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
EXPERIMENTAL STUDY OF TURNING OPERATION AND OPTIMIZATION OF MRR AND SURFACE R...AM Publications
In this research work turning operation is performed on AISI 1020 mild steel. Here we conducted experiments by taking Cutting Speed, Feed Rate & Depth of cut as process parameters and got the optimized value of MRR & SR. An L9 orthogonal array, the signal-to-noise (S/N) ratio are employed to the study the performance characteristics in the turning using WNMG332RP carbide insert with a nose radius of 0.8mm. Taguchi method is used to optimize surface roughness and material removal rate (MRR) during machining operation on CNC turning. The experimental result shows that on increasing depth of cut and feed the combined S/N ratio increases while on increasing cutting speed the combined S/N ratio decreases. It results that cutting speed is most significantly influences the Surface roughness followed by feed and in case of MRR, depth of cut is the most significant parameter followed by cutting speed .While the combination of both is most significantly affected by the depth of cut followed by the feed.
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
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
EXPERIMENTAL STUDY OF TURNING OPERATION AND OPTIMIZATION OF MRR AND SURFACE R...AM Publications
In this research work turning operation is performed on AISI 1020 mild steel. Here we conducted experiments by taking Cutting Speed, Feed Rate & Depth of cut as process parameters and got the optimized value of MRR & SR. An L9 orthogonal array, the signal-to-noise (S/N) ratio are employed to the study the performance characteristics in the turning using WNMG332RP carbide insert with a nose radius of 0.8mm. Taguchi method is used to optimize surface roughness and material removal rate (MRR) during machining operation on CNC turning. The experimental result shows that on increasing depth of cut and feed the combined S/N ratio increases while on increasing cutting speed the combined S/N ratio decreases. It results that cutting speed is most significantly influences the Surface roughness followed by feed and in case of MRR, depth of cut is the most significant parameter followed by cutting speed .While the combination of both is most significantly affected by the depth of cut followed by the feed.
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
Artificial Neural Network Modeling and Analysis of EN24 &EN36 Using CNC Milli...ijiert bestjournal
Metal cutting is one of the most significant manufa cturing processes in the area of material removal. It is Block it is defined metal cutting as the removal of metal chips from a work piece in order to obtain a finished product with de sired attributes of size,shape,and surface roughness.The imperative objective of the science o f metal cutting is the solution of practical problems associated with the efficient and precise removal of metal from work piece. It has been recognized that the reliable quantitative pred ictions of the various technological performance measures,preferably in the form of equ ations,are essential to develop optimization strategies for selecting cutting condi tions in process planning. In this thesis experiments has to be conducted to improve the surf ace finish quality of a work piece by using carbide tips. The type is bull nose tip. A se ries of experiments have to be done by varying the milling parameters spindle speed,feed rate and depth of cut and modeling is done by ANN. and Analysis is done by ANSYS.
INFLUENCE OF PROCESS PARAMETERS ON SURFACE ROUGHNESS AND MATERIAL REMOVAL RAT...ijmech
Optimization of machining parameters is very valuable to maintain the accuracy of the components and
obtain cost effective Machining.MRR (material removal rate) and surface roughness is playing primary
role in manufacturing using contemporary CNC (computer numerical controlled) machines, in the case of
mass manufacturing. In present study experimental and work is done for optimization of process
parameters. In experimental work total 32 experiments are designed according DOE method “Mixed
taguchi”. Three factors are selected for experimental work. Depth of cut, speed and feed rate is selected
factors for experimental work. All experiments are carried out in CIPET, Jaipur. Two responses are find
out in this work and are following: first one is material removal rate (MRR) and second response is surface
roughness (Ra) measurement. An artificial neural network is ‘Feed Forward Back Propagation’ type
model of developing the analysis and prediction of surface roughness and MRR with relationship between
all input process parameters
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.
Optimization and Process Parameters of CNC End Milling For Aluminum Alloy 6082 ijiert bestjournal
he study aims at optimization of cutting parameters in CNC End milling of Aluminum Alloy 6082. CNC milling is a versatile and most widely used operation in present industry. Sur face quality affects fatigue life of components and influences various mechanical properties and has receive d serious attention for many years. In this work,experiments are conducted to analyze the surface roughnes s using various machining parameters such as Spindle speed,feed rate and depth of cut . The data was used to devel op surface roughness prediction models as a function of the machining parameters. In the present study,CNC machining centre with Cemented carbide end mill of 25mm diameter and 30� helix angle was used. A multiple regression analysis is used to correlate the relationship between the machining parameters and surface roughnes s. RS methodology was selected to optimize the surface roughness resulting minimum values of surface roughness and their r espective optimal conditions. Key words:CNC end milling,Aluminum alloy 6082,Taguchi,ANOVA
EXPERIMENTAL INVESTIGATION OF PCM USING RESPONSE SURFACE METHODOLOGY ON SS316...IAEME Publication
Photochemical machining (PCM) is the non-conventional machining processes which produce burr free & stress free flat complex metal components. In the present work optimization of process parameters for Photo chemical machining of SS316L by using response surface methodology. Mathematical models have been developed to study the effect of input parameters on Undercut from the results of the experiments. The different input parameters such as time, concentration and temperature were set during the photochemical machining. Design of Experiment was done by centre composite design method by having 20 experiments to see the effect on etching of SS316L. Minimum Undercut was observed at the etching temperature 63.99, etchant concentration 769.69 gm/lit and 46.96 min etching time. The optimum material undercut was found 0.0815 mm.
Experimental Investigation and Analysis of Torque in Drilling Hybrid Metal Ma...IJMERJOURNAL
ABSTRACT :This paper presents an experimental investigation on torque in drilling of aluminium hybrid metal matrix composite the machining parameters used here was speed, feed, drill diameter of the drill bits for 3 levels. The optimized response parameter of aluminium hybrid composite found by Taguchi L27 orthogonal array experimentation. This hybrid metal matrix composite is fabricated using 50 micron sized Silicon Carbide and graphite particles are reinforced into aluminium matrix material via stir casting process. The torque is considered as experimental result and it is predicted using fuzzy logic. The results specify that the predicted torque values
Artificial Neural Network Modeling and Analysis of EN24 &EN36 Using CNC Milli...ijiert bestjournal
Metal cutting is one of the most significant manufa cturing processes in the area of material removal. It is Block it is defined metal cutting as the removal of metal chips from a work piece in order to obtain a finished product with de sired attributes of size,shape,and surface roughness.The imperative objective of the science o f metal cutting is the solution of practical problems associated with the efficient and precise removal of metal from work piece. It has been recognized that the reliable quantitative pred ictions of the various technological performance measures,preferably in the form of equ ations,are essential to develop optimization strategies for selecting cutting condi tions in process planning. In this thesis experiments has to be conducted to improve the surf ace finish quality of a work piece by using carbide tips. The type is bull nose tip. A se ries of experiments have to be done by varying the milling parameters spindle speed,feed rate and depth of cut and modeling is done by ANN. and Analysis is done by ANSYS.
INFLUENCE OF PROCESS PARAMETERS ON SURFACE ROUGHNESS AND MATERIAL REMOVAL RAT...ijmech
Optimization of machining parameters is very valuable to maintain the accuracy of the components and
obtain cost effective Machining.MRR (material removal rate) and surface roughness is playing primary
role in manufacturing using contemporary CNC (computer numerical controlled) machines, in the case of
mass manufacturing. In present study experimental and work is done for optimization of process
parameters. In experimental work total 32 experiments are designed according DOE method “Mixed
taguchi”. Three factors are selected for experimental work. Depth of cut, speed and feed rate is selected
factors for experimental work. All experiments are carried out in CIPET, Jaipur. Two responses are find
out in this work and are following: first one is material removal rate (MRR) and second response is surface
roughness (Ra) measurement. An artificial neural network is ‘Feed Forward Back Propagation’ type
model of developing the analysis and prediction of surface roughness and MRR with relationship between
all input process parameters
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.
Optimization and Process Parameters of CNC End Milling For Aluminum Alloy 6082 ijiert bestjournal
he study aims at optimization of cutting parameters in CNC End milling of Aluminum Alloy 6082. CNC milling is a versatile and most widely used operation in present industry. Sur face quality affects fatigue life of components and influences various mechanical properties and has receive d serious attention for many years. In this work,experiments are conducted to analyze the surface roughnes s using various machining parameters such as Spindle speed,feed rate and depth of cut . The data was used to devel op surface roughness prediction models as a function of the machining parameters. In the present study,CNC machining centre with Cemented carbide end mill of 25mm diameter and 30� helix angle was used. A multiple regression analysis is used to correlate the relationship between the machining parameters and surface roughnes s. RS methodology was selected to optimize the surface roughness resulting minimum values of surface roughness and their r espective optimal conditions. Key words:CNC end milling,Aluminum alloy 6082,Taguchi,ANOVA
EXPERIMENTAL INVESTIGATION OF PCM USING RESPONSE SURFACE METHODOLOGY ON SS316...IAEME Publication
Photochemical machining (PCM) is the non-conventional machining processes which produce burr free & stress free flat complex metal components. In the present work optimization of process parameters for Photo chemical machining of SS316L by using response surface methodology. Mathematical models have been developed to study the effect of input parameters on Undercut from the results of the experiments. The different input parameters such as time, concentration and temperature were set during the photochemical machining. Design of Experiment was done by centre composite design method by having 20 experiments to see the effect on etching of SS316L. Minimum Undercut was observed at the etching temperature 63.99, etchant concentration 769.69 gm/lit and 46.96 min etching time. The optimum material undercut was found 0.0815 mm.
Experimental Investigation and Analysis of Torque in Drilling Hybrid Metal Ma...IJMERJOURNAL
ABSTRACT :This paper presents an experimental investigation on torque in drilling of aluminium hybrid metal matrix composite the machining parameters used here was speed, feed, drill diameter of the drill bits for 3 levels. The optimized response parameter of aluminium hybrid composite found by Taguchi L27 orthogonal array experimentation. This hybrid metal matrix composite is fabricated using 50 micron sized Silicon Carbide and graphite particles are reinforced into aluminium matrix material via stir casting process. The torque is considered as experimental result and it is predicted using fuzzy logic. The results specify that the predicted torque values
IOSR Journal of Pharmacy and Biological Sciences(IOSR-JPBS) is an open access international journal that provides rapid publication (within a month) of articles in all areas of Pharmacy and Biological Science. The journal welcomes publications of high quality papers on theoretical developments and practical applications in Pharmacy and Biological Science. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
Crash Analysis of Front under Run Protection Device using Finite Element Anal...IOSR Journals
Under-running of passenger vehicles is one of the important parameters to be considered during
design and development of truck chassis. Front Under-run Protection Device (FUPD) plays an important role
in avoiding under-running of vehicles from front side of a truck. An explicit finite element software Altair
Radio's is used in FUPD analysis for impact loading. The deformation of FUPD bar and plastic strains in
FUPD components are determined in the impact analysis for predicting failure of the system to meet the
compliance requirements as per IS 14812-2005. Additionally, failure analysis of the FUPD attachment points
with chassis is determined. Physical testing can be reduced significantly with this approach which ultimately
reduces the total cycle time as well as the cost involved in product development.
Implementation of PCI Target Controller Interfacing with Asynchronous SRAMIOSR Journals
Abstract: In this paper, we present design of a PCI (Peripheral Component Interconnect) target controller
which is interfacing with asynchronous SRAM 64kX8 memory. The target controller provides the control signals
to the SRAM for read and writes cycles. The master sends the address, data and other control signals. Based on
these signals the controller initiates the read and write cycles we have designed PCI block diagram which
represents how the master controls target and target interfaces with memory. We also designed state machine to
generate control signals for target controller by which the controller initiates the read and write cycles. PCI
implements a 32-bit multiplexed Address and Data bus (AD [31:0]).The simulation results presented in this
paper represents read and write transactions between slave and memory according to commands generated by
controller. We have been used Xilinx ISE project navigator 0.40d to simulate project code which is written in
Verilog Hardware Description Language. We have been tested our functionality by writing test bench and then
compared that results with actual functionality.
Keywords – Asynchronous SRAM, PCI, PCI connector
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.
Minimization of Surface Roughness in CNC Turning Using Taguchi MethodIOSR Journals
Turning is a process to remove the material from the outer diameter of the rotating cylindrical work
piece. The aim of the project is minimization of surface roughness in turning operation by using taguchi method.
Taguchi method is used to find the best combination of cutting parameters like speed (N), feed (f), depth of cut
(d), tool nose radius (Rn) and shim materials (Sm) are predicted by using L16 orthogonal array. The
combination of control levels was predicted for the optimal surface roughness and using (S/N) ratio. A
confirmation runs was used to verify the results for the optimal surface roughness
“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.
Experimental Study of Surface Parameters of EN31 on Powder Mixed EDM using Ta...ijsrd.com
PEDM has become an effective method of machining extremely tough and brittle electrically conductive materials. It is widely used in the process of making moulds and dies and sections of complex geometry and intricate shapes. The work piece material selected in this experiment is EN 31 taking into account its wide usage in industrial applications. In today’s world 304 stainless steel contributes to almost half of the world’s production and consumption for industrial purposes. The input variable parameters are type of powder, current, pulse on time and powder concentration. Taguchi method is applied to create an L18 orthogonal array of input variables using the Design of Experiments (DOE). The effect of the variable parameters mentioned above upon machining characteristics such as Material Removal Rate (MRR) and Surface Roughness (SR) is studied and investigated. The tool material is copper. All the calculations are made with the help of MINITAB 16 software. Dielectric used for experimentation is kerosene. Two powders silicon carbide and boron carbide of 70 mesh is used. Most influence factor for MRR observed is powder concentration with 49.12 % contribution. For SR peak current with contribution of 43.4 % plays a n important role.
APPLICATION OF GREY RELATIONAL ANALYSIS FOR MULTI VARIABLE OPTIMIZATION OF PR...IAEME Publication
The present work deals with a simple approach which predicts the optimum setting
of process parameters of drilling operation on Polymer Based Glass Fiber (PBGF)
composite. The process parameters selected are drill angle (DA), Drill diameter (DD),
Material Thickness (MT), Speed (N) and Feed (f). The output parameters are Thrust,
Torque, Surface Roughness and Delamination. Three levels of each input parameters
are considered. Taguchi’s L27 array is used to set the process parameters. Gray
relational analysis (GRA) is used to find the optimum value of process parameters.
Conduction of ANOVA on GRA shown the significance of each factor on the process
output. A conformation test conducted revealed that the setting of parameters ensures
optimum output
Parametric Analysis and Optimization of Turning Operation by Using Taguchi Ap...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
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
In this experimental study, an attempt is made to obtain optimum cutting parameters for turning
of mild steel on the basis of surface roughness and surface temperature. Optimization of cutting parameters is
very important to obtain a good machining quality of surface and to inhibit the increase of temperature.
Minimum Quantity Lubrication (MQL) has been introduced to avoid excessive use of cutting fluid. The
parameters considered here are cutting speed, feed and depth of cut. Optimal cutting parameters for each
performance measure were obtained employing Taguchi experimental method. To study the performance
characteristics in turning operation Analysis of Variance (ANOVA) was employed. It is found that cutting speed
and feed has significant effect on both surface roughness and temperature.
Research Inventy : International Journal of Engineering and Scienceinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
Surface Topology Evaluation of P20 Steel by Multipass Cutting Strategy in Wir...IJERA Editor
Wire EDM process eliminates the work materials by a series of electrical sparks between the workpiece and wire electrode. These sparks creates craters and burs on the machined surface. Machined surface with poor integrity is a major disadvantage of WEDM. This work presents the investigation on multi-pass cutting operation (single rough cut followed by multi trim cuts) in wire electrical discharge machining (WEDM) of p20 steel. Trim cuts were performed using Taguchi’s design of experiment method to investigate the influence of discharge current (Ip), pulse-on time (Ton), pulse-off time, servo voltage and number of trim cuts on two performance characteristics namely cutting rate and surface roughness (SR).Experiments were performed using 0.25mm brass wire. Result shows that the surface finish improves significantly in trim cutting operation.
Prediction of output Responses in Milling of Casted Aluminum by using ANNijiert bestjournal
The important goal in the modern industries is to m anufacture the products with lower cost and with hi gh quality in short span of time. There are two main p ractical problems that engineers face in a manufacturing process. The first is to determine th e values of process parameters that will yield the desired product quality (meet technical specificati ons) and the second is to maximize manufacturing system performance using the available resources. T he increase of customer needs for quality products (more precise tolerances and better product surface roughness) have driven the metal cutting process. The main objective of this project work is to study the effect of surface roughness and Material Removal R ate in a machining of cast aluminum on CNC milling mach ine with High Speed Steel cutting tool. The feasibility of implementation of design of experime nts (DOE),and Artificial Neural network in milling process is analyzed.
Investigation of Process Parameters for Optimization of Surface Roughness in ...IJERA Editor
Surface roughness has significant effect on functionality and service life of components. If surface roughness is properly controlled then, performance of the component enhances in operational applications. Surface roughness becomes key concern when intricate profiles and shapes are required to be manufactured in components. The objective of the paper is to bring up an adequate surface roughness in finish cut by optimizing process variables. If initial surface form is obtained by proper control of machining parameters then additional finishing efforts and lead time reduce a lot. In the industrial tool room survey availability of machining data is prime concern in terms of tuned process parameter for precision machining. Optimization of process parameters is essential in order to arrest surface roughness and thereby improve surface textures. Experimental investigations are performed to study the effect of pulse current, pulse on time and gap voltage on response of surface roughness, in case of ram EDM. Design of experimentation (DOE) and ANOVA are carried out for optimization of process parameters, within work interval of finish cut machining
Experimental Investigation and Parametric Analysis of Surface Roughness in C...IJMER
The manufacturing industries are very much concerned about the quality of their products.
They are focused on producing high quality products in time at minimum cost. Surface finish is one of the
crucial performance parameters that have to be controlled within suitable limits for a particular process.
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. These include cutting tool variables, work
piece material variables, cutting conditions etc. Therefore, prediction or monitoring of the surface
roughness of machined components has been challenging and unexplored area of research
The present work is therefore in a direction to integrate effect of various parameters which effect the
surface roughness. Experiments were carried out with the help of factorial method of design of
experiment (DOE) approach to study the impact of turning parameters on the roughness of turned
surfaces. A mathematical model was formulated to predict the effect of machining parameters on surface
roughness of a machined work piece. Model was validated with the experimental data and the reported
data of other researchers. Further parametric investigations were carried out to predict the effect of
various parameters on the surface research
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Transcript: Selling digital books in 2024: Insights from industry leaders - T...BookNet Canada
The publishing industry has been selling digital audiobooks and ebooks for over a decade and has found its groove. What’s changed? What has stayed the same? Where do we go from here? Join a group of leading sales peers from across the industry for a conversation about the lessons learned since the popularization of digital books, best practices, digital book supply chain management, and more.
Link to video recording: https://bnctechforum.ca/sessions/selling-digital-books-in-2024-insights-from-industry-leaders/
Presented by BookNet Canada on May 28, 2024, with support from the Department of Canadian Heritage.
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
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How world-class product teams are winning in the AI era by CEO and Founder, P...
D012112027
1. IOSR Journal of Mechanical and Civil Engineering (IOSR-JMCE)
e-ISSN: 2278-1684,p-ISSN: 2320-334X, Volume 12, Issue 1 Ver. I (Jan- Feb. 2015), PP 20-27
www.iosrjournals.org
DOI: 10.9790/1684-12112027 www.iosrjournals.org 20 | Page
Cutting Parameter Optimization for Surface Finish and Hole
Accuracy in Drilling Of EN-31
Mr. Nalawade P.S. and Prof. Shinde S.S.
1
Productionl Engineering Department, KIT, Kolhapur, India
2
Mechanical Engineering Department, KIT, Kolhapur, India
Abstract: In today’s competitive world of manufacturing and machining, drilling process plays a vital role.
Drilling of hole with minimum time, along with maintaining accuracy of hole is important. For assembly and
sliding motion of shaft in hole, hole finishing also became significant. So for drilling operation, now a day’s
surface finish and accuracy of hole are new challenges for industry. Paper will deal with above mentioned
requirements viz. surface finish and hole accuracy for EN 31 as widely used material with selected input
parameters as speed, depth of cut, feed and type of tool. Confirmation of input parameters is done by review of
literature, and optimums setting are made by taguchi’s design after performing experimentation, followed by
ANOVA and regression analysis, for optimization of surface finish speed, feed and type of tool found significant
with values of 30m/min, 0.2 mm/rev., HSS respectively. For optimization of hole accuracy speed, feed, type of
tool and drill depth found significant with values of 30m/min, 0.2 mm/rev., HSS + TiN, 20mm respectively.
Result will be useful for manufacturing industries for maintaining higher surface finish and accuracy for dry
drilling process for EN 31 material.
Keywords: ANOVA, DOE, Drilling, Hole Accuracy, Regression, Surface Finish, Taguchi Method
I. Introduction
Drilling processes are widely used in the aerospace, aircraft, and automotive industries. Although
modern metal-cutting methods have improved in the manufacturing industry, including electron beam
machining, ultrasonic machining, electrolytic machining, and abrasive jet machining, conventional drilling still
remains one of the most common machining processes. Amongst traditional machining processes, drilling is one
of the most important metal-cutting operations, comprising approximately 33% of all metal-cutting operations.
(Zhao H, 1994)
Steps applied in Taguchi’s optimization method
Fig.1 Taguchi’s Approach To Parameter Design
II. Taguchi’s Approach To Parameter Design
Taguchi's approach to parameter design provides the design engineer with a systematic and efficient
method for determining near optimum design parameters for performance and cost (Chen WC, Tsao CC, 1999).
The objective is to select the best combination of control parameters so that the product or process is most
robust with respect to noise factors. The Taguchi method utilizes orthogonal arrays from design of experiments
2. Cutting Parameter Optimization for Surface Finish and Hole Accuracy in Drilling of EN 31
DOI: 10.9790/1684-12112027 www.iosrjournals.org 21 | Page
theory to study a large number of variables with a small number of experiments. Using orthogonal arrays
significantly reduces the number of experimental configurations to be studied. Furthermore, the conclusions
drawn from small scale experiments are valid over the entire experimental region spanned by the control factors
and settings (Dasch JM et al., 2010)
2.1 Orthogonal Arrays:
These are not unique to Taguchi. They were discovered considerably earlier However, Taguchi has
simplified their use by providing tabulated sets of standard orthogonal arrays and corresponding linear graphs to
fit specific projects (Pirtini M, Lazoglu I, 2005)
2.2Linear Graphs:
Linear graphs are simple tools for the allocation of effects (main effects and interactions) to the
columns of an orthogonal array. A linear graph consists of dots, lines and numbers. A dot represents a main
effect; a line between two dots represents the interaction between the two connected main effects (dots). Each of
the dots and lines is numbered, the numbers representing the columns of the orthogonal array (Phadke, 1989).
2.3Signal-to-Noise Ratio:
Asignal-to-noise (S/N) ratio is a performance measure, which estimates the effect of the noise factors
on the quality characteristic. For each of the three optimization goals a S/N ratio has been developed. These S/N
ratios are proposed to provide a product design that simultaneously places the response on a target and a
minimum variance (Yang JL, Chen JC, 2001).
III. Experimental Work
Taguchi methods which combine the experiment design theory and the quality loss function concept
have been used in developing robust designs of products and processes and in solving some taxing problems of
manufacturing (Furness RJ, 1996). The ranges of cutting parameters are selected based on the tool
manufacturer’s recommendation and industrial applications.
3.1 Drilling Tools and Work Piece Material:
In this study, drilling tests were performed using 10 mm diameter, HSS twist uncoated drills, HSS
TiAlN-coated drills, and HSS TiN-coated drills. Table 3 shows the dimensional properties of the drilling tools.
The work piece material was EN31, which is extensively used in the manufacturing industry.
3.1.1 Dimensional Properties of Cutting Tool:
The dimensional properties of the cutting tool plays very important role in drilling process which are
mentioned in the following Table no.1
Table 1: Dimensional properties of cutting tool
Drill 1 2 3
Too Diameter 10 mm 10 mm 10 mm
Flute 2 flute 2 flute 2 flute
Point Angle 118 118 118
Helix Angle 30 30 30
Flute Angle 87 87 87
Shank Type Cylindrical Cylindrical Cylindrical
Coating Uncoated TiAlN TiN
3.2 Surface Finish:
For optimizqtion of surface finish parameters, with reference to duscussion with expert and from
literatute, we have selected 3 parameters viz. Cutting Speed, Feed rate and type of tool with 3 levels as shown
infollowing table. We will set smaller is better for optimization of setting of parameters for achieving higher
surface finish.
3.2.1 Levels of parameters for surface finish:
By taking the opinion from experts in academic and industry and also after intense literature review the
input parameters and their levels are selected which are given in the following Table no. 2
For 3 factors and 3 levels we have to conduct 3^3=27 experiments. To avoid this, by using orthogonal
array for 3 factors and 3 levels, we will use L9 orthogonal array, so that we will need to do 9 experiments only.
3. Cutting Parameter Optimization for Surface Finish and Hole Accuracy in Drilling of EN 31
DOI: 10.9790/1684-12112027 www.iosrjournals.org 22 | Page
Table No2: Levels of parameters for surface finish
Parameter Level 1 Level 2 Level 3
Cutting Speed(m/min) 30 40 50
Feed Rate(mm/min) 0.2 0.3 0.4
Type of tool HSS+TiN HSS+TiAlN HSS (uncoated)
3.2.2 Surface Finish Values with S/N Ratio:
After performing above mentioned experiments with mentioned levels, following surface finish values
are obtained which are tabulated below in Table no.3.
Table No3: Surface Finish Values with S/N Ratio
Experiment
No.
(A) Feed rate
(mm/min)
(B) Cutting speed
(m/min
(C) Drilling
tool
Surface
finish
value (μm)
S/N Ratio
1 1 1 1 5.72 -15.1479
2 1 2 2 5.56 -14.9015
3 1 3 3 3.64 -11.222
4 2 1 3 5.94 -15.4757
5 2 2 2 5.22 -14.3534
6 2 3 1 7.48 -17.478
7 3 1 3 5.16 -14.253
8 3 2 1 7.32 -17.2902
9 3 3 2 7.76 -17.7972
3.3 Hole Acuuracy:
For 4 factors and 3 levels we have to conduct 3^4=81 experiments. To avoid this, by using orthogonal
array for 3 factors and 4 levels, we will use mix L18 orthogonal array, so that we will need to do 18 experiments
only for hole accuracy.
3.3.1 Selection of factors and their levels for hole accuracy:
For optimizqtion of surface finish parameters, with reference to duscussion with expert and from
literatute , we have selected 4 parameters viz. Cutting Speed, Feed Rate ,Type of Tool & Drilling Depth with 3
levels as shown infollowing Table no. 4.
Table No 4: Selection of factors and their levels for hole accuracy
Parameter Level 1 Level 2 Level 3
Cutting Speed ( m/min) 30 40 50
Feed Rate(mm/min) 0.2 0.3 0.4
Type of tool HSS+TiN HSS+TiAlN HSS (uncoated)
Drill Depth (or mm) 15 20 -
Table No 5: Hole diametral error values with S/N Ratio
Experiment
No.
Drill Depth
(mm)
Feed
Rate(mm/min)
Cutting Speed (
m/min)
Type of
tool
Hole diametral
error
value (μm)
S/N Ratio
1 1 1 1 1 42.47 -32.5616
2 1 1 2 2 52.90 -34.4691
3 1 1 3 3 51.62 -34.2564
4 1 2 1 1 52.90 -34.4691
5 1 2 2 2 68.72 -36.7417
6 1 2 3 3 72.38 -37.1924
7 1 3 1 2 84.10 -38.4959
8 1 3 2 3 80.72 -38.1396
9 1 3 3 1 104.70 -40.3989
10 2 1 1 3 40.16 -32.0759
11 2 1 2 1 37.20 -31.4109
12 2 1 3 2 51.48 -34.2328
13 2 2 1 2 56.88 -35.0992
14 2 2 2 3 58.70 -35.3728
15 2 2 3 1 58.60 -35.358
16 2 3 1 3 70.66 -36.9835
17 2 3 2 1 79.20 -37.9745
18 2 3 3 2 68.40 -36.7011
4. Cutting Parameter Optimization for Surface Finish and Hole Accuracy in Drilling of EN 31
DOI: 10.9790/1684-12112027 www.iosrjournals.org 23 | Page
3.3.2 Hole diametral error values with S/N Ratio:
After performing above mentioned experiments with mentioned levels, following hole diametral error values are
obtained which are given with their S/N ratio in Table no. 5.
IV. Analysis Of Experimental Work
4.1 Response Table for Surface Finish:
After performing 9 experiments for surface finish, following table gives optimum setting for achieving higher
surface finish value and the optimum values of the various parameters are given in the Table no.6.
Table No 6: Response Table for Surface Finish
Levels (A) Feed rate (mm/min) (B) Cutting speed (m/min) (C) Drilling tool
1 4.97333* 5.6067* 6.84
2 6.21333 6.0333 6.4200
3 6.74667 6.29333 4.67333*
Δmax-min (Delta) 1.77333 0.68667 2.16667
Rank 2 3 1
4.2 Graphical Representation of Effect of Drilling Parameter on Surface Finish (SN Ratio):
Following graphs gives additional information with confirmation for setting of optimum values and
effect of each parameter on surface finish. As we expect S/N ratio value should be higher, we can predict setting
level for surface finish from following graph as
Feed rate - setting at Level 1
Cutting Speed - setting at Level 1
Type of Tool - setting at Level 3
Fig.: 2 Graph 1: Effect of drilling parameter on Surface Finish (S/N Ratio)
4.3 Response table for hole diametral error:
After performing 18 experiments for hole diametral error, following table gives optimum setting for
achieving lower hole diametral error and the optimum values of the various parameters are given in the
following Table no.7
Table No7: Response table for hole diametral error
Levels (D) Drill Depth
( mm)
(A) Feed rate
(mm/min)
(B) Cutting
speed (m/min)
(C) Drilling
tool
1 67.8344 45.9717* 57.8617* 62.5117*
2 57.9200* 61.3633 62.9067 63.7467
3 - 81.2967 67.8633 62.373
Δ(max-min) Delta) 9.9144 35.3250 10.0017 1.3733
Rank 3 1 2 4
4.4 Graphical representation of Effect of drilling parameter on hole diametral error (SN Ratio):
Following graphs gives additional information with confirmation for setting of optimum values and
effect of each parameter on hole diametral error. As we expect S/N ratio value should be higher, we can predict
setting level for Hole accuracy from following graph as
5. Cutting Parameter Optimization for Surface Finish and Hole Accuracy in Drilling of EN 31
DOI: 10.9790/1684-12112027 www.iosrjournals.org 24 | Page
Feed rate – setting at Level 1
Cutting Speed - setting at Level 1
Type of Tool - setting at Level 1
Drill Depth- setting at Level 2
Fig. 3: Effect of drilling parameter on hole diametral error (S/N Ratio).
4.5 Regression Analysis:
The cutting speed, feed rate, drilling depth, and drilling tool were considered in the development of
mathematical models for the hole diameter accuracy, while cutting speed, feed rate, and drilling tool for surface
finish. The correlation between factors (cutting speed, feed rate, drilling depth, and drilling tool) and hole
diameter accuracy for dry drilling conditions on the EN31 alloy were obtained by multiple linear regression. A
linear polynomial model is developed to control whether the hole diameter accuracy and surface finish data
represent a fitness characteristic as below:
Hole diameter accuracy HDA=b0+b1 (drilling depth) +b2f+b3Vc++b4 (drilling tool) + ε
Surface finish value (Ra) = b0+b1f+b2Vc+b3d+ ε
Where b1, b2, b3, and b4 are estimates of the process parameters and ε is the error. The standard
commercial statistical software package MINITAB was used to derive the models of the form:
- For hole diameter accuracy: HDA=f (drilling depth, f, Vc, drilling tool)
- For the surface finish value: Ra=f (f, Vc, drilling tool)
Where the drilling depth is in mm, f=feed rate in mm/min, Vc=cutting speed in rev/min, and the
drilling tools are uncoated, TiAlN, and TiN-coated). The models obtained are as follows:
Surface Finish = 4.43 + 8.87 f + 0.0188 Vc - 0.932 drilling tool ……………………….. (Eq.1)
R-Sq = 84.0%
Hole Diameter Error = 32.6 - 9.91 dd + 17.7 f + 5.00 Vc - 0.07 drilling tool …………..... (Eq.2)
R-Sq = 87.6%
4.6 Analysis of Variance (ANOVA)
4.6.1 Analysis of variance (ANOVA) results for the whole diametral error for the drilling:
The depth of drilling and feed rate factors present statistical and physical significance on the hole
diameter accuracy value, because the test F>Fα=5%, as shown in Table no. 8.
The P-value reports the significance level (suitable and unsuitable) in Table 8. Percent (%) is defined as
the significance rate of the process parameters on the hole diameter accuracy. The percent numbers depict that
the depth of drilling, feed rate and cutting speed have significant effects on the hole diameter accuracy. It can
observed from Table 14 that the depth of drilling (A), feed rate (B), cutting speed (C), and drill tool affect the
hole diameter accuracy by 8.64%, 73.53%, 5.86%, and 0.13% in the dry drilling.
6. Cutting Parameter Optimization for Surface Finish and Hole Accuracy in Drilling of EN 31
DOI: 10.9790/1684-12112027 www.iosrjournals.org 25 | Page
Table No 8 : (ANOVA) results for the hole diametral error for the drilling
Source DF Seq. SS Adj. SS Adj. MS F P %
Depth of cut 1 442.33 442.33 442.33 7.30 0.022 8.64
Feed Rate 2 3764.19 3764.19 1882.10 31.08 0.000 73.53
Cutting 2 300.11 300.11 150.05 2.48 0.134 5.86
Drilling 2 6.86 6.86 3.43 0.06 0.945 0.13
Error 10 605.64 605.64 60.56 11.83
Total 17 5119.13
The F-ratio corresponding to the 95% confidence level in the calculation of the process parameters
accurately is F0.05, 1, 17=4.451 for the depth of drilling parameter (A) and F0.05, 2, 17=3.592 for the feed rate
(B), cutting speed (C), and drill tools (D). The depth of drilling and feed rate factors present statistical and
physical significance on the hole diameter accuracy value, because the test F>Fα=5%, as shown Table 14.
4.6.2 Analysis of variance (ANOVA) results for the hole surface finish:
The F-ratio corresponding to the 95% confidence level in the calculation of the process parameters
accurately is F0.05, 2, 8=4.459. The feed rate and different drill tool factors present statistical and physical
significance on the surface finish, because the test F>Fα=5%, as shown in Table no. 9.
Table No9 : (ANOVA) results for the hole surface finish
Source DF Seq. SS Adj. SS Adj. MS F P %
Feed Rate 2 4.9668 4.9668 2.4834 8.63 0.104 35.01
Cutting 2 0.7212 0.7212 0.3606 1.25 0.444 5.08
Drilling 2 7.9217 7.9217 3.9608 13.76 0.068 55.84
Error 2 0.5756 0.5756 0.2878 4.05
Total 8 14.1852
P-value reports the significance level (suitable and unsuitable) in Table 15. Percent (%) is defined as
the significance rate of the process parameters on the surface finish values. The percent numbers depict that the
cutting speed and drill tool factors have significant effects on the surface finish. It can observed from Table 17
that the feed rate (A),cutting speed (B), and drill tool (C) affect the surface finish value by 35.01%, 5.08%, and
55.84% in the drilling, respectively.
The F-ratio corresponding to the 95% confidence level in the calculation of the process parameters
accurately is F0.05, 2, 8=4.459. The feed rate and different drill tool factors present statistical and physical
significance on the surface finish, because the test F>Fα=5%, as shown in Table 15.
V. Confirmation Of Experiment
5.1 Confirmation Test:
The experimental confirmation test is the final step in verifying the results drawn based on Taguchi’s
design approach. The optimal conditions are set for the significant factors (the insignificant factors are set at
economic levels) and a selected number of experiments are run under specified cutting conditions. The average
of the results from the confirmation experiment is compared with the predicted average based on the parameters
and levels tested. The confirmation experiment is a crucial step and is highly recommended by Taguchi to verify
the experimental results.
In this study, a confirmation experiment was conducted by utilizing the levels of the optimal process
parameters (A1B1C3) for surface finish and (A2B1C1D2) for the hole diameter accuracy value in the dry
drilling.
5.2 Determination of Minimum Ra and Diametral Error:
Using the aforementioned data, one can predict the optimum surface finish and minimum hole
diametral error value performance using the cutting parameters as follows. For the diametral error:
Predicted mean (min diametral error) =A1+B1+C1+D2-3(Y)
=45.9717+57.8617+62.5117+57.9200- 3(62.87)
=35.65μm
Similarly, the maximum S/N ratio is calculated to determine whether or not the minimum surface finish
is acceptable.
7. Cutting Parameter Optimization for Surface Finish and Hole Accuracy in Drilling of EN 31
DOI: 10.9790/1684-12112027 www.iosrjournals.org 26 | Page
Also, the maximum S/N ratio for the diametral error varies in the range (−40.39 dB) < (−32.56 dB) <
(+∞ dB). The S/ N ratio could be predicted as:
Predicted S/N ratio ðmax:
ηA1+ ηB1+ ηC1+ ηD2- 3ðη
= -35.023-33.167-34.9475-35.3621-3(-35.6629)
=-31.51dB
Where η is the average value of the hole diametral error or S/N ratio. With this prediction, one could
conclude that the machine creates the optimal hole diameter accuracy (HDA= 35.65 μm) within the range of
specified cutting conditions.
For the surface finish:
Predicted mean min: Ra
A1 + B1 + C3 - 2Y
= 4.97333+5.6067+4.67333-2(5.97)
=3.31μm
Similarly, the maximum S/N ratio is calculated to determine whether or not the minimum surface finish is
acceptable. Also, the maximum S/N ratio for the surface finish varies in the range Ra= ((−17.7972 dB) <
(−11.222dB) < (+∞ dB). The S/N ratio could be predicted as:
Predicted S/N ratio max:
ηA1+ ηB1+ ηC3- 2ðη
-13.757-14.958-13.65-(2-15.32)
=-11.725dB
VI. Result
6.1 Results of the confirmation experiment for surface finish:
After performing an experiment and doing the calculations the results are obtained in which the
predicted and confirmed values of surface finish have been compared as shown in following Table no.10 and
obtained results are with input parameters as cutting speed, feed, type of tool with corresponding levels to
achieve higher surface finish.
Table No 10 : confirmation experiment for surface finish.
Optimal Machining
Parameters
Predicted Confirmation
Level A1B1C3 A1B1C3
Ra ( Micron) 3.31 3.4
S/N Ratio for Ra -11.725dB -11.52dB
6.2 Results of the confirmation experiment for hole diameter accuracy:
After performing an experiment and doing the calculations the results are obtained in which the
predicted and confirmed values of hole diametral error have been compared as shown in following Table no.11
and obtained results are with input parameters as cutting speed, feed, type of tool and drill depth with
corresponding levels to achieve higher surface finish.
Table No 11 : confirmation experiment for hole diameter accuracy
Optimal Machining Parameters
Predicted
Confirmation
Level A1B1C1D2 A1B1C1D2
Dia. Error 35.65μm 35.42μm
S/N Ratio for Dia. Error -31.51dB -31.34dB
VII. Conclusions
This study has discussed an application of the Taguchi method for investigating the effects of cutting
parameters on the surface finish and hole diameter accuracy values in the dry drilling. In the drilling process, the
parameters were selected taking into consideration of manufacturer and industrial requirements. The obtained
optimal parameters have been used in drilling processes by the manufacturer. From the analysis of the results in
the drilling process using the conceptual signal-to-noise (S/N) ratio approach, regression analysis, analysis of
variance (ANOVA), and Taguchi’s optimization method, the following can be concluded from the present
study:
8. Cutting Parameter Optimization for Surface Finish and Hole Accuracy in Drilling of EN 31
DOI: 10.9790/1684-12112027 www.iosrjournals.org 27 | Page
For Surface Finish For Hole Accuracy
Input Parameter Level (Setting Value)
Cutting Speed 1 (30 m/min)
Feed 1 (0.2 mm/min)
Type of Tool 3 (HSS Un Coated)
References
[1]. Chen WC, Tsao CC (1999) Cutting performance of different coated twist drills. J Mater Process Technol 88:203–207
[2]. Dasch JM, Ang CC, Wong CA, Cheng YT, Weiner AM, Lev LC (2006) A comparison of five categories of carbon-based tool
coatings for dry drilling of aluminum. Surf Coat Technol200:2970–2977
[3]. Pirtini M, Lazoglu I (2005) Forces and hole quality in drilling. IntJ Mach Tools Manuf 45:1271–1281
[4]. Phadke MS (1989) Quality engineering using robust design. Prentice-Hill, Englewood Cliffs, NJ
[5]. Yang JL, Chen JC (2001) A systematic approach for identifying optimum surface roughness performance in end-milling
operations.J IndTechnol 17:1–8
[6]. Zhao H (1994) Predictive models for forces, power and holeoversize in drilling operations. PhD thesis, University of Melbourne,
Australia
Input Parameter Level (Setting Value)
Cutting Speed 1 (30 m/min)
Feed 1 (0.2mm /min)
Type of Tool 1 (HSS+ TIN)
Drill Depth 2(20 mm)