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CHAPTER 1

INTRODUCTION

1.1. GENERAL

Development of machine tools forms the basis of the industrial

improvement and has been realized especially better accuracy of machined

parts. Turning is the most widely used among all turning operations is gaining

new dimensions in the present industrial age, in which the growing competition

calls for all the efforts to be directed towards the economical manufacture of

machined parts and surface finish is one of the most critical quality measure in

mechanical products as the competition grows closer, customer now have

increasingly high demands on the quality, making surface roughness one of the

quality, making surface roughness one of the most competitive parameters in

todays manufacturing industry. The quality of machined component is evaluated

by how closely they adhere to set product specifications of length, width, surface

finish etc. Among them surface finish is the central to determining the quality of

workspace. In practice, predicting and controlling the roughness is difficult, which

due to the fact that many variables are affecting the process. Some of these

factors can be controlled and some cannot. Controllable process parameter

include feed, cutting speed, tool geometry and tool setup.

The development within production engineering is accompanied by

increasing quality requirements of the produced work pieces. It is important to

limit vibrations of the machine tool structure as their presence results in poor

surface finish, cutting edge damage, and irritating noise. The causes and control

of free and forced vibrations are generally well understood and the sources of

vibration can be removed or avoided during operation of the machine. Chattervibrations are less easily controlled and metal removal rates are frequently

limited because the operator must stop the machine to improve the machining

conditions, which often means reducing the depth of cut of feed rate. In the

previous researches the steel with less hardness is taken as work piece and the

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experiment is conducted for that work piece, but in this study OHNS (oil

hardened non-shrinkage steel) of hardness 45HRC is taken for the experiment.

Machining parameters affects production rate, quality and cost of a

product. The selection of machining parameters is traditionally carried out by

process planners rather on the basis of their experience or with the help of

machining database. However, the parameters selected by such practice do not

include any economic criterion in a machining process will usually be either to

minimize the production cost or maximize the production rate. Moreover, in

determining the optimal parameters, special attention has to be give to the

constraints imposed on the production operation by machine tools, cutting tool

and work piece.

The challenge of modern machining industries is mainly focused on the

achievement of high quality in terms of work piece, dimensional accuracy,

surface finish, high production rate, less wear on cutting tool, economy of

machining in terms of cost saving and increase the performance of the product

with reduced environmental impact.

1.2. Chatter Vibrations and Damping

The basic cause of chatter is the dynamic interaction of the cuttingprocess and the machine tool structure. During cutting, a force is generated

between the tool and work piece, which acts at an angle to the surface. The

magnitude of this cutting force depends largely on the tool-work engagement and

depth of cut. The cutting force strains the structure elastically and can cause a

relative displacement of the tool and work piece, which alters the tool-work

engagement (un-deformed chip thickness). Chatter is the resonant vibration of

cutting or work piece. The produces the following effects,

1. It increases wear of cutting tool and machine tool

2. Vibration of the machine tool work piece system deteriotes the surface

finish and accuracy.

3. It reduces tool life.

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1.3. Elimination of chatter

It is desirable to reduce chatter in order to improve work piece surface

finish and to protect the machine tool. Self excited vibration are more severe and

has the forced vibrations. Chatter can be reduced by the following methods.

1. Chatter can be reduced by the use of special device such as vibration

dampers which impede the development of vibrations work piece system.

2. Rigid installation of machine tool on its properly prepared foundation

reduces the vibrations.

3. The use of cutting fluids sometimes helps to reduce vibrations.

4. The machine tool should be dynamically balanced to limit the unbalanced

forces produced during its operation.

1.4. Effect of vibration on the cutting conditions

There are mainly three effects on the cutting conditions

1. Chip thickness variation effect.

2. Penetration rate variation effect.

3. Cutting speed variation effect.

1.5. Hard Turning

Hard turning is a cutting process defined as turning materials with

hardness higher than 45 HRC under appropriate cutting tools and high cutting

speed. Machining of hard steel using advanced tool materials, such as mixed

ceramic, has more advantages than grinding or polishing, such as short cycle

time, process flexibility, compatible surface roughness, higher material removal

rate and less environment problems without the use of cutting fluid. High-speed

machining of dies and molds in their hardened state has become a normal

practice in industry because it increased productivity and reduced energy

consumption.

Hard turning is a cost- effective, high productivity and flexible machining

process for ferrous metal work pieces that are often hardened above 40 HRC

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and up to 60 HRC. This process has become a popular technique in

manufacturing of gears, shafts, bearings, cams, forgings, dies and molds. Hard

machining is performed dry using ceramics and polycrystalline cubic boron nitride

(PCBN, commonly CBN) cutting tools due to the required tool material hardness.

Hard turning is a lathe machining process where most of the cutting is done with

the nose of the inserts.

In addition to the effects of work material hardness, tool geometry and

cutting conditions on surface integrity of the finish machined parts. Since hard

turning demands a strong and prudent tool cutting edge, nose design with proper

edge preparation becomes crucial to provide high edge strength as well as to

attain favorable surface roughness. Performance of Ceramic and CBN cutting

tools and the quality of the surfaces machined are highly dependent on cut and

the tool nose radius which significantly influence surface roughness.

1.6. Need for the research

Extensive research has been devoted to the characterization, modeling,

and control of vibrations that occur when machine tools operate at the limit of

their dynamic stability. These vibrations, known as machine-tool chatter, must beavoided to maintain machining tolerances, preserve surface finish, and prevent

tool breakage. To avoid chatter, machine tool users limit material removal rates

in order to stay within the dynamic stability boundary of their machines. From a

manufacturing stand point, chatter is a constraint on the machine-tool user that

limits the available production capacity. Thus, vibration-control methods for

extending machine-tool operating envelopes are highly desirable.

1.8. Objective of the research

1. To determine the vibration spectrum curve using vibration data

collector for various overhanging length of boring bar and also by

varying the speed, feed under dynamic condition .

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CHAPTER 2

LITERATURE REVIEW

2.1. Vibration

L.Petterson, L.Hakanson, I. Claesson, and S. Olsson states that the

knowledge of vibrations involved in boring operations and active control of

external turning operations, have given a good basis for the active control

solution in boring operations. The active control solution is based on a standard

boring bar with an embedded piezo ceramic actuator placed at the peak modal

strain of the boring bar. An accelerometer is also included in the design, mounted

as close as possible to the cutting tool. The control algorithm is a filtered X LMS

algorithm built on a feedback approach since the original excitation, the cutting

process, cannot be observed directly. Preliminary results show reduction of the

vibration in the boring bar by up to 30db.

Damping capacity greatly affects the dynamic rigidity of a machine tool

system. This paper deals with the damping capacity of boring tools. Dampingcapacity is measured as a function of clamping conditions such as clamping

conditions such as clamping load or surface topography of tool shank. An

empirical equation of damping capacity representing the clamping load

dependence is induced for the fundamental mode of vibration in tangential and

normal directions. The optimum clamping load, at which the stability of turning

tool for chatter excitation becomes maximum, is experimentally clarified [2].

Y.Altintas,E.Budak presents a new method for the analytical prediction of

stability lobes in milling. The stability model requires transfer function of the

structure at the cutter-work piece contact zone, static cutting force coefficients,

radial immersion and the number of teeth on the cutter. Time varying dynamic

cutting force coefficients are approximated by their Fourier series components

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and their chatter free axial depth of cuts and spindle speeds are calculated

directly from the proposed set of linear analytical expressions without any digital

iteration. Analytically predicated stability lobes generated by time domain and

another numerical methods available in the literature.

Fedrico M. Anerio, Reginaldo T. Coelho, Lincoln C.Brandao the efficiency

of the high-speed milling process is often limited by the occurrence of chatter. In

order to predict the occurrence of chatter, accurate models are necessary. In

most models regarding milling the cutter is assumed to follow a circular tooth

path. However the real tool path is trochoidal in the ideal case, i.e., without

vibrations of the tool. Therefore, models using a circular tool path lead to errors,

especially when the cutting angle is close to 0 or radians. An updated model

for the milling process is presented which features a model of the unreformed

chip thickness and a time-periodic delay. In combination with this tool path

model, a nonlinear cutting force model is used; to include the dependency of the

chatter boundary on the feed rate. The stability of the milling system, and hence

the occurrence of chatter, is investigated using both the traditional and the

trochoidal model by means of the semi-discrimination method. Due to the

combation of this updated tool path model with a nonlinear cutting force model,the periodic solution of this system, representing a chatter-free process, needs to

be computed before the stability can be investigated. This periodic solution is

computed using a finite difference method for delay- differential equations.

Especially for low immersion cuts, the stability lobes diagram (SLD) using the

updated model shows significant differences compared to the SLD using the

traditional model. Also the use of the nonlinear cutting force model results in

significant differences in the SLD compared to the linear cutting force model. [4]

Xiaolio Li, Alexander Djordjevich, and Patri K. Venuvinod in this part of

the paper series, chatter experiments are conducted in order to verify the

proposed stability models presented in the first part. Turning and boring chatter

experiments are conducted for the cases where the tool or the work piece is the

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most flexible component of the cutting system. In addition, chatter experiments

demonstrating the effect of the insert nose radius on the stability limit are

presented. Satisfactory agreements is observed between the analytical

predictions and the experimental results.[5]

Mohammed Usman Ghani-Nuri A.Abukshim, presents a new method for

varying the spindle speed to suppress chatter in machining. The spindle speed is

varied in a pseudo-random fashion within the bandwidth of the spindle system.

Both implementation issues and spindle system responses to such signals are

investigated. A new method to analyze the stability of machining systems with

varying spindle speed is also introduced. The effectiveness and advantages of

the random spindle speed variation in chatter suppression is verified using

numerical simulations and experiments.

Jing Shi, C.Richard Liu A finite modal is developed to predict the chip formation

and phase transformation in orthogonal machining of hardened AISI 52100 steel

(62HRC) using Poly crystalline Cubic Boron Nitride(PCBN) tools. The model

mainly includes a chip separation criterion based on critical equivalent. Plastic

strain; a coloumbs law for the friction at the tool/chip interface; a thermal analysisincorporating the heat dissipated from inelastic deformation energy and friction;

and an annealing effect model, in which the work hardening effect may be lost or

re-accumulate depending on material temperature. This fully coupled thermal

mechanical finite element analysis accurately simulates the formation of

segmental chips, as verified by experiment. It is found that high temperature

around the secondary shear zone causes fast re-austenitization and martensite

transformation, while other parts of the chips retain the original tempered

martensite structure.

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2.2 Signal Processing

Quality evaluation and control is an almost universal concern in across all

manufacturing sectors. Statistical methods play an important role, as do both

automated and human inspection. Many sensing modalities including electrical

physical, optical, x-ray, acoustical, ultrasound, chemical measurements (M.P.S.

Krishnan Kiran et al., 2007) applied in inspection procedures; many of these

measurements already contain, or could be enchanced by, signal conditioning

and machine monitoring applications. These include auto-regressive (AR)

models, time domain signal envelope analysis and other time-domain methods

such as kurtosis or root-mean-square (RMS) signal power (Alexandria, VA 1996).

The constant false alarm rate (CFAR), ratio of power (ROP), Kurtosis and

correlation of AE have been presented more sensitive than root mean square

(RMS) (Paulo R.Aguiar et al., 2006).

Many paper described the practical aspect of vibration phenomena and

measurement requirements of a general monitoring system consisting of data

collection with data reports in digital manner, followed by the acquisition phase

calculating the statistical values and functions in time and frequency domain withintergrated data reduction by fault and operational pattern (Wilfried Reimche et

al., 2003; Warren Liao T et al., 2007; Steven Y. Liang et al., 2004). AE RMS

frequency and count rate have good correlation with white layer formation and

thus, may be used to monitor surface integrity factors (Guo. Y.B. et al., 2005).

The tool wear forms were correlated to features in the vibrations signals in the

time and frequency domains (Dimla D,E 2002). Signal parameters characterizing

acoustic emission (AE) detected during metal cutting have been theoretically

correlated in a simple manner, to the work material properties, cutting conditions

and tool geometry (Keraita J.N. et al 2000 and Richard Y. Chiou et al., 2000).

Arnuad and Devillez (2006) were discussed the problem of vibration occurring

during a machining operation and signals of tool micro movement were

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correlated with surface finish. Surface roughness has received serious attentions

for many years.

A considerable number of studies have been investigated the general

effects of the speed, feed, and depth of cut, nose radius and others on the

surface roughness. In the present paper, the effects of carbide shim, Brass, shim

and Aluminum shin on surface roughness in turning process are also studies.

Vibration signal are collected using accelerometer during machining process for

different dampers. The surface roughness of the machined workpieces is

measured using surface tester. Features of the amplitude spectrum and

probability density curve are correlated with the measured roughness values.

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CHAPTER 3

METHODOLOGY

Based on the literature review and an examination of prior experimentalstudies, a methodology was developed to study the progression of flank wear of

the cutting tools and the change in the surface roughness of the machined part in

turning. Since the present trend in the manufacturing industry is high speed dry

machining. It was suggested to apply dry machining and high turning speed to

simulate the machining conditions that are observed to typical manufacturing

industries. This chapter describes the steps that were taken to achieve the

objectives of this study Commercially available cutting tools that are used by

numerous manufacturing Industries were ordered from cutting tools distributors,

and the appropriate machining parameter were selected so that the machining

experiment would simulate the conditions in the manufacturing industry.

3.1 MACHINE SELECTION:

Machine : MAS CENTER LATHE

Make : ACE Designers (Bangalore)

Work piece

Materials : OHNS AISI 01

Composition : (C=0.90%, Cr=.50%, Mn=1.00%,

W=0.5%, Hardness=45 HRC

Size : 120mm length and 30mm diameter.

Cutting tool

Cutting insert: Carbide, CNMG 120408 (P-30 ISO specification)

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INSERTVIEW

Fig.1. PVD miracle coating

Tool holder: PSBNR 2525M12(ISO specification),

Working tool geometry: -6,-6, 6, 6, 15, 75

Cutting Condition :

Cutting Speed : 1000rpm, 600 rpm

Feed : 0.31 mm/rev, 0.17 mm/rev

Depth of Cut : 0.5mm, 1.0mm

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3.2. EXPERIMENTAL CONDITION

Ex. No CUTTING SPEED (rpm) FEED(mm/rev) DEPTH OF CUT (mm)

EX 1 1000 0.34 1

EX 2 1000 0.34 0.5

EX 3 1000 0.17 1

EX 4 1000 0.17 0.5

EX 5 600 0.34 1

EX 6 600 0.34 0.5

EX 7 600 0.17 1

EX 8 600 0.17 0.5

Table .1

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3.3. ONLINE MONITORING INSTRUMENTS

3.3.1 ACCELEROMETER:

Type : SENDIG L-15 Accelerometer

An accelerometer is a liner seismic transducer which produces an

electric charge proportional to the applied acceleration. A simple model of an

accelerometer is shown in fig 2. a mass is supported on a piece of piezoelectric

ceramic crystal which is fastened to the frame of the transducer body.

Piezoelectric materials have the property that if they are compressed or shared,

they produce an electric potential between their extremities.

Fig.2. Accelerometer Setup

Specifications:

Sensor: Charge-output Accelerometer

Output: 0-5Vdc or 4-20mAdc, True RMS, Equivalent Peak, Equivalent Peak-

Peak,

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Overall value output Displacement, Velocity, Acceleration

Waveform Output: +5Vac, Displacement, Velocity, Acceleration all are

voltage can be observed by using oscillograph or spectrum

analyzer.

Alarm output : TTL signal, 1 level adjustable

Electrical power isolation to reduce ground disturbance

This electric potential is proportional to the amount of compression or

shear. As the frame experience an upward acceleration it also experiences a

displacement. Because the mass is attached to the frame through the spring-like

piezoelectric element, the resulting displacement it experiences is of different

phase and amplitude than the displacement of the frame. This relative

displacement between the frame and mass causes the piezoelectric crystal to be

compressed, giving off a voltage proportional to the acceleration of the frame

3.3.2. Vibration Collector

A simple model of an vibration data collector is shown in fig 3. Vibration

data collector, It can be used in field vibration measurement, fault analysis,machinery condition monitoring as well as the storage of the characteristic values

and waveforms of acceleration

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Fig.3. Vibration Collector

The velocity, displacement and high-frequency acceleration envelope. Its

measurement data can be sent to a computer for archiving of equipment

maintenance information database and signal analysis and fault analysis.

3.3.3. MCME 2.0H SOFTWARE

Sendig-900 is aseries of instrument that used for condition monitoring and

faults diagnosis of machinery.

This program provides a variety of tools and technologies to make your

manipulation of Sendig-900 even easier and more efficient. It constructs a

database system to store and manage the vibration information that collected

from spots, which solved successfully the matter of memory lack. Powerful

graphics display and data processing function can show the vibration waveforms

and spectrum that stored in the files. Through calling the fault diagnosis expert

system, it can instruct the causes of faults and means of maintenance

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3.3.5.ONLINE EXPERIMENTAL SETUP:

The Experimental setup consists of an accelerometer and vibration data

collector. the details of cutting tests are given in the table 1. In the first

experimental group 8 experiments were carried out using 2 and for each shim.

Fig. 5. Experimental setup

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Two different cutting conditions were selected. Each work piece is 120mm

length and 30mm diameter. A commercial piezoelectric sensor of Beijing

SENDIG Technology Co was mounted on the top of the tool holder using a

magnet ring fixture. The sensor was placed as close as possible to the cutting

insert to minimize signal loss and achieve a good signal-to-noise ratio.

Fig.6. Online Experimental setup

Data base were created to collect signal up to 500Hz frequency spanusing MCMe2.0 software package of SENDIG and the data base were

transferred to vibration data collector before machining. The signals were

collected by vibration data collector 911 through the piezoelectric sensor during

the cutting test. After machining the collected vibration data and signals were

uploaded to software package MCMe2.0H.

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CHAPTER 4

RESULTS AND DISCUSSION

4.1. Experimental Analysis:

After the machining RMS value was measured using probability density

curve and average roughness value was measured using SJ400 surface

roughness tester .The average roughness value Ra is the most commenly used

parameter in surface finish measurement .

EXPERIMENT 1

AMPLITUDE SPECTRUM CURVE

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Graph. 1

PROBABILITY DENSITY CURVE

Graph. 1

Table. 2

19

RegionNatural frequency Ra

(m)RMS

Peak(amplitude) Frequency(Hz)

1

2

3

0.78

0.05

0.10

2.5

450

925

1.96 0.71

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From the graph 1 and table 2, it is observed that the third natural

frequency is greater than second natural frequency. At this time, the peak value

increases from second to third region. So chatter will occur.

EXPERIMENT 2


Graph. 2

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Graph. 2

21


(m)RMS


1

2

3

0.51

0.08

0.07

5.0

495

1000

1.12 0.66

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Table. 3

From the graph 2 and table 3 value it is observed the second natural

frequency is less than third natural frequency. At this time, the second peak value

increases to the peak value decreases. So the curve diminishes, and chatter will

not occur.

EXPERIMENT 3


Graph . 3


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Graph. 3

Table .4

From the graph 3 and table 4 value, it is observed the second natural

frequency is less than third natural frequency. At this time, the second peak

23


(m)RMS


1

2

3

0.61

0.12

below 0.5

7.5

475

900

1.01 0.66

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value increases to the peak value decreases. So the curve diminishes, and

chatter will not occur

EXPERIMENT 4


Graph .

4


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Graph . 4

Table. 5

25


(m)RMS


1

23

0.51

0.040.06

7.5

435842.5

1.4 0.38

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EXPERIMENT 5


Graph. 5

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Graph .5

Table .6

27

Region Natural frequency Ra(m)

RMSPeak(amplitude) Frequency(Hz)

1

2

3

0.77

0.06

0.08

5.0

445.0

887.0

1.31 0.59

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EXPERIMENT 6


Graph. 6

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Graph. 6

29

RegionNatural frequency Ra(m

)RMS


1

2

3

0.42

0.16

0.07

2.5

370.0

725

0.89 0.57

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Table. 7




not occur.

EXPERIMENT 7


Graph. 7


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Table .8




not occur

EXPERIMENT 8


31

Region Natural frequency Ra

(m)

RMS


1

2

3

0.28

0.15

0.07

7.5

460

477.5

0.9 0.40

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Graph. 8


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Graph .8

Table. 9



33


(m)RMS


1

2

3

1.0

0.06

0.05

5.0

730

807.5

0.90 0.69

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not occur.

4.2. COMPARISON OF OFFLINE AND ONLINE SYSTEM

SURFACE ROUGHNESS VALUE AND RMS VALUE

Ex. NoCUTTING

SPEED(rpm)FEED(mm/rev)

DEPTH OF

CUT (mm)Ra (m) RMS

EX1 1000 0.34 1 1.96 0.71

EX2 1000 0.34 0.5 1.12 0.66

EX3 1000 0.17 1 1.01 0.66

EX4 1000 0.17 0.5 1.4 0.38

EX5 600 0.34 1.41 1.31 0.59

EX6 600 0.34 0.5 0.57 0.89

EX7 600 0.17 1 0.9 0.40

EX8 600 0.17 0.5 0.903 0.69

Table.10

From the table 10 when the cutting speed and depth of cut increase

corresponding to the roughness value and RMS value increases. So chatter will

occur.

When the cutting speed and depth of cut decrease corresponding to

the roughness value and RMS value decrease. So chatter will occurs.

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4.3.CONCLUSION CHART

E.NO

Natural

frequencyFrequency(HZ

)RMS Ra (m) Remarks

EX1

1 0.78

2 0.05

3 0.10

2.5

450

925

0.71 1.96 Chatter

EX2

1 0.51

2 0.08

3 0.07

5.0

495

1000

0.66 1.12 No Chatter

EX3

1 0.61

2 0.12

3 900

7.5

4.75

below 0.5


EX4

1 0.51

2 0.04

3 0.06

7.5

435

842.5

0.38 1.4 Chatter

EX5

1 0.77

2 0.06

3 0.08

5.0

445.0

887.0

0.59 1.31 Chatter

EX6

1 0.42

2 0.16

3 0.07

2.5

370.0

725


EX7

1 0.28

2 0.15

3 0.07

7.5

460

477.5

0.40 0.9 No Chatter

EX81 1.02 0.06

3 0.05

5.0730

807.5


Table.11

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CHAPTER 5

CONCLUSION

The following observation is made by introducing signal analysis method for

online monitoring of the chatter and surface roughness. The dynamic

characteristics for hard turning of OHNS01 material with various cutting speed

are investigating by using vibration data collector and surface roughness tester

1. The third natural frequency is greater than second natural frequency. At

this time, the peak value increases from second to third region. So chatter

will occur.

2. The second natural frequency is less than third natural frequency. At this

time, the second peak value increases to the peak value decreases. So

the curve diminishes, and chatter will not occur.

3. When the cutting speed and depth of cut increase corresponding to the

roughness value and RMS value increases. So chatter will occur.

4. When the cutting speed and depth of cut decreases corresponding to the

roughness value and RMS value decreases. So chatter will occurs.

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