As per the modern Industrial requirements, higher surface finish mechanical components and mating parts with close limits and tolerances, is one of the most important requirement. Abrasive machining processes are generally the last operations performed on manufactured products for higher surface finishing and for fine or small scale material removal. Higher surface finish and high rate of removal can be obtained if a large number of grains act together. This is accomplished by using bonded abrasives as in grinding wheel or by modern machining processes. In the present study, Taguchi method or Design of experiments has been used to optimize the effect of cylindrical grinding parameters such as wheel speed (rpm), work speed, feed (mm/min.), depth of cut and cutting fluid on the surface roughness of EN15AM steel. Ground surface roughness measurements were carried out by Talysurf surface roughness tester. EN15AM steel has several industrial applications in manufacturing of engine shafts, connecting rods, spindles, studs, bolt, screws etc. The results indicated that grinding wheel speed, work piece speed, table feed rate and depth of cut were the significant factors for the surface roughness and material removal rate. Surface roughness is minimum at 2000 r.p.m. of grinding wheel speed , work piece speed 80 rpm, feed rate 275 mm/min. and 0.06 mm depth of cut.
Optimization of Cylindrical Grinding Process Parameters on C40E Steel Using T...IJERA Editor
Surface finish and dimensional accuracy play a vital role in the today’s engineering industry. There are several methods used to achieve good surface finish like burnishing, honing and lapping, and grinding. Grinding is one of these ways that improves the surface finish and dimensional accuracy simultaneously. C40E steel has good industrial application in manufacturing of shafts, axles, spindles, studs, etc. In the present work the cylindrical grinding of C40E steel is done for the optimization of grinding process parameters. During this experimental work input process parameters i.e. speed, feed, depth of cut is optimized using Taguchi L9 orthogonal array. Analysis of variance (ANOVA) concluded that surface roughness is minimum at the 210 rpm, 0.11mm/rev feed, and 0.04mm depth of penetration.
International Journal of Engineering Research and Applications (IJERA) aims to cover the latest outstanding developments in the field of all Engineering Technologies & science.
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Our journal system primarily aims to bring out the research talent and the works done by sciaentists, academia, engineers, practitioners, scholars, post graduate students of engineering and science. This journal aims to cover the scientific research in a broader sense and not publishing a niche area of research facilitating researchers from various verticals to publish their papers. It is also aimed to provide a platform for the researchers to publish in a shorter of time, enabling them to continue further All articles published are freely available to scientific researchers in the Government agencies,educators and the general public. We are taking serious efforts to promote our journal across the globe in various ways, we are sure that our journal will act as a scientific platform for all researchers to publish their works online.
Determining the Influence of Various Cutting Parameters on Surface Roughness ...IOSR Journals
The document describes an experimental investigation that analyzed the effect of various cutting parameters on surface roughness during wet CNC turning of AISI 1040 medium carbon steel. The parameters tested included cutting speed, feed rate, depth of cut, cutting fluid concentration, and two different cutting fluids. Custom experimental design and statistical analysis using JMP software revealed that feed rate had the most significant influence on surface roughness, and that there was no significant difference in surface roughness between the two cutting fluids tested.
IRJET- Taguchi Optimization of Cutting Parameters for Surface Roughness and M...IRJET Journal
This document summarizes a study that used the Taguchi method to optimize cutting parameters (cutting speed, feed rate, and depth of cut) for surface roughness and material removal rate during turning operations. Experiments were conducted using a CNC lathe machine and 25Cr-12 Ni TP309 steel workpiece material. An L9 orthogonal array was used to collect data on the response variables (surface roughness and material removal rate) based on variations in the cutting parameters. The data was analyzed using signal-to-noise ratios and ANOVA to determine the optimal cutting parameter settings that minimized surface roughness and maximized material removal rate.
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.
Analysis of process parameters in dry machining of en 31 steel by grey relati...IAEME Publication
This paper presents the optimization of surface roughness & material removal rate in dry turning of EN-31 steel.Carbide inserts were used for machining of EN-31 to study effects of process parameters [Cutting speed (S), Feed (F) and depth of cut (d)]. These models can be effectively used to predict the surface roughness (Ra) of the workpiece. The big challenge of the Micro, small& medium industries in India for achieving high quality products with increased productivity.Paper presentswork of an investigation of turning process parameters on EN-31 material, for optimization of surface roughness, material removal rate.The experiment is carried out by considering three controllable input variables namely cutting speed, feed rate, and depth of cut.The design of experiment and optimization of surface roughness is carried out by using Taguchi L9 orthogonal array & Grey Relational analysis.
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 of turning process parameter in dry turning of sae52100 steelIAEME Publication
This document discusses optimizing surface roughness and material removal rate in dry turning of SAE52100 steel. Experiments were conducted using different cutting speeds, feeds, and depths of cut. Surface roughness and material removal rate were measured for each experimental condition. The results were analyzed using Taguchi methods to determine the optimal levels for each process parameter to minimize surface roughness and maximize material removal rate. The analysis found that feed rate had the greatest influence on surface roughness, while cutting speed had the greatest influence on material removal rate.
IRJET- A Review on: Parametric Study for Optimization of CNC Turning Process ...IRJET Journal
This document reviews research on optimizing CNC turning process parameters to minimize surface roughness. It summarizes 10 research papers that studied the effects of cutting speed, feed rate, depth of cut, cutting tool type, and cooling conditions on surface roughness when turning various materials like steel, aluminum, and titanium. The document finds that feed rate typically has the largest effect on surface roughness, followed by cutting speed, while depth of cut has a smaller impact. It recommends using techniques like Taguchi methods, response surface methodology, and ANOVA to determine the optimal process parameters that achieve the minimum possible surface roughness.
The document discusses optimizing parameters for boring operations. It aims to achieve a surface finish less than 2 micrometers and bore diameter of 70 mm. Experiments were conducted varying speed, feed rate, and depth of cut. Analysis of variance and response surface methodology were used to analyze results. The optimal parameters were found to be a speed of 1000 rpm and feed rate of 100 mm/min, predicted to achieve a surface roughness of 1.843 micrometers and bore diameter of 70.005 mm. Validation experiments confirmed the predicted results were within acceptable ranges.
The big challenge of the mass production firms is concentrated for achieving high quality
products with good dimensionability with high productivity, less wear on the cutting insert, less use
of cutting fluid, within less time. This paper present dissertation work of an investigation of turning
process parameters on hard EN 31 material, for optimization of surface roughness, material removal
rate, machining time in wet and minimum quantity lubrication system. The experiment is carried out
by considering four controllable input variables namely cutting speed, feed rate, depth of cut and
insert nose radius in the presence of wet & MQL system. This experiment also present the relation
between chip formations and controllable variables along with chip thickness, chip colors & chip
velocity from which its effect on insert wear, quality of product can be easily found out, because of
chip morphology gives indirectly the effect of it on the insert wear. In this dissertation work
minimum quantity lubrication system is used for reducing the cutting zone temperature properly and
very fastly. Finally comparison is carried out between wet and minimum quantity lubrication system
from which one can easily identify which system is better for higher productivity along with high
surface finish. This work also present the productivity (MRR) concept in production. The design of
experiment and optimization of surface roughness, material removal rate, machining time is carried
out by using response surface methodology (RSM). Central composite design method is used (CCD)
for the total experimental design work and its analysis and also for optimization of turning process
parameter by which wastage of the machining time, power can be avoided.
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.
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1) JK Files (India) Limited aimed to become the largest and best manufacturer of files in the world through redesigning operations, processes, and technology infusion to build world-class plants, de-skilled processes, and offer a wider range of high-quality products.
2) The company redesigned value stream layouts across plants to reduce material movement, work in process, and throughput times, improving productivity and quality consistency.
3) New technologies like induction heating furnaces and saw cutting were introduced to improve steel quality while reducing wastage. Robotic hardening and new generation grinding/teeth cutting machines increased productivity five to six times.
4) Other changes included single-piece lamin
IRJET- Review Paper Optimization of Machining Parameters by using of Taguchi'...IRJET Journal
This document summarizes a research paper that used the Taguchi method to optimize machining parameters for turning operations on EN-31 alloy steel. The paper conducted experiments using various cutting speeds, feed rates, and depths of cut. The Taguchi design of experiments approach was used to determine the optimal machining parameters that maximize material removal rate. Analysis with MINITAB statistical software found that feed rate had the greatest influence on surface roughness, while cutting speed most significantly impacted cutting forces. The optimized parameters can improve the efficiency and cost-effectiveness of turning EN-31 alloy steel.
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 of Surface Roughness Parameters in Turning EN1A Steel on a CNC L...IRJET Journal
This document summarizes an experiment to optimize surface roughness parameters when turning EN1A steel on a CNC lathe with coolant. The experiment uses Taguchi methods to design the experiment with three factors (cutting speed, feed rate, and depth of cut) at three levels each, for a total of nine experiments. Analysis of variance is used to analyze the results and determine that feed rate has the highest contribution to surface roughness at 68.56%, followed by cutting speed at 18.98% and depth of cut at 12.46%. Regression and general linear models are developed to model the relationship between the input and output parameters. The results provide optimal cutting conditions and are useful for manufacturing industries to improve surface finish.
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.
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.
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.
Optimization of input parameters of cnc turning operation for the given compIAEME Publication
This document summarizes a study that used Taguchi methods to optimize cutting parameters (spindle speed, feed rate, depth of cut) for CNC turning of an aluminum alloy component. The goals were to minimize surface roughness and dimensional variation. An L9 orthogonal array experiment was conducted, varying the three parameters at three levels each. Surface roughness and dimensional tolerance measurements were used as quality metrics. Analysis found that spindle speed most impacts dimensional variation while feed rate most influences surface roughness. The optimal combination of cutting parameters was identified to improve both surface roughness and dimensional tolerance.
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.
OPTIMIZATION OF TURNING PROCESS PARAMETER IN DRY TURNING OF SAE52100 STEELIAEME Publication
This document summarizes an experiment to optimize surface roughness and material removal rate during dry turning of SAE52100 steel. The experiment varied cutting speed, feed rate, and depth of cut using a Taguchi L9 orthogonal array. Surface roughness increased with increasing feed rate and decreasing cutting speed. Material removal rate models were developed that showed it increases with cutting speed and depth of cut but decreases with feed rate. Analysis found feed rate has the greatest influence on surface roughness, while depth of cut most influences material removal rate. The goal of the experiment was to determine optimal machining parameters that minimize surface roughness and maximize material removal rate and productivity during dry turning of SAE52100 steel.
Effects of the Cutting Conditions and Vibration on the Surface Roughness of E...IRJET Journal
The document presents the results of a study investigating the influence of cutting parameters (spindle speed, axial depth of cut, feed rate) and machining vibration on surface roughness in an end milling process of aluminum alloy. Regression analysis was used to establish mathematical models for predicting surface roughness under various cutting conditions. The results show that accounting for machining vibration in the model improves the correlation between predicted and measured surface roughness values compared to a model using only cutting parameters. This suggests vibration greatly influences cutting quality and is an important parameter for prediction models.
Analysis of process parameters in dry machining of en 31 steel by grey relati...IAEME Publication
This document summarizes a study that optimized surface roughness and material removal rate when dry turning the steel alloy EN-31. Experiments were conducted using carbide inserts with cutting speed, feed rate, and depth of cut as controllable variables. Taguchi's design of experiments and Grey relational analysis were used to optimize surface roughness. The literature review found that feed rate is often the most influential factor on surface roughness in hard turning steel alloys like EN-31. The goal of the study was to determine optimal machining parameters in dry turning of EN-31 to improve productivity for small and medium industries in India.
ANALYSIS OF PROCESS PARAMETERS IN DRY MACHINING OF EN-31 STEEL by GREY RELATI...IAEME Publication
This paper presents the optimization of surface roughness & material removal rate in dry turning of EN-31 steel.Carbide inserts were used for machining of EN-31 to study effects of process parameters [Cutting speed (S), Feed (F) and depth o f cut (d)]. These models can be effectively used to predict the surface roughness (Ra) of the workpiece. The big challenge of the Micro, small& medium industries in India for achieving high quality products with increased productivity.Paper presents work of an investigation of turning process parameters on EN-31 material, for optimization of surface roughness, material removal rate.The experiment is carried out by considering three controllable input variables namely cutting speed, feed rate, and depth of cut.The design of experiment and optimization of surface roughness is carried out by using Taguchi L9 orthogonal array & Grey Relational analysis.
This document presents a comparative analysis of surface roughness and material removal rate during milling of AISI 410 steel and aluminum 6061. Experiments were conducted using a CNC milling machine varying spindle speed, feed rate, and depth of cut. Response surface methodology was used to optimize surface roughness. The results showed that for AISI 410 steel, spindle speed had the greatest effect on material removal rate and surface roughness, while for aluminum 6061, no parameters significantly affected the responses. Overall, different milling parameters impacted the materials differently in terms of surface finish and productivity.
Milling machining GFRP composites using grey relational analysis and the resp...IRJET Journal
This document summarizes research on optimizing the milling machining process for glass fiber reinforced polymer (GFRP) composites. The researchers used a Taguchi experimental design and Grey Relational Analysis (GRA) to determine the optimal machining parameters that minimize machining force and surface roughness. Their results showed that at optimal levels for spindle speed, feed rate, depth of cut, and cutting tool type, machining force decreased from 17.19N to 15.92N and surface roughness improved. Analysis of variance found that cutting tool type had the greatest influence on machining force. The researchers concluded that Taguchi and GRA methods can effectively optimize composite machining outcomes.
This document summarizes a research paper that investigated and optimized turning process parameters for machining hardened EN31 steel under wet and minimum quantity lubrication (MQL) systems. The paper studies the effects of cutting speed, feed rate, depth of cut, and insert nose radius on surface roughness, material removal rate, and machining time. Experiments were conducted to analyze chip formations and measure chip thickness, color, and velocity to determine their effects on insert wear and product quality. The research aims to identify the lubrication system that achieves higher productivity while maintaining high surface finish. Response surface methodology and central composite design were used to design the experiments, analyze results, and optimize turning parameters to reduce machining time and waste.
Analysis of Surface Roughness for Cylindrical Stainless Steel Pipe (Ss 3163) ...IRJET Journal
This document discusses using artificial neural networks (ANN) to predict surface roughness in cylindrical stainless steel pipes machined using CNC lathe turning. Surface roughness is an important quality metric that is influenced by machining parameters like cutting speed, feed rate, depth of cut, and tool geometry. The document reviews previous research applying ANN and other methods to model surface roughness. It then describes an experiment using ANN to develop a model relating machining parameters to surface roughness measured from turning 316L stainless steel pipes on a CNC lathe. The results indicate ANN is an effective method for accurately predicting surface roughness based on cutting conditions.
Taguchi based Optimization of Cutting Parameters Affecting Surface Roughness ...IRJET Journal
This document summarizes a study that used the Taguchi method to optimize cutting parameters (speed, feed rate, depth of cut) for minimizing surface roughness during CNC dry turning of 16MnCr5 steel. Experiments were conducted based on an L27 orthogonal array with three factors at three levels. Analysis of variance (ANOVA) was used to determine the percentage contribution of each factor on surface roughness. Results showed that depth of cut had the highest influence on surface roughness, followed by speed and then feed rate.
Turning Parameter Optimization for Material Removal Rate of AISI 4140 Alloy S...IRJET Journal
1. The document analyzes the optimization of turning parameters for material removal rate when machining AISI 4140 alloy steel.
2. Experiments were conducted using different levels of spindle speed, feed rate, and depth of cut. Material removal rate was calculated and analyzed using Taguchi methods.
3. Analysis of variance found feed rate to be the most influential parameter on material removal rate, followed by depth of cut and then spindle speed. The optimal combination for maximum material removal rate was found to be a spindle speed of 2100 rpm, feed rate of 0.3 mm/rev, and depth of cut of 0.6 mm.
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
Optimization of Metal Removal Rateon Cylindrical Grinding For Is 319 Brass Us...IJERA Editor
Cylindrical grinding is one of the most important metal cutting processes used extensively in the Metal finishing operations. Metal removal rate and surface finish are the important output responses in the production with respect to quantity and quality respectively. The objective of this paper is to arrive at the optimal grinding conditions that will maximize metal removal rate when grinding IS 319 brass. Empirical models were developed using design of experiments by Taguchi L9 Orthogonal Array and the adequacy of the developed model is tested with ANOVA.
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- Determining the Effect of Cutting Parameters in CNC TurningIRJET Journal
This document discusses a study that aims to determine the effect of cutting parameters in CNC turning. The study analyzes the effects of spindle speed, feed rate, depth of cut, and material type on surface roughness and material removal rate during CNC turning operations. Experiments were designed using Taguchi's orthogonal array and analyzed using ANOVA. The results showed that spindle speed and feed rate significantly affect surface roughness, while depth of cut significantly affects material removal rate. Optimal parameters were identified for minimum surface roughness and maximum material removal rate.
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Experimental Analysis & Optimization of Cylindirical Grinding Process Parameters on Surface Roughness of En15AM Steel
1. Sandeep Kumar Int. Journal of Engineering Research and Applications www.ijera.com
ISSN: 2248-9622, Vol. 5, Issue 7, (Part - 2) July 2015, pp.01-08
www.ijera.com 1 | P a g e
Experimental Analysis & Optimization of Cylindirical Grinding
Process Parameters on Surface Roughness of En15AM Steel
Sandeep Kumar *, Onkar Singh Bhatia**
*(Student of Mechanical Engineering), (M.Tech.), Green Hills Engineering College/ Himachal Pradesh
Technical University (H.P.), INDIA)
** (Associate Professor, Department of Mechanical Engineering, Green Hills Engineering College, Kumarhatti,
Solan (H.P.), INDIA)
ABSTRACT
As per the modern Industrial requirements, higher surface finish mechanical components and mating parts with
close limits and tolerances, is one of the most important requirement. Abrasive machining processes are
generally the last operations performed on manufactured products for higher surface finishing and for fine or
small scale material removal. Higher surface finish and high rate of removal can be obtained if a large number of
grains act together. This is accomplished by using bonded abrasives as in grinding wheel or by modern
machining processes. In the present study, Taguchi method or Design of experiments has been used to optimize
the effect of cylindrical grinding parameters such as wheel speed (rpm), work speed, feed (mm/min.), depth of
cut and cutting fluid on the surface roughness of EN15AM steel. Ground surface roughness measurements were
carried out by Talysurf surface roughness tester. EN15AM steel has several industrial applications in
manufacturing of engine shafts, connecting rods, spindles, studs, bolt, screws etc. The results indicated that
grinding wheel speed, work piece speed, table feed rate and depth of cut were the significant factors for the
surface roughness and material removal rate. Surface roughness is minimum at 2000 r.p.m. of grinding wheel
speed , work piece speed 80 rpm, feed rate 275 mm/min. and 0.06 mm depth of cut.
Keywords-Cylindrical Grinding, Process parameters, Surface roughness measurement, Taguchi method,
ANOVA methodology.
I. INTRODUCTION
Grinding is a small scale material removal
surface finishing process operation in which the
cutting tool is an individual abrasive grain of an
irregular geometry and is spaced randomly along the
periphery of the wheel. The average rake angle of the
grains is highly negative, typically -60 degree or
lower, consequently the shear angle are very low.
The cutting speeds of grinding wheels at very high,
typically on the order of 30 m/s. Grinding are the
machining processes which improve surface quality
and dimensional accuracy of work piece. [1]
There are various process parameters of a
cylindrical grinding machine that include grinding
wheel speed, work piece speed, table feed, depth of
cut, material hardness, grinding wheel grain size, no.
of passes and material removal rate. Work piece
Speed and feed rate are very important factor
because increasing the both speed and feed rate has
negative impact on surface roughness but high
material removal cause reduction in surface
roughness. [2]
Surface roughness is one of the most important
requirements in machining process, as it is
considered an index of product quality. It measures
the finer irregularities of the surface texture.
Achieving the desired surface quality is critical for
the functional behavior of a part. Surface roughness
influences the performance of mechanical parts and
their production costs because it affects factors such
as friction, ease of holding lubricant, electrical and
thermal conductivity, geometric tolerances and
more. The ability of a manufacturing operation to
produce a desired surface roughness depends on
various parameters. The factors that influence
surface roughness are machining parameters, tool
and work piece material properties and cutting
conditions. For example, in grinding operation the
surface roughness depends on depth of cut, material
hardness, work piece speed, grinding wheel grain
size, no. of pass, material removal rate and grinding
wheel speed and on the mechanical and other
properties of the material being machined. Even
small changes in any of the mentioned factors may
have a significant effect on the produced surface. [3]
Therefore, it is important for the researchers to
model and quantify the relationship between
roughness and the parameters affecting its value.
The determination of this relationship remains an
open field of research, mainly because of the
RESEARCH ARTICLE OPEN ACCESS
2. Sandeep Kumar Int. Journal of Engineering Research and Applications www.ijera.com
ISSN: 2248-9622, Vol. 5, Issue 7, (Part - 2) July 2015, pp.01-08
www.ijera.com 2 | P a g e
advances in machining and materials technology and
the available modeling techniques. [4]
Grinding is traditionally a finishing process
employed to apply high quality surfaces to a work
piece. This was possible due to the increased number
of cutting edges present on a grinding wheel over
that of conventional single point cutting tools. The
relationship between cutting condition and the
surface finish of the work piece has been establish
and verified through series of studies. Grinding
wheel consist of power driven grinding wheel driven
at the required speed and a bed with a fixture to
guide and hold the work piece. The grinding head
can be controlled to travel across the fixed work
piece or the work piece can be moved whilst the
grind head stay in fixed position. Grinding, as a
complex machining process with large numbers of
parameters influencing each other, can be considered
as a process where the grinding wheel engage with
the work piece at a high speed. To achieve better
process control a model is required to predict and
demonstrate the whole life cycle performance in
relation to the process input parameters. [5]
With increase is in grinding wheel speed, table feed,
and work piece speed showed improvement in
surface roughness and material removal rate on
En15AM steel [6].
The authors found that the depths of cut and
work piece speeds are significant. Parameter work
piece speed, Grinding wheel speed and table feed
among these factors are found more significant
whereas the depth of cut and number of passes are
found less significant during grinding of EN15AM
steel [7].
Temperature rise in grinding is an important
consideration because it can adversely affect surface
properties and casual residual stresses on the work
piece. It is found from the previous researches that
the use of pure oil decreases the grinding force,
specific energy, and acoustic emission and
roughness values. These characteristics result from
the high lubricating power of pure oil, which
decreases the friction and reduces the generation of
heat in the grinding zone. Therefore, pure oil used as
a grinding fluid to obtain high quality superficial
dressing and lower tool wear is the best choice for
industrial applications [8]
Cutting fluid like water soluble oil gives better
surface finish than pure oil used because the water
mixed oil has lesser viscosity and more flow rate
which results smoothing action during grinding
process on EN15AM steel [9]
II. OBJECTIVE OF PRESENT
INVESTIGATION
To analyze the effect of cylindrical grinding
process parameters like grinding wheel speed, work
piece speed, table feed, depth of cut, conditions, and
optimize for enhancement of surface finish and effect
on surface roughness on EN15AM steel.
III. EXPERIMENTATION
The work piece material EN15AM selected as
work piece material having diameter 30 mm and
length 380 mm round bar was used. This steel is
widely used in industrial application like engine
shafts, spindles, connecting rods, studs, screws etc
for its good mechanical properties. The chemical
composition of EN15AM steel is shown in Table1.
The round bar was cut into pieces each having
approximate length of 380 mm. The work piece was
turned to a diameter of 28.5 mm using centre lathe
machine, and the work piece was divided into 3
equal parts of 126.7 mm each. The surface
roughness of work piece was measured before
grinding at each region with the help of Surface
Roughness Tester shown in Figure 4.1. To minimize
the error, three reading have been taken for each
region. Average values of three readings were taken
for record.
Table 1 Chemical Composition (in weight %)
After turning operation of work piece on centre lathe
machine, the next step was grinding. GG-600
universal cylindrical grinding machine was used for
the experimentation as shown in fig. 3.1. Process
parameters like speed of work piece, grinding wheel
speed, feed rate and depth of cut were used as input
parameters. And other parameter, condition of
grinding (wet condition) was kept constant. The
surface roughness was taken as response. The work
pieces prepared after grinding process are shown in
fig.3.2.
Table 2 Assigned values of input machining
parameters at different levels and their designation
Assigned values of input machining parameters at
different levels and their designation are shown in
C Mn S i Ni Mo Cr S P
0.3 - 0.4 1.3–1.7 0.25 …… …… …… 0.12-0.20 0.06
Factor
Design
ation
Parameters (units) LevelsandcorrespondingvaluesofMachiningparameter
Level
1
L e v e l
2
Level
3
A GrindingwheelSpeed(rpm) 1 8 0 0 1 8 0 0 200 0
B Workpiece spindleSpeed(rpm) 8 0 1 5 5 3 2 4
C Tablefeed(mm/min.) 1 0 0 1 7 5 2 7 5
D Depth of cut (mm) 0 . 0 2 0 . 0 4 0 . 0 6
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Table 2. Taguchi design of experiment was used for
optimizing the input parameters using L18 (21
x 33
)
orthogonal array which has been shown in Table 3
Fig. 3.1 G.G.-600 Universal Cylindrical grinding
machine
Fig.3.2 Prepared Work pieces after cylindrical
Grinding Process
Table 3Design Matrix of L18 (21
x 33
) orthogonal
array
Exp.No. GrinderSpeed(rpm) Workpiecespeed(rpm) FeedRate(Mm/min.) Depth of Cut (mm)
1 1 8 0 0 8 0 1 0 0 0 . 0 2
2 1 8 0 0 8 0 1 7 5 0 . 0 4
3 1 8 0 0 8 0 2 7 5 0 . 0 6
4 1 8 0 0 1 5 5 1 0 0 0 . 0 2
5 1 8 0 0 1 5 5 1 7 5 0 . 0 4
6 1 8 0 0 1 5 5 2 7 5 0 . 0 6
7 1 8 0 0 3 2 4 1 0 0 0 . 0 4
8 1 8 0 0 3 2 4 1 7 5 0 . 0 6
9 1 8 0 0 3 2 4 2 7 5 0 . 0 2
1 0 2 0 0 0 8 0 1 0 0 0 . 0 6
1 1 2 0 0 0 8 0 1 7 5 0 . 0 2
1 2 2 0 0 0 8 0 2 7 5 0 . 0 4
1 3 2 0 0 0 1 5 5 1 0 0 0 . 0 4
1 4 2 0 0 0 1 5 5 1 7 5 0 . 0 6
1 5 2 0 0 0 1 5 5 2 7 5 0 . 0 2
1 6 2 0 0 0 3 2 4 1 0 0 0 . 0 6
1 7 2 0 0 0 3 2 4 1 7 5 0 . 0 2
1 8 2 0 0 0 3 2 4 2 7 5 0 . 0 4
IV. RESULTS AND DISCUSSIONS
4.1 Surface roughness results : After
cylindrical grinding, Surface roughness values at
each region were measured by using Surftest-4,
L.C.-0.1µm surface roughness tester .Three reading
were taken on each region and the average of them
was taken to minimize the error. Figure 4.1 shows
the Surftest-4 surface roughness tester which was
used for measurement of surface roughness. The
experimental results for surface roughness obtained
using Taguchi optimization technique are given in
Table 4.
Figure 4.1 Mitutoyo - Surf test–4, L.C.-0.1µm
surface roughness tester
4.2. Analysis of Variance: The results for surface
roughness (SR) are analyzed using ANOVA in
Minitab 17 software. As lower value of surface
roughness is the requirement in experimentation so
the criterion for evaluation "smaller is better" is
used. The interaction plot for SN ratio is shown in
figure 4.2.1. Table 5 summarizes the information of
analysis of variance and case statistics for further
interpretation.
Smaller is better S/N = -10 log [1/n (Σyi2)] (n=1)
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Figure 4.2.1 Interaction plot for SN ratios
Figure 4.2.1 Interaction plot for SN ratio clearly
indicates that the value of surface finish is
minimum at first level of work piece speed i.e. 80
rpm and table feed rate i.e. 100 mm/min., as the
feed rate is increased to 175 mm/min., the surface
finish of the work piece is also increased. While the
table feed is increased to 275rpm, the surface finish
of work piece is declined because as the feed rate
increases the work piece doesn’t get proper time
for process. At second level, the value of surface
finish is higher at 155 rpm of wok piece speed and
100 mm/min. of table feed; further increase in the
value of feed rate, surface roughness also
decreases. At third level of work piece speed i.e.
324rpm, surface finish remains constant.
Interaction of feed rate and depth of cut, it indicates
that the value of surface finish is higher at 0.04
depths of cut and 100mm/min. Feed rate at first
level, 0.02 depth of cut and 175 mm/min. feed rate
at second level and 0.04 depth of cut and 275
mm/min. feed rate at second level. Interaction of
work piece speed and feed rate indicates that the
value of surface finish is higher at 155 rpm work
piece speed and 100 mm/min table feed at first
level, 324 rpm and 175 mm/min. At second level
and 324 rpm and 275 mm/min. at third level.
Interaction of work piece speed and depth of cut
indicates that the surface finish is higher at 155 rpm
work speed and 0.02mm depth of cut at first level,
at second level surface finish is higher at 324 rpm
of work piece speed and 0.04 mm depth of cut, at
third level higher surface finish value obtained at
324 rpm of work piece speed.
Main effect plots for the surface roughness figure
4.2.3 indicates very clearly that the 2nd
level of
Grinding wheel speed i.e. 2000 rpm , 1st
level of
work piece speed i.e. 80 rpm , 3rd
level of feed
rate i.e. 275 Mm/min. and 3rd
level of depth of cut
i.e.0.06 mm are the optimum values for the
minimum surface roughness. The level and the
values at which surface roughness is minimum has
been obtained are given in Table7.
Workpiece speed
-4
-6
-8
Feed Rate
-4
-6
-8
Depth of Cut
0.060.040.02
275175100
32415580
-4
-6
-8
Workpiece
324
speed
80
155
Feed
275
Rate
100
175
Depth
0.06
of
Cut
0.02
0.04
Interaction Plot (data means) for SN ratios
Signal-to-noise: Smaller is better
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Table 5 Analysis of Variance for means of SN ratio for Surface Roughness (Smaller is Better)
S o u r c e D F Seq SS Adj SS Adj MS F P PercentageContribution
Grinding wheel Speed 1 1 6 . 4 8 1 1 6 . 4 8 1 1 6 . 4 8 1 3 0 . 8 6 0 . 0 3 1 4
2 2 . 9 5
Work piece speed 2 1 1 . 8 3 1 1 . 8 5 5 . 9 2 5 1 1 . 0 9 0 . 0 8 2 7
1 6 . 4 7
Feed rat e 2 1 0 . 2 4 5 1 0 . 2 4 5 5 . 1 2 2 9 . 5 9 0 . 0 9 4 4
1 4 . 4 6
Depth of cut 2 1 3 . 2 2 0 1 3 . 8 4 1 6 . 9 2 0 1 2 . 9 5 0 . 0 7 1 7
1 8 . 4 0
WorkpieceSpeed*FeedRate 4 9 . 1 7 3 1 1 . 4 4 9 2 . 8 6 2 5 . 3 5 0 . 1 6 3 6
1 2 . 7 7
WorkpieceSpeed*DepthofCut 4 9 . 7 9 2 9 . 7 9 2 2 . 4 3 2 4 . 5 5 0 . 1 8 8 2
1 3 . 6 3
Residual Error 2 1 . 0 6 8 1 . 0 6 8 0 . 5 3 4
1 . 4 8
T o t a l 1 7 7 1 . 8 0 8
1 0 0 . 0 0
Figure 4.2.2 Percentage contributions of parameters towards surface roughness
Table 6 Response Table for Signal to Noise Ratios Smaller is better
L e v e l Grinding wheel Speed Work piece speed F e e d r a t e Depth o f cut
1 - 6 . 4 1 0 - 7 . 7 6 2 - 6 . 5 2 7 - 6 . 4 8 3
2 - 7 . 8 9 9 - 6 . 8 2 2 - 7 . 3 4 0 - 7 . 2 5 6
3 - 6 . 8 8 0 - 7 . 5 9 7 - 7 . 7 2 5
D e l t a 1 . 4 8 9 0 . 9 4 0 1 . 0 7 0 1 . 2 4 2
R a n k 1 4 3 2
0
5
10
15
20
25
30
35
1 2 3 4 5 6 7 8
Grinding wheel Speed
Work piece speed
Feed rate
Depth of cut
Work piece Speed*Feed Rate
Work piece Speed*Depth of Cut
Residual Error
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Figure 4.2.3 Main effects plot for means SN ratios (Surface Roughness)
Table 7 Levels and values of input parameters at minimum Surface Roughness
F a c t o r Grinding wheel Speed(rpm) Work piece speed(rpm) Feed rate (mm/min.) Depth of cut (mm)
L e v e l 3 1 3 3
V a l u e s 2 0 0 0 8 0 2 7 5 0 . 0 6
4.3 Confirmation of experiment: Predicted
values of means were investigated using
conformation test .The experimental values and
predicted values are given in the Table 8. Since the
error between experimental and predicted value for
surface roughness is 2.94 % it is clear from the
literature that if percentage of error between the
predicted data and the actual data is less than 10%
then the experimental work is said to be
satisfactory.
Table 8 Confirmation test result and comparison
with predicted result as per model
CONCLUSION
Based on the analytical and experimental results
obtained by Taguchi method, in this study
following conclusions can be drawn:
1. The various input parameters of cylindrical
grinding such as the work piece speed,
grinding wheel speed and feed rate has more
significant effect for surface roughness and
depth of cut has least effect on surface
roughness of EN15 AM steel.
2. The optimized parameters for minimum
surface roughness are grinding wheel speed
2000 rpm, work piece speed 80 rpm, feed rate
275 mm/rev and depth of cut 0.06 mm.
3. The optimized minimum surface roughness is
0.99 µm which is about 76 % of initial value.
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8. Sandeep Kumar Int. Journal of Engineering Research and Applications www.ijera.com
ISSN: 2248-9622, Vol. 5, Issue 7, (Part - 2) July 2015, pp.01-08
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