different levels of control factors.The test results were analyzed using “smallerthe-better” criteria for Signal-to-Noise ratio in order to optimize the process. The experimental results were analyzed, conformed and successfully used to achieve good surface finish on work piece materials.
IRJET- Multi-Objective Optimization of Machining Parameters by using Response...IRJET Journal
This document summarizes a literature review on optimization of machining parameters for turning operations. Several studies that optimized cutting speed, feed rate, and depth of cut to minimize surface roughness and maximize material removal rate are reviewed. Response surface methodology was used in many of these studies to develop models of the output responses based on the input parameters. The literature showed that feed rate typically had the greatest influence on surface roughness, while cutting speed most influenced material removal rate. This study aims to use response surface methodology to optimize machining time and maximize material removal rate during turning of EN-31 alloy steel.
This document summarizes a study that used Taguchi methodology and Grey Relational Analysis to optimize machining parameters for CNC end milling of stainless steel 304. The goals were to minimize surface roughness (Ra) and maximize material removal rate (MRR). Experiments were conducted using an L9 orthogonal array to test cutting speed, feed rate, and depth of cut at three levels. Response data was normalized and Grey Relational Coefficients were calculated to determine the optimal parameter combination. The analysis found that a cutting speed of 75 m/min, feed rate of 0.15 mm/rev, and depth of cut of 1.5 mm provided the best results for achieving the combined objectives of lower Ra and higher MRR.
Experimental Analysis of Material Removal Rate in Drilling of 41Cr4 by a Tagu...IJERA Editor
In manufacturing industries the largest amount of money spent on drills. Therefore, from the viewpoint of cost and productivity, modeling and optimization of drilling processes parameter are extremely important for the manufacturing industry this paper presents a detailed model for drilling process parameter. The detailed structure includes in the model, are three parameters such as such as Spindle Speed, feed and depth of cut on material removal rate in drilling of 41 Cr 4 material using HSS spiral drill .We an effect of this three parameters on material removal rate .The detailed mathematical model is simulated by Minitab14 and simulation results fit experiment data very well In this investigation, an effective approach based on Taguchi method, analysis of variance (ANOVA), multivariable linear regression (MVLR), has been developed to determine the optimum conditions leading to higher MRR. Experiments were conducted by varying Spindle Speed, feed and depth of cut using L9 orthogonal array of Taguchi method. The present work aims at optimizing process parameters to achieve high MMR. Experimental results from the orthogonal array were used as the training data for the MVLR model to map the relationship between process parameters and MMR the experiment was conducted on drilling machine. From the investigation It concludes that speed is most influencing parameter followed by feed and depth of cut on MRR
Application of taguchi method in the optimization of boring parameters 2IAEME Publication
1. The document describes using the Taguchi method to optimize boring parameters, including cutting speed, feed rate, and depth of cut, to minimize surface roughness.
2. An experiment was conducted using an L27 orthogonal array with 3 factors at 3 levels each, for a total of 27 experiments. Signal-to-noise ratios and analysis of variance were used to analyze the results.
3. The experimental results revealed that depth of cut had the most significant effect on surface roughness, followed by feed rate and then cutting speed, within the specified test ranges. The optimal parameter settings were identified as cutting speed at level 2, feed rate at level 3, and depth of cut at level 1.
This document describes a study that uses ant colony optimization (ACO) to optimize cutting parameters during turning of EN31 alloy steel. The goal is to minimize surface roughness and maximize material removal rate by determining the optimal combination of cutting speed, feed rate, depth of cut, and nose radius of the cutting insert. Experimental data was collected and regression models were developed to relate the response characteristics (surface roughness and material removal rate) to the cutting parameters. The ACO algorithm was then used to find the cutting parameter values that provide the best tradeoff between the two response characteristics. The optimized parameters found by ACO were then validated through actual CNC turning experiments.
Experimental Investigation and Parametric Studies of Surface Roughness Analy...IJMER
The modern machining industries are focused on achieving high quality, in terms of part/component accuracy, surface finish, high production rate and increase in product life. Surface roughness of machined components has received serious attention of researchers for many years. It has
been an important design feature and quality measure in machining process. There are a large number of
parameters which affect the surface roughness. The typical controllable parameters for the CNC machines
include cutting tool variables, work piece material variables, cutting conditions etc. The desired output is
surface roughness, material removal rate, tool wear, etc. Optimization of machining parameters needs to
determine the most significant parameter for required output. Many techniques are used for optimization
of machining parameters including Taguchi, RSM and ANOVA approach to determine most significant
parameter. The present work is therefore in a direction to integrate effect of various parameters which affect
the surface roughness. This paper investigates the parameters affecting the surface roughness and / or
material removal rate with CNC turning process studied by researchers. It also discusses some other parameters such as cutting force and power consumption in different conditions
Optimization of Machining Parameters of 20MnCr5 Steel in Turning Operation u...IJMER
Now-a-days increasing the productivity and the quality of the machined parts are the main
challenges of metal cutting industry during turning processes. Optimization methods in turning
processes, considered being a vital role for continual improvement of output quality in product and
processes include modeling of input-output and in process parameters relationship and determination of
optimal cutting conditions. This paper present on Experimental study to optimize the effects of cutting
Parameters on Surface finish and MRR of 20MnCr5 Steel alloy work material by employing Taguchi
techniques. The orthogonal array, signal to noise ratio and analysis of variance were employed to study
the performance characteristics in turning operation. Five parameters were chosen as process variables:
Cutting Speed, Feed, Depth of cut, Hardness of cutting Tool, Cutting environment (wet and dry). The
experimentation plan is designed using Taguchi’s L9 Orthogonal Array (OA) and Minitab statistical
software is used. Optimal cutting parameters for minimum surface roughness (SR) and maximum material
removal rate were obtained. Finally, the relationship between factors and the performance measures
were developed by using multiple regression analysis
Process Parametric Optimization of CNC Vertical Milling Machine Using Taguchi...IOSR Journals
Abstract- An experiment was conducted to perform the parametric optimization of CNC end milling machine
tool in varying condition. The tool used for experiment was of Solid Carbide and the Mild Steel work piece was
used during experiment. The experiment has been taken place efficiently and completes its all objective of
optimization. The practical result can be used in industry to get the desirable Surface Roughness and Material
Removal Rate for the work piece by using suitable parameter combination.
Optimization of surface roughness in high speed end milling operation usingIAEME Publication
This document summarizes an investigation into optimizing surface roughness in high-speed end milling of Al-Si-Mg-Fe alloy workpieces using Taguchi's method. The study used an L9 orthogonal array to experiment with cutting speed, feed rate, and depth of cut. Surface roughness was measured and ANOVA was performed. Results showed depth of cut had the strongest influence on surface roughness, contributing over 73% of the variation, while cutting speed and feed rate also significantly impacted surface roughness. Surface roughness decreased with increasing cutting speed and increased with higher feed rates and depths of cut. Overall, Taguchi's method was able to optimize the machining parameters to minimize surface roughness.
Turning parameters optimization for surface roughness by taguchi methodIAEME Publication
This document summarizes a study that used the Taguchi method to optimize surface roughness in a turning operation of cast iron. Experiments were conducted using an L27 orthogonal array to investigate the effects of cutting speed, feed rate, and depth of cut on surface roughness. The results showed that cutting speed had the most significant effect on surface roughness, followed by feed rate and then depth of cut. Based on the analysis, the optimum cutting parameters to minimize surface roughness were determined to be a cutting speed of 1560 rpm, feed rate of 0.16 mm/rev, and depth of cut of 0.5 mm.
IRJET- Optimization of Machining Parameters for Turning on CNC Machine of Sta...IRJET Journal
This document discusses an experimental investigation into optimizing machining parameters for turning stainless steel 316 on a CNC machine. Taguchi methods were used to determine the optimal levels for cutting speed, feed rate, and depth of cut. Eighteen experiments were conducted using an L18 orthogonal array with different combinations of the parameters. The results found that depth of cut and feed rate significantly affected material removal rate and surface roughness, while cutting speed did not have a significant impact. Analysis of variance (ANOVA) identified depth of cut as the most influential factor. Optimization found the maximum material removal rate occurred at high cutting speeds, low feed rates, and high depth of cuts.
The document summarizes a study that used Taguchi methods and Grey Relational Analysis to optimize machining parameters (cutting speed, feed rate, depth of cut) for turning AISI H13 steel to maximize material removal rate and minimize surface roughness. Experiments were conducted based on an L18 orthogonal array design. Analysis of variance identified the significant parameters affecting each response. Optimal conditions for combined effects were found to be a cutting speed of 270m/min, feed rate of 0.1mm/rev, and depth of cut of 1.5mm, resulting in a surface roughness of 1.0828μm and material removal rate of 554.04mm3/sec.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Multi-Response Optimization of Aluminum alloy using GRA & PCA by employing Ta...IRJET Journal
This document summarizes a study that used multi-response optimization techniques including Grey Relational Analysis (GRA) and Principal Component Analysis (PCA) to optimize the machining parameters for end milling of an aluminum alloy. The goal was to provide better surface quality with optimal Material Removal Rate (MRR). Taguchi's design of experiments was used to design and conduct 27 experiments varying speed, depth of cut, and feed rate. GRA and PCA were then used to analyze the experimental data and determine the optimal machining parameter settings to achieve the desired surface roughness and MRR. The techniques effectively identified the optimal parameter combinations for end milling the aluminum alloy.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
IRJET- Parametric Study of CNC Turning Process Parameters for Surface Roughne...IRJET Journal
The document presents a study analyzing the effect of machining parameters on surface roughness in CNC turning processes. Experiments were conducted varying speed, feed rate, and depth of cut using stainless steel 304. Surface roughness values were measured and analyzed using analysis of variance, artificial neural networks, and genetic algorithms. The optimal machining parameters were determined that minimized surface roughness. Specifically, 27 experiments were conducted using a full factorial design, and surface roughness values were measured. The data was then analyzed using ANOVA, ANN, and GA models to understand the relationship between inputs and surface roughness, and identify the best settings.
A study of the effects of machining parameters on surface roughness using res...IAEME Publication
This document discusses a study on the effects of machining parameters on surface roughness in end milling of EN11 alloy steel. Experiments were conducted using an L18 orthogonal array to test combinations of four factors (depth of cut, feed rate, spindle speed, coolant type) at three levels each. Surface roughness was measured after each trial. Statistical analysis using ANOVA and response surface methodology was performed on the experimental data to develop a model relating the factors to surface roughness. The goal was to determine the optimal factor levels that minimize surface roughness.
This document presents a study that uses Taguchi design of experiments and regression analysis to optimize the machining parameters of cutting speed, feed rate, and depth of cut during CNC turning of EN-19 steel. The goal is to minimize surface roughness, feed force, and radial force. An orthogonal array experiment is designed using Taguchi's L9 array. Regression models are developed to predict the optimal settings, which are then verified with confirmation experiments. The Taguchi method aims to optimize the process parameters to obtain high quality products efficiently with minimal experimentation.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
A Review on Experimental Investigation of Machining Parameters during CNC Mac...IJERA Editor
This review paper aims towards the optimization of CNC turning operation when used over an OHNS material.
The lathe machine was chosen because of its widespread availability and its ability to perform various tasks
without much change in its structure. Also using lathe machines is very cheap and hence it is beneficial from
economic point of view as well. The turning operation was specifically chosen because of the various
advantages that it offers. It can be used for machining a large variety of materials and it is cheaper than milling.
OHNS (Oil Hardened Non Shrinking) tool was chosen due to its hardness. These materials are used only for
dies so it was chosen so that its industrial usage could be exploited. To comprehend the usage, all the input and
output parameters that could affect the machining process, namely input parameters like feed, cutting
conditions, speed, etc. and output parameters like surface roughness, surface finish, material removal rate were
analyzed using the researches that had already been done on CNC turning. After careful study of a variety of
research papers on this topic, it was decided that several input as well as the output parameters would be
considered which included feed, depth of cut and cutting speed were taken as the input parameters whereas
Material Removal Rate (MRR) and surface finish were taken as the output parameters. From the results of the
research papers, it was concluded that feed, depth of cut and cutting speed could be chosen as input parameters
whereas MRR and surface finish would be the output parameters
“Gray Relational Based Analysis of Al-6351”iosrjce
IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of mechanical and civil engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in mechanical and civil engineering. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
IRJET- Research Review on Multi-Objective Optimization of Machining Parameter...IRJET Journal
This document reviews research on optimizing machining parameters for turning operations using response surface methodology. It discusses previous studies that investigated factors like cutting speed, feed rate, depth of cut, nose radius, and how they affect responses such as surface roughness, material removal rate, forces, tool life. Most research found feed rate and depth of cut to be most significant for surface roughness, while cutting speed was important for material removal rate and forces. The document concludes that further research is needed to optimize multiple responses simultaneously to improve productivity and reduce costs.
Investigations of machining parameters on surface roughness in cnc milling u...Alexander Decker
This document summarizes a study that investigated the effect of machining parameters on surface roughness in CNC milling of H-13 die steel using the Taguchi technique. The parameters examined were spindle speed, feed rate, and depth of cut. Experiments were conducted using an L9 orthogonal array. Surface roughness measurements showed that lower feed rates, higher spindle speeds, and greater depths of cut produced lower surface roughness values. Analysis of variance identified feed rate as the most influential parameter on surface roughness. The optimized parameters determined were a low feed rate of 0.08 mm/tooth, high spindle speed of 358.8 RPM, and high depth of cut of 0.3 mm.
Experimental Investigation and Parametric Studies of Surface Roughness Analys...IJMER
The modern machining industries are focused on achieving high quality, in terms of
part/component accuracy, surface finish, high production rate and increase in product life. Surface
roughness of machined components has received serious attention of researchers for many years. It has
been an important design feature and quality measure in machining process. There are a large number of
parameters which affect the surface roughness. The typical controllable parameters for the CNC machines
include cutting tool variables, work piece material variables, cutting conditions etc. The desired output is
surface roughness, material removal rate, tool wear, etc. Optimization of machining parameters needs to
determine the most significant parameter for required output. Many techniques are used for optimization
of machining parameters including Taguchi, RSM and ANOVA approach to determine most significant
parameter.
The present work is therefore in a direction to integrate effect of various parameters which affect
the surface roughness. This paper investigates the parameters affecting the surface roughness and / or
material removal rate with CNC turning process studied by researchers. It also discusses some other
parameters such as cutting force and power consumption in different conditions.
IRJET- Analysis of Cutting Process Parameter During Turning of EN 31 for Mini...IRJET Journal
This document analyzes cutting process parameters to minimize surface roughness during turning of EN 31 steel. Experiments were conducted using a Taguchi design of experiments with cutting speed, feed rate, and tool nose radius as parameters. Measurements showed feed rate had the greatest influence on surface roughness, followed by nose radius. The optimal combination for minimum roughness was a feed rate of 0.025 mm/rev, nose radius of 0.8 mm, and cutting speed of 210 m/min.
This document describes a study that uses ant colony optimization (ACO) to optimize cutting parameters during turning of EN31 alloy steel. The goal is to minimize surface roughness and maximize material removal rate by determining the optimal combination of cutting speed, feed rate, depth of cut, and nose radius of the cutting insert. Experimental data was collected and regression models were developed to relate the response characteristics (surface roughness and material removal rate) to the cutting parameters. The ACO algorithm was then used to find the cutting parameter values that provide the best tradeoff between the two response characteristics. The optimized parameters found by ACO were then validated through actual CNC turning experiments.
Experimental Investigation and Parametric Studies of Surface Roughness Analy...IJMER
The modern machining industries are focused on achieving high quality, in terms of part/component accuracy, surface finish, high production rate and increase in product life. Surface roughness of machined components has received serious attention of researchers for many years. It has
been an important design feature and quality measure in machining process. There are a large number of
parameters which affect the surface roughness. The typical controllable parameters for the CNC machines
include cutting tool variables, work piece material variables, cutting conditions etc. The desired output is
surface roughness, material removal rate, tool wear, etc. Optimization of machining parameters needs to
determine the most significant parameter for required output. Many techniques are used for optimization
of machining parameters including Taguchi, RSM and ANOVA approach to determine most significant
parameter. The present work is therefore in a direction to integrate effect of various parameters which affect
the surface roughness. This paper investigates the parameters affecting the surface roughness and / or
material removal rate with CNC turning process studied by researchers. It also discusses some other parameters such as cutting force and power consumption in different conditions
Optimization of Machining Parameters of 20MnCr5 Steel in Turning Operation u...IJMER
Now-a-days increasing the productivity and the quality of the machined parts are the main
challenges of metal cutting industry during turning processes. Optimization methods in turning
processes, considered being a vital role for continual improvement of output quality in product and
processes include modeling of input-output and in process parameters relationship and determination of
optimal cutting conditions. This paper present on Experimental study to optimize the effects of cutting
Parameters on Surface finish and MRR of 20MnCr5 Steel alloy work material by employing Taguchi
techniques. The orthogonal array, signal to noise ratio and analysis of variance were employed to study
the performance characteristics in turning operation. Five parameters were chosen as process variables:
Cutting Speed, Feed, Depth of cut, Hardness of cutting Tool, Cutting environment (wet and dry). The
experimentation plan is designed using Taguchi’s L9 Orthogonal Array (OA) and Minitab statistical
software is used. Optimal cutting parameters for minimum surface roughness (SR) and maximum material
removal rate were obtained. Finally, the relationship between factors and the performance measures
were developed by using multiple regression analysis
Process Parametric Optimization of CNC Vertical Milling Machine Using Taguchi...IOSR Journals
Abstract- An experiment was conducted to perform the parametric optimization of CNC end milling machine
tool in varying condition. The tool used for experiment was of Solid Carbide and the Mild Steel work piece was
used during experiment. The experiment has been taken place efficiently and completes its all objective of
optimization. The practical result can be used in industry to get the desirable Surface Roughness and Material
Removal Rate for the work piece by using suitable parameter combination.
Optimization of surface roughness in high speed end milling operation usingIAEME Publication
This document summarizes an investigation into optimizing surface roughness in high-speed end milling of Al-Si-Mg-Fe alloy workpieces using Taguchi's method. The study used an L9 orthogonal array to experiment with cutting speed, feed rate, and depth of cut. Surface roughness was measured and ANOVA was performed. Results showed depth of cut had the strongest influence on surface roughness, contributing over 73% of the variation, while cutting speed and feed rate also significantly impacted surface roughness. Surface roughness decreased with increasing cutting speed and increased with higher feed rates and depths of cut. Overall, Taguchi's method was able to optimize the machining parameters to minimize surface roughness.
Turning parameters optimization for surface roughness by taguchi methodIAEME Publication
This document summarizes a study that used the Taguchi method to optimize surface roughness in a turning operation of cast iron. Experiments were conducted using an L27 orthogonal array to investigate the effects of cutting speed, feed rate, and depth of cut on surface roughness. The results showed that cutting speed had the most significant effect on surface roughness, followed by feed rate and then depth of cut. Based on the analysis, the optimum cutting parameters to minimize surface roughness were determined to be a cutting speed of 1560 rpm, feed rate of 0.16 mm/rev, and depth of cut of 0.5 mm.
IRJET- Optimization of Machining Parameters for Turning on CNC Machine of Sta...IRJET Journal
This document discusses an experimental investigation into optimizing machining parameters for turning stainless steel 316 on a CNC machine. Taguchi methods were used to determine the optimal levels for cutting speed, feed rate, and depth of cut. Eighteen experiments were conducted using an L18 orthogonal array with different combinations of the parameters. The results found that depth of cut and feed rate significantly affected material removal rate and surface roughness, while cutting speed did not have a significant impact. Analysis of variance (ANOVA) identified depth of cut as the most influential factor. Optimization found the maximum material removal rate occurred at high cutting speeds, low feed rates, and high depth of cuts.
The document summarizes a study that used Taguchi methods and Grey Relational Analysis to optimize machining parameters (cutting speed, feed rate, depth of cut) for turning AISI H13 steel to maximize material removal rate and minimize surface roughness. Experiments were conducted based on an L18 orthogonal array design. Analysis of variance identified the significant parameters affecting each response. Optimal conditions for combined effects were found to be a cutting speed of 270m/min, feed rate of 0.1mm/rev, and depth of cut of 1.5mm, resulting in a surface roughness of 1.0828μm and material removal rate of 554.04mm3/sec.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Multi-Response Optimization of Aluminum alloy using GRA & PCA by employing Ta...IRJET Journal
This document summarizes a study that used multi-response optimization techniques including Grey Relational Analysis (GRA) and Principal Component Analysis (PCA) to optimize the machining parameters for end milling of an aluminum alloy. The goal was to provide better surface quality with optimal Material Removal Rate (MRR). Taguchi's design of experiments was used to design and conduct 27 experiments varying speed, depth of cut, and feed rate. GRA and PCA were then used to analyze the experimental data and determine the optimal machining parameter settings to achieve the desired surface roughness and MRR. The techniques effectively identified the optimal parameter combinations for end milling the aluminum alloy.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
IRJET- Parametric Study of CNC Turning Process Parameters for Surface Roughne...IRJET Journal
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parameter.
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IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
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International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
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Surface roughness an indicator of surface quality is
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Optimization of Thrust Force and Material Removal Rate in Turning EN-16 Steel Alloy using Taguchi Approach
1. International Journal of Advanced Engineering Research and Applications
ISSN (online): 2454-2377
Vol. – 1, Issue – 1
May – 2015
www.ijaera.org
1
Optimization of Thrust Force and Material Removal Rate in Turning EN-16
Steel Alloy using Taguchi Approach
Vijay Kumar
M. Tech. Scholar, Department of Mechanical Engineering
University Institute of Engineering & Technology, Kurukshetra
Kurukshetra University, Kurukshetra - 136119, INDIA
E-mail: vijaybaberwal@gmail.com
Abstract: The selection of optimal cutting parameters in turning operation is very important to
achieve high cutting performance. This paper deals with the optimization of performance
characteristics of turning EN-16 steel alloy using tungsten carbide inserts by Taguchi approach. The
experiments were performed on the basis of an L-18 orthogonal array given by Taguchi’s parameter
design approach. The performance characteristics such as thrust force and Material Removal Rate
(MRR) are optimized with the optimal combination of cutting parameters such as nose radius,
cutting speed, feed rate and depth of cut. Analysis of variance (ANOVA) is applied to identify the
most significant factor using MINITAB-16 software. The cutting parameters are varied to observe
the effects on performance characteristics and find the optimal results. Finally, confirmation tests are
performed to verify the experimental results. The results from the confirmation tests proved that the
performance characteristics such as thrust force and MRR are improved simultaneously through
optimal combination of process parameters obtained from Taguchi approach.
Keywords: EN-16 steel alloy, cutting parameters, turning, thrust force and material removal rate,
taguchi approach
I. INTRODUCTION
In today‘s competative marketplace, the manufacturing industries are continuously challenged
for achieving higher productivity and qualitative of products. The required size and shape of ferrous
materials are conventionally produced by turning the blanks with the help of cutting tools that moved
past the workpiece in a machine tool. Machine tool technology is often labeled as “Mother
technology” in view of the fact that it provides essential tools that generate production in almost all
sectors of economy. Higher material removal rate (MRR) and lower the cutting forces are the needs of
industry to cope up with the mass production (without compromising with quality of products) in
shorter time. Higher MRR can be achieved by increasing the process parameters such as cutting
speed, feed rate, depth of cut and nose radius. In a turning operation, it is important to select cutting
parameters so that high cutting performance can be achieved. Selection of desired cutting parameters
by experience or using handbook does not ensure that the selected cutting parameters are optimal for a
particular machine and environment. The effect of cutting parameters is reflected on surface
roughness, surface texture and dimensional deviations of the product. For optimization of turning
operations, it is desired to determine the cutting parameter more efficiently [1,10]. In order to achieve
the objective of this research, a literature review was conducted. Various contributions are discussed
here. Thamizhmanii et al [2] analyzed the surface roughness in turning process using Taguchi method.
The study was focused on the determination of optimum condition to get best surface roughness in
2. International Journal of Advanced Engineering Research and Applications
(IJAERA)
Vol. – 1, Issue – 1
May –2015
www.ijaera.org 2
turning SCM 440 alloy steel. Aggarwal [3] present the findings of an experimental investigation into
the effects of cutting speed, feed rate, and depth of cut, nose radius and cutting environment in CNC
turning of AISI P-20 tool steel. Gopalsamy et al [4] investigating the application of Taguchi method
for parametric optimization of hard machining while machining hardened steel using L18 orthogonal
array was used to design the experiments (machining parameters: cutting speed, feed, depth of cut,
length of cut) with consideration of surface finish and tool life as response variable. Jaswin and
Mohan Lal [5] investigated the optimization of deep cryogenic treatment for EN 52 valve steel using
Taguchi method in combination with Grey relational analysis. The factors considered for the
optimization are the cooling rate, soaking temperature, soaking period and tempering temperature,
each at three different levels. Babu et al [6] studied that amongst the most critical quality measures
that define the product quality surface roughness plays a vital role. This study has attempted in
developing an empirical second order model for the predicting the surface roughness in machining
EN24 alloy steel using RSM. Abhang and Hameedullah [7] optimized the multi-criteria problems
because it is a great need of producers to produce precision parts with low costs. Optimization of
multi-performance characteristics is more complex compared to optimization of single-performance
characteristics. Rajyalakshmi [8] addressed an effective approach, Taguchi grey relational analysis,
has been applied to experimental results of WEDM on Inconel 825 with consideration of multiple
response measures. Saraswat [9] studied that the main objective of today's manufacturing industries is
to produce low cost, high quality products in short time. The selection of optimal cutting parameters is
a very important issue for every machining process in order to enhance the quality of machining
products and reduce the machining costs. The performance characteristics in turning operation have
been optimized for various work materials like EN-31, EN-24, EN-8, AISI P20 steel and some super
alloys. An attempt is made to optimize the thrust force and material removal rate in turning EN-16
steel alloy using Taguchi approach.
II. EXPERMINTAL DETAILS
A. Experimental Conditions and Planning of Experiment
The experiments are performed, on the basis of L18 standard orthogonal array design with
four process parameters namely nose radius, cutting speed, feed rate and depth of cut for two
performance characteristics (thrust force and MRR). The experimental conditions on which the
experiments are performed are given in table 1.
Table 1: Experimental conditions
Work piece EN- 16 Steel alloy
Workpiece
Composition
C= 0.30-0.40%, Si=0.10-0.35%,Mn=1.30-1.80% , Mo=0.20-0.35%, S=0.05%,
P=0.05%
Environment Wet Cutting
Size (mm) Diameter = 26 mm and length =600 mm
Machine Tool HMT Lathe Machine
In cutting parameter design, two levels of nose radius and three levels of other cutting
parameters such as spindle speed, feed rate and depth of cut are selected. The process parameters and
their levels are shown in table 2. All the factors are represented in the table 3.
3. International Journal of Advanced Engineering Research and Applications
(IJAERA)
Vol. – 1, Issue – 1
May –2015
www.ijaera.org 3
Table 2: Process parameters and levels
Level Nose Radius (A),
mm
Cutting Speed
(B), rpm
Feed Rate
(C),mm/rev
Depth of Cut
(D),mm
1 0.2 420 0.04 0.3
2 0.4 490 0.08 0.5
3 ------- 540 0.12 0.7
Table 3: Representation of factors
Factor Nose Radius Spindle Speed Feed Rate Depth of Cut
Level 1 A1 B1 C1 1
Level 2 A2 B2 C2 2
Level 3 --- B3 C3 3
B. Selection of Orthogonal Array
Taguchi’s design of experiments (DOE) methodology is used to plan the experiments
statistically. To select an appropriate orthogonal array for the experiments, the total degrees of
freedom need to be computed. In the present work, the nose radius has two levels of experiments so it
has 1 degree of freedom (DOF) where as the other parameters have three levels so they have 2 DOF.
Therefore, total degree of freedom = (1×1) + (3×2) = 7. Once the required degrees of freedom are
known, the next step is to select an appropriate orthogonal array to fit specific task. In this study, an
L18 orthogonal array with five columns and nineteen rows is used. The array has seventeen degrees of
freedom and it can handle three level design parameters. Each cutting parameter is assigned to a
column, eighteen cutting parameter combinations being available. The experimental layout for the
four cutting parameters using the L18 orthogonal array is shown in table 4 as:
Table 4: Basic Taguchi's l18 orthogonal array
S. No. Nose Radius (A),
mm
Cutting Speed (B),
m/min
Feed Rate(C),
mm/rev.
Depth of Cut (D),
mm
1 1 1 1 1
2 1 1 2 2
3 1 1 3 3
4 1 2 1 1
5 1 2 2 2
6 1 2 3 3
7 1 3 1 2
8 1 3 2 3
9 1 3 3 1
10 2 1 1 3
11 2 1 2 1
12 2 1 3 2
13 2 2 1 2
14 2 2 2 3
15 2 2 3 1
16 2 3 1 3
17 2 3 2 1
18 2 3 3 2
4. International Journal of Advanced Engineering Research and Applications
(IJAERA)
Vol. – 1, Issue – 1
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III. EXPERIMENTAL RESULTS
A. Thrust Force
After performing turning EN-16 steel alloy on lathe machine, the results are obtained for thrust
force and material removal rate. A total (18×3) = 54 experiments are performed on lathe machine.
Each experiment is performed thrice to obtain the mean values of response variables. Table 5 shows
three readings R1, R2, R3 and mean value of thrust force for eighteen runs.
Table 5: Experimental results for thrust force
Exp. No. Thrust force (kg) Mean value (kg)
Reading1 Reading2 Reading3
1 6 8 7 7
2 13 15 11 13
3 28 24 26 26
4 4 6 5 5
5 11 13 9 11
6 29 27 25 27
7 14 10 12 12
8 21 18 24 21
9 13 12 11 12
10 14 18 16 16
11 13 12 11 12
12 19 18 20 19
13 15 13 11 13
14 19 25 22 22
15 15 17 13 15
16 13 11 15 13
17 9 8 10 9
18 13 15 14 14
The mean values are used in MINITAB-16 to observe the effects of process parameter (nose
radius, cutting speed, feed rate and depth of cut) on response variables such as thrust force and MRR.
21
20.0
17.5
15.0
12.5
10.0
321
321
20.0
17.5
15.0
12.5
10.0
321
A
MeanofMeans
B
C D
Main Effects Plot for Means
Data Means
Figure 2: Effect of process parameters on Thrust force (smaller the better)
5. International Journal of Advanced Engineering Research and Applications
(IJAERA)
Vol. – 1, Issue – 1
May –2015
www.ijaera.org 5
Table 6: Response table of means for thrust force
Level Nose radius (A) Cutting speed (B) Feed rate (C) Depth of cut (D)
1 14.89 15.50 11.00 10.00
2 14.78 15.50 14.67 13.67
3 --- 13.50 18.83 20.83
Delta 0.11 2.00 7.83 10.83
Rank 4 3 2 1
Figure 2 and table 6 show the effect of process parameters on the thrust force at different levels and it
can be noticed that:
a) There is negligible change in thrust force, when nose radius changes from level 1 to 2.
b) Thrust force is constant when cutting speed changes from level 1 to 2. But significantly
decreases, when speed changes from level 2 to 3.
c) As the feed rate and depth of cut increases from level 1 to 3, thrust force also increases
significantly.
Table 7: ANOVA result for thrust force (raw data)
Source DF Seq. SS Adj. SS Adj.MS F P % contribution
Nose radius 1 0.17 0.17 0.17 0.03 0.87 0.008
Cutting
speed
2 48.00 48.00 24.00 3.74 0.031 2.41
Feed rate 2 553.00 553.00 276.50 43.07 0.000 27.79
Depth of
cut
2 1093.00 1093.00 546.50 85.12 0.000 54.94
Error 46 295.33 295.33 6.42
Total 53 1989.50
Order of significance: 1. Depth of cut 2. Feed rate 3. Cutting speed
DF= degree of freedom; SS= sum of squares; MS= mean squares (variance); F= ratio of variance to variance error
Table 7 gives the significant variables. In table 7, the value of P indicates the significant or
insignificant variables. If the value of P is less than 0.05 or near about 0.05, means the variable is
significant otherwise insignificant. It is clear from the ANOVA table that depth of cut is the most
significant parameter for thrust force. Among the four process parameters, depth of cut is the largest
i.e. the contribution of depth of cut is 54.94% so it is highly significant factor. The contribution of
feed rate is 27.79 % so it is less significant factor as compare to depth of cut. The contribution of
cutting speed and nose radius are 2.41 and 0.008% so they are less significant factor as compared to
depth of cut and feed rate.
B. Material Removal Rate
Table 8: Experimental results for MRR
Exp. No.
MRR (g/sec.) Mean value
(g/sec.)Reading1 Reading2 Reading3
1 2.656 2.000 3.343 2.666
2 2.676 3.383 2.000 2.686
3 5.373 4.687 4.042 4.704
4 1.697 2.020 2.383 2.033
5 4.687 4.043 3.387 4.042
6 3.000 3.669 4.833 3.834
7 2.021 3.383 2.650 2.685
Table Continue on Next Page………
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8 4.041 4.669 4.388 4.366
9 1.689 3.039 2.633 2.454
10 4.031 4.363 5.647 4.680
11 1.387 2.104 2.467 1.986
12 4.063 2.667 3.443 3.391
13 4.567 3.283 4.123 3.991
14 4.669 4.073 5.123 4.622
15 1.707 2.860 2.000 2.189
16 4.000 2.767 3.533 3.433
17 2.403 2.707 2.037 2.382
18 4.051 2.680 3.412 3.381
Table 9: Response table for means for MRR
Figure 3 and table 9 shows the effects of process parameters on the MRR and it can be noticed
that depth of cut is the main influencing process factor for MRR. MRR increases as the depth of cut
increases from level 1 to 3. From the ANOVA table 10 it is clear that D3 is the optimal parameter
setting for the MRR. The contribution of depth of cut is 59.12% so; it is most significant factor than
nose radius, cutting speed and feed rate.
Table 10: ANOVA result for MRR (raw data)
21
4.0
3.5
3.0
2.5
2.0
321
321
4.0
3.5
3.0
2.5
2.0
321
A
MeanofMeans
B
C D
Main Effects Plot for Means
Data Means
Figure 3: Effect of process parameters on material removal rate (larger the better)
Level Nose radius Cutting speed Feed rate Depth of cut
1 3.275 3.352 3.248 2.285
2 3.340 3.452 3.347 3.363
3 --- 3.117 3.325 4.273
Delta 0.065 0.335 0.099 1.988
Rank 4 2 3 1
Source DF Seq. SS Adj. SS Adj.MS F P % contribution
Nose Radius 1 0.570 0.570 0.570 0.11 0.739 0.95
Cutting speed 2 1.0658 1.0658 0.5329 1.05 0.360 1.77
Feed rate 2 0.0979 0.0979 0.0489 0.10 0.909 0.16
Depth of cut 2 35.6571 35.6571 17.8285 35.00 0.000 59.12
Error 46 23.4349 23.4349 0.5095
Total 53 60.313
Order of significance: 1. Depth of cut.
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C. Prediction of mean and confidence interval
Prediction of mean and confidence interval are two methods for finding out the optimal
results. The estimate of the mean (µ) is only a point estimate based on the average of results obtains
from the experiment. In other words, the confidence interval (CI) is a maximum and minimum value
between which the true average should fall at some stated percentage of confidence. The Taguchi
approach for predicting the mean performance characteristics and determination of confidence
interval for the predicted mean has been applied. For the optimum value of various parameters the
predicted value is always greater than the value of confidence interval. Prediction of mean for Thrust
force (µTF): The optimum combination of process parameters for thrust force is B3 C1 D1
Hence,
µTF = TF + (B3-TF) + (C1-TF) + (D1-TF)
µTF = Prediction of mean
TF = 14.833; average value of thrust force
B3 C1 D1 is the value of different input parameters at which thrust force is optimum.
µTF = 4.834
Now, calculate the confidence interval:
C.I. = √ (Fa(1,fe)Ve⌈1/neff+1/R⌉ )
Where Fa (1, fe) = 4.0157; the F ratio at a confidence level of degree of freedom 1 and its value is
constant
Ve = 6.42; an error in the ANOVA table in (adjMS) column (variance error)
neff = N / (1+total degree of freedom associated in the estimate of mean) = 54/(1+7)= 6.75
N = 54; total no. of results
R = 3; total no. of repetition
C.I. = 3.52
The confidence interval of the predicted optimal thrust force is:
[µTF – CI] < µTF < [µTF + CI]
[4.834 – 3.52] < µTF < [4.834 + 3.52]
1.314 < µTF (kg) < 8.354
Prediction of mean for MRR (µTmrr):
The optimum combination of various parameters for mrr is D3
Hence, µTmrr = Tmrr + (D3-Tmrr) µTmrr = 4.273
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Now, calculate the confidence interval: C.I. = .9922
The confidence interval of the predicted optimal material removal rate (mrr) is:
[µTmrr – CI] < µTmrr < [µTmrr + CI]
[4.273 – 0.9922] < µRF < [4.273 + 0.9922]
3.281 < µTmrr < 5.265
In case of MRR, variation of nose radius and feed rate do not affect the material removal rate.
Only depth of cut plays a significant role in case of material removal rate in turning EN-16 alloy steel.
Hence, the value of CI is less than predicted mean so, the optimum values are right.
IV. CONFIRMATION EXPERIMENTS
This investigation recommends the optimal level of parameters on which three confirmations
experiment have been performed. The actual mean value of all response variables lies between the
confidence interval of the predicted mean value of response variables respectively as shown in table
11. Therefore, the performance characteristics in turning EN-16 steel alloy can be improved by given
below optimal setting of process parameters.
Table 11: Conformation experiments
Response Optimum value setting Predicted mean value Actual mean value
Thrust force A2B3C1D1 4.834 5.347
MRR A2B2C2D3 4.273 4.667
V. CONCLUSIONS
The following conclusions can be drawn based on the experimental results of this study:
a) It is found that the parameter design of the Taguchi method provides a simple, systematic and
efficient methodology for the optimization of the machining parameters.
b) Feed rate and depth of cut are the main parameters among the four controllable factors (nose
radius, cutting speed, feed rate and depth of cut) that influence the thrust force significantly in
turning EN-16 steel alloy. Also from ANOVA, B3C1D1 are the optimal parameter setting for
thrust force.
c) Depth of cut at level 3, D3 i.e. (0.7) is recommended to obtain the maximum MRR.
VI. REFERENCES
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edition, McGraw-Hill.
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[3] Aggarwal, A., Singh, H., Kumar, P., & Singh, M. (2008). Optimizing power consumption for CNC
turned parts using response surface methodology and Taguchi's technique—a comparative analysis.
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[4] Gopalsamy, B. M., Mondal, B., & Ghosh, S. (2009). Taguchi method and ANOVA: An approach for
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