International Journal of Innovative and Emerging Research in Engineering
Volume 3, Issue 5, 2016
Available online at www.ijiere.com
International Journal of Innovative and Emerging
Research in Engineering
e-ISSN: 2394 – 3343
p-ISSN: 2394 – 5494
Review on Estimation of Tool Wear Rate in Orthogonal
Cutting Using Experimental and Statistical Approach
S.V.SONAWANEa, B.R.BORKARb and P.B.WAKCHAUREc
a
PG (ME) Student, Production Engg. AVCOE, Sangamner and India
Associate Proffesor , Production Engg. AVCOE, Sangamner and India
c
Assistant Professor, Production Engg. AVCOE, Sangamner and India
b
ABSTRACT:
This study presents a new methodology to estimate tool wear rate in orthogonal cutting based on experimental
data and statistical approach. In metal cutting tool wear is strongly influenced by cutting forces, speed, feed, and
depth of cut. Based on these variables and cutting forces measured by dynamometer, tool wear is estimated with
desired accuracy.
The major objective of this study is to develop a model (equation) to predict the tool wear in orthogonal
cutting by regression analysis. The work presented in this paper uses the data of conducted experiments. This
data is statistically analyzed to develop a model, which can predict the wear rate of cutting tool used in orthogonal
cutting operation considering different machining variables such as, spindle speed, depth of cut, feed. The cutting
forces predicted by the equation (model) is closely matching with those with results obtained experimentally. So
based on another statistical equation tool wear rate is estimated over the wide range of speed, feed and depth of
cut values required for different types of machining operations. The proposed methodology can be used for
developing another model which will predict the tool wear rate for other machining processes.
Keywords: Toll life, Tool wear, Orthogonal cutting, FEA Etc.
I. INTRODUCTION
1.1 Definition:
Tool wear is defined as change of shape of the tool from its original shape, during cutting, resulting from the
gradual loss of tool material.
Cutting tools are subjected to an extremely severe rubbing process. Under conditions of very high stress at high
temperature, then they are in metal-to-metal contact between the chip and workpiece. The situation is further aggravated
due to the situation of extreme stress and temperature gradients near the surface of the tool.
When during machining, cutting tools are remove material from the component to achieve the required shape, size
and surface roughness . Then, wear occurs during the cutting action, and it will ultimately result in the failure of the cutting
tool. When the tool wear go to a certain extent, the tool or active edge has to be replaced to guarantee the desired cutting
action.
1.2 Tool wear phenomena
The high contact stress into the tool rake-face and the chip causes severe friction at the rake face, as well, there is
friction into the flank and the machined surface. The result is a variety of wear patterns and scars which can observed at
the rake face and the flank face.
Fig.1.1 tool wear phenomena
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1.3functional elements influencing tool wear
Tool wear has a high influence on the economics of the machining operations. Thus, knowledge of tool wear
mechanisms and capability of predicting tool life are very important and necessary in metal cutting. A view of the functional
elements that affect the wear of a cutting tool is clearly in fig. 1.2 and can be summarized in four major groups, as follows:
1.
The physical properties and its workpiece material (mechanical and thermal properties, microstructure, hardness,
etc.), which calculate cutting forces and energy for the applied cutting conditions.
2.
The interface conditions: in 80-82% of the industrial cutting applications, then coolants are used to decrease
cutting temperatures and likely reduce tool wear. Increasingly some new technologies, such as the minimum liquid
lubrication, have been developed to reduce the cost of coolant that makes up to 15-16% of the total machining
costs.
The cutting tool: tool parameters such as tool material, coatings, and geometric design (edge preparation, rake
angle, etc.) Need to be appropriately chosen for different operations (roughing, semi-roughing, or finishing etc.).
3.
4.
The dynamic function of the machine tool, affected by the machine tool structure and all components taking part
in the cutting process, play an important role for successful cutting. An unsatble cutting processes with very large
vibrations (chatters) result in a fluctuating overload on cutting tool and often lead to the direct failure of the cutting
edge by tool chipping and excessive tool wear
.
Fig.1.2. Four major functional elements influencing tool wear in machining processes. [1]
Literature SurveyIn this chapter an overview of different literatures in this context is given.ghani et. Al. [2], in their study presents
a new concept for detecting the cutting tool wear based on the measured cutting force signals. A statistical-based method
is called as an integrated kurtosis-based algorithm for z-filter technique, i-kaz was used for developed regression model
and 3d graphic are presentation of i-kaz 3d coefficient during machining process. The machining tests were carried out on
a cnc lathe turning machine colchester master tornado t4 in dry cutting condition, and kistler 9255b dynamo meter was
used to measure the cutting force, which then stored and displayed in the daisy lab software.
A number of force signals from machining was analyzed and an each has a characteristic value called i-kaz 3d
coefficient. These coefficients have relationship with for flank wear land (vb). Results of regression model shows the i-kaz
3d coefficient value decreases when the tool wears increases. This result can be used for real time tool wear monitoring.This
paper is presented by huang, et. Al.[3], in journal of industrial technology. In the actual manufacturing world, most of the
cnc machines cannot detect the tool conditions in an on-line manner. Because a broken tool may continue functioning
without any detected, the materials costs will increase and the quality of products diminish as errors are made by the
broken tool inprocess. To reduce the materials costs and prevent damage to the cutting tool, a detecting technology of
unmanned, on-line tool breakage detection system is necessary (lan and naerheim, 1986). However, to be successful in
developing a new detecting system, it is necessary to implement sensing technology. There are two major an approaches
using sensing technology for detecting tool breakage: one is the direct method, which measures and an evaluates the
volumetric change in the tool, and the other is the indirect method, which measures the cutting parameters are during the
operation process. The indirect method can work as an on-line technique because it measures the cutting parameters during
the operation process. To detect the tool breakage immediately, the indirect sensing technology are recommended. The
detection of tool breakage in the milling operations with sensing technology has been widely studied in previous research.
Most of the research utilized the principle of vibration and cutting force signals to diagnose the tool condition.
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Tyan et. Al. [6], in their study presents the orthogonal metal cutting process for a controlled contact tool is
simulated using a limit are analysis theorem. The basic principles are stated in the form of a primal optimization problem
with an objective function subjected to constraints of the equilibrium equation, its static boundary conditions and a
constitutive inequality. Eulerian reference co-ordinate is used to describe the steady state motion of the workpiece relative
to the tool. Based on a duality theorem, a dual functional bounds the objective functional of the primal problem from above
by a sharp inequality. The dual formulation seeks the least upper bound and thus recovers the maximum of the primal
functional theoretically. A finite element an approximation of the continuous variables in the dual problem reduces it to a
convex programming. Since the an original dual problem admits discontinuous solutions in the form of bounded variation
functions, must care be taken in the finite element approximation of account for such a possibility. This accomplished by
a combined smoothing and successive approximation an algorithm. Convergence is robust from any initial iterate. Results
are obtained for a wide range of control parameters are cutting depth, rake angle, rake length and friction. The converged
solutions provide an information on cutting force, chip thickness, chip stream angle and shear angle which agree well both
in values and trend with the published all data. But the available data represent only a small subset in the range of
parameters an exhaustively investigated in this paper. This paper is presented by ravindra thamma.[7], critical quality
measure and surface roughness (ra) in mechanical parts depends on turning parameters during the turning process.
Researchers have predicted and developed various models for the optimum turning parameters for required surface
roughness.
This study focuses on comparing multiple regression models by collecting data pertaining to depth of cuts, nose
radii, feed rates, surface roughness, and cutting speeds during the turning operation for an aluminium 6061 workpieces.
The conducted analyses show the behavior of turning parameters and high accuracy levels of the models to predicted
surfaces. In this work, mustafa et, al [8], presented the geometric tolerance and surface quality of an aluminium piece
produced by turning is analysed. The effect of the length and diameter of working piece, cutting depth and feed were also
investigated. The cutting speed, which is an important machining parameter, was kept constant in this study. Going from
past works experience the effect of cutting speed was ignored. Statically method of taguchi was used in this work in order
to obtain more reliable and optimum results. By this method, time and cost savings were made, and the test results were
optimized. The relation between the dependent and independent variables were also modelled by regression analysis. The
results showed that cutting force, surface roughness, cylindricity and vibration were minimised in machining process and
production quality was improved.
This experimental study is conducted to determine statistical models of cutting forces in hard turning of aisi h11
hot work tool steel (∼ 50 hrc). This steel is free from tungsten on cr–mo–v basis, insensitive to temperature changes and
having a high wear resistance. It is employed for the manufacture of highly stressed diecasting moulds and inserts with
high tool life expectancy, plastic moulds subject to high stress, helicopter rotor blades and forging dies. The workpiece is
machined by a mixed ceramic tool (insert cc650 of chemical composition 70%al2o3+30%tic) under dry conditions. Based
on 33 full factorial design, a total of 27 tests were carried out. The range of each parameter is set at three different levels,
namely low, medium and high. Mathematical models were deduced by software minitab (multiple linear regression and
response surface methodology) in order to express the influence degree of the main cutting variables such as cutting speed,
feed rate and depth of cut on cutting force components. These models would be helpful in selecting cutting variables for
optimization of hard cutting process. The results indicate that the depth of cut is the dominant factor affecting cutting force
components. The feed rate influences tangential cutting force more than radial and axial forces. The cutting speed affects
radial force more than tangential and axial forces. [9]
Astakhov et, al, [10], conducted experimental study to assessment and proper reporting of the tool wear rates.
Abstract most published studies on metal cutting process regard the cutting speed as having the greatest influence on tool
wear and, thus, tool life, other parameters and characteristics of the cutting process have not attracted as much attention in
this respect. This is because of existence of a number of contradicting results on the influence of the cutting feed, depth of
cut, speed and workpiece (bore) diameter. The present paper discusses the origin of the aforementioned contradicting
results. It an argues that, when the optimal cutting temperature is considered, the influence of the aforementioned
parameters on tool wear becomes clear and straight. The obtained results reveal the true influence of the cutting feed,
diameter of the workpiece, and diameter of the hole do bored on the tool wear rate. It was also found that the depth of cut
does not have a significant an influence on the tool wear rate. The obtained results provide methodological help in the
experimental and proper reporting of the tool wear rates studied under different cutting conditions.
II. CONCLUSIONS
A successful monitoring system for conventional machining operations has the potential to reduce cost, guarantee
consistency of product quality, improve productivity and provide a safe environment for the operator. It is very important
to develop a reliable and inexpensive monitoring system for use in cutting processes. A successful monitoring system can
effectively maintain related machine tools, cutting tool and workpiece. Research to date has shown that there are four
parameters, including cutting force, speed,acoustic emission, motor power/current and vibration, which could be used to
monitor tool wear condition in real time during turning process.
In this paper a conclude that how to presented for the estimation of flank wear in turning operations from force
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measurements under conditions where one of the cutting parameters (i.e., depth or feed or speed) exhibits stepwise
variations. The key idea in the method is to employ statistical model for parameter estimation method together with a
simple model of the relationship between the measured force and the flank wear.
REFERENCES
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Blaine Lilly a, Taylan Altan a,∗ Journal of Materials Processing Technology 146 (2004) 82–91 )
[2] “Statistical Analysis for Detection Cutting Tool Wear Based on Regression Model” (Jaharah A. Ghani, Muhammad
Rizal, Mohd Zaki Nuawi, Che Hassan Che Haron, Rizauddin Ramli).
[3] “A Statistical Approach in Detecting Tool Breakage in End Milling Operations” (Journal of Industrial Technology •
Volume 15, Number 3 • May 1999 to July 1999)
[4] “Determination and optimization of the effect of cutting parameters and workpiece length on the geometric tolerances
and surface roughness in turning operation” (International Journal of the Physical Sciences Vol. 6(5), pp. 1074-1084,
4 March, 2011 Available online at ISSN 1992 - 1950 ©2011 Academic Journals)
[5] “Tool Wear and Surface Roughness Prediction using an Artificial Neural Network (ANN) in Turning Steel under
Minimum Quantity Lubrication” (World Academy of Science, Engineering and Technology 62 2010 S. M. Ali, and
N. R. Dhar)
[6] “Analysis of orthogonal metal cutting Processes” (T. TYAN* AND WE1 H. YANG, International journal for
numerical methods in engineering, vol. 34, 365-389 (1992)
[7] “Comparison Between Multiple Regression Models to Study Effect of Turning Parameters on the Surface Roughness”(
Ravindra Thamma, Proceedings of The 2008 IAJC-IJME International Conference ISBN 978-1-60643-379-9)
[8] “Determination and optimization of the effect of cutting parameters and workpiece length on the geometric tolerances
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4 March, 2011 A. Y. Mustafa1* and T. Ali2)
[9] “Application of response surface methodology for determining cutting force model in turning hardened AISI H11 hot
work tool steel” (S¯adhan¯a Vol. 36, Part 1, February 2011, pp. 109–
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