Tool health monitoring
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16-01-2011, 06:51 PM



ABSTRACT

The concept of Computer Integrated Manufacturing (CIM) and Flexible Manufacturing System (FMS) has created a whole new area of what is called ‘Tool Management System’ (TMS). For efficient operation of TMS, a real-time monitoring of tool condition is desirable. Tool health monitoring is critical in today’s automated production and is likely to become crucial as we progress towards the unmanned factory of the future. This paper describes the development of a microcomputer-based Acoustic Emission (AE) system for monitoring progressive wear of a cutting tool. Acoustic Emission Technique (AET) with potential for many important applications has already become an important Non Destructive Testing (NDT) technique. This paper also describes the state of art of acoustic emission technique and its comparison with other techniques for tool condition monitoring.


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1. INTRODUCTION
In the rapidly changing competitive market of today, productivity and quality are matters of major concern. New technologies based largely around computers are being developed to meet this challenge. Flexible machining, flexible assembly, computer-aided inspection and associated manufacturing systems are proving to be superior to conventional production systems. Most companies are adopting these new technologies to remain competitive.

It is the concept of CIM that will lead us to the unmanned factory of the future. Within the CIM philosophy, the entire operation, from design through production to marketing and service, will be integrated together as a global system. Its main features of quick market response, increased machine utilization, improved product quality and reduced in- process inventory are amongst the various tangible and intangible benefits. The objective of this paper is to (a) highlight the importance of tool health monitoring in an automated manufacturing system, (b) summarize, and critically examine, the state-of-the-art in this area, and © discuss the micro computer-based tool wear monitoring system that has been developed at the University of Windsor, Canada.


2. ROLE OF TOOL MANAGEMENT IN FMS

As a subsystem of CIM, FMS integrated machine tools and automated storage and retrieval system (AS/RS) to provide flexibility for meeting varied demands. Each of the machine centres within a machining cell is normally equipped with a tool magazine consisting of a large number of different tools for a variety of operations. Thus, an FMS which may contain several of such machining cells deals with hundreds, sometimes thousands, of tools. This has created a whole new area of what is called Tool Management System (TMS). The principal function of TMS is to ensure the availability of the right tool at the right time and at the right station for carrying out the required machining operation. The TMS, as represented in Figure1 , is a major activity within the FMS domain of the CIM environment. The TMS itself includes tool health monitoring (THM) of which acoustic emission (AE), or any such method, is one of the elements.

However flexible and intelligent the FMS may be, its overall productivity is controlled largely by the throughout the manufacturing processes. Most subsystems within FMS including tool management are centered around manufacturing process. Non-availability of a tool or its improper replacement within the subsystem will halt machining operations and other dependent process, there by hindering the smooth flow of work-in- process. All this will eventually increase the unit cost.

2.1. Tool health monitoring

An interruption of TMS due to excessive tool wear/fracture could be detrimental to the entire operation. Not only does it halt production, it also affects the quality of the machined surface. Thus the cutting tool could very well become the weakest link in the long and complicated chain of FMS. Therefore, on-line monitoring of the health of tool and its timely replacement are important functions of tool management system.

Tool monitoring is concerned with assessing the condition of the tool as machining progresses. It involves measuring direct or indirect parameter(s) that affect tool condition (wear and fracture) and comparing with pre-set levels to initial changes in the system. This information could also be used for developing suitable adaptive control systems for optimizing the cutting process. Benefits of tool health monitoring include effect tool replacement policies, improved product quality and lower tool costs.




FIGURE. 2. Tool health monitoring as an element of CIM







3. TEHNIQUES FOR TOOL HEALTH MONITORING

The sharpness of a cutting tool is one of the important parameters affecting the accuracy of the machined surface. The earliest research on tool life was the pioneering work of Taylor in 1894, when he introduced the ‘twenty-minute tool life’ concept. Significant research has, however, been carried out only during the post World War ll period. Much of this work had been directed towards understanding the mechanism of tool wear and its relationship with cutting variable. Several mathematical and stochastic models have been developed- Abou-zeid and Oweis (1981) summarizes some of the important contributions in this area. However, the advances in manufacturing technology of the last 10 years, have created a need for on-line prediction of the tool-condition to help realize the factory of the future. It requires the development of highly reliable tool wear sensing technique for monitoring progressive tool wear as well as sudden breakage. The method should also be capable of responding quickly to prevent any damage. Thus, the reliability and speed of response are the critical parameters of the tool monitoring system.

3.1. Tool wear condition measurement

Several sensing methods have been developed for tool wear measurement. Depending on the sensors used, the methods could broadly be classified into two: direct and indirect, as shown in Fig. 3. The various methods under these groupings, some of which are already in use at the shop floor are discussed in this section.

Direct methods: Some of the direct sensing techniques are as below.

(a) Electrical resistance method: This method measures the flank wear by sensing the electric resistance of a thin film coated on the tool flank face.
(b) Optical method: In this methods the flank wear is measured directly using an ITV camera.
© Radioactive sensing method: In this method an exceedingly small amount of radioactive material is implanted on the tool flank at a known distance from the cutting edge. As the flank wear progresses beyond this point the radioactive material is

removed. At the end of each cycle the amount of radioactivity from the tool is measured to determine whether the limiting flank wear had been reached.
(d) Contact sensing method: Measurement of the tool edge position is done using touch probes. The stylus of the probe is brought in contact with the tool surface; the change in the co-ordinates measured determines the amount of tool wear (Tiusty and Andrews 1983).

Indirect methods: Some of the techniques sense those parameters which are indirectly related to the tool wear. Five of the major indirect methods are discussed below.

(a) Cutting force methods: In this methods, the cutting force components and the ‘flank wear are measured and the two are plotted for any correlation. Micheletti et. al. (1976) reported that the flank wear is linearly related to the cutting forces with a high degree of correlation. Uehara et.al.(1979) have suggested a new concept based on feed force osillogram. Once a complete correlation has been established, the magnitude of the cutting force, measured while cutting, is used to predict the tool wear without interrupting machining.
(b) Cutting temperature method. The temperature at the tool-work interface is sensed directly by infrared radiation or, indirectly, by thermocouples. It was found a correlation between tool wear and the variation of temperature field. Theoretical models have also been developed which predict an increase in temperature with that in wear. Coewell (1975) has also reported significant correlation between tool wear and cutting temperature. Here again, after the establishment of a correlation, the temperature being measured is used for on-line prediction of the amount of tool wear.
© Torque and power method. Torque and power control monitors are also used to measure the tool wear. The current, voltage and the rotational speed of the spindle drive motor are sensed to determine drive power and torque. The variation in the power consumption, or the torque generated, is related to the growth of tool wear. Control limits are set for allowable power or torque based on the maximum tool wear acceptable. The values, measured on-line, are compared with these limits and necessary action initiated to stop the spindle rotation.
(d) Vibration method. As a tool wears, its vibration characteristics change. It is this change that is monitored in the vibration method for the measurement of tool wear. In a

recent work, the vertical vibration of the tool holder in the frequency based of 4-5 kHz, 8-10kHz and 14-16kHz has been analysed for developing a data dependent systems strategy. The vibration and the cutting forces were measured for approximately 30 seconds in each cut and the ensuing power spectrum plotted. It has been found that the vibration spectral density initially decreases with increase of wear, reaches minimum corresponding to a critical tool wear, and then continues to increase.

3.2. Relative assessment of existing techniques

In the early research on tool wear, ordinary microscopes were used for measuring the magnitude of wear. Later on, for detailed quick measurement, special microscopes- like the tool-maker’s microscope-were found more suitable. Measuring the tool wear this way required frequent interruption of machining which in many cases was unacceptable. In order to overcome this difficulty and also to provide for on-line monitoring, other direct methods, such as the electrical resistance and radioactive sensing methods where proposed. These direct methods suffer from their inability to access the worn surface properly and could not be used on the shop floor for on-line measurement of tool wear. That is why indirect methods have been, and are being, developed/perfected. The first three of the indirect methods -namely, force, temperature and power-torque method-are the earliest ones developed. These suffer from two limitations, the questionable correction between tool wear with the parameter measured, and the likely effect on the parameter of sources other than tool wear.

In the cutting force method the correlation between the cutting forces and the tool wear is questionable because the former is affected not only by the later but also by tool geometry, cutting conditions and the work material. Moreover, the flank wear increases the feed force while the crater wear reduces it. The distinction between flank wear and the crater wear is important since whereas the breakage is influenced by both, the dimensional accuracy is largely dependent on the former only. Micheletti et. Al.(1968) have concluded that it is impossible to provide accurate information about wear solely on the basis of measured forces. Drozda and wiek (1983) state that experiments using thermocouples for measuring cutting temperature cause problems of noisy signals, complicated set ups and stringent calibration requirements. They also

point out that, according to a literature survey by the University of Michigan. U.S.A.. the temperature measurement alone would not be adequate for many application of adaptive control.

The vibration; method suffers form its vulnerability to sources other than those due to wear because tool vibrations are of low frequencies at which contamination of the signal by external noise is likely. Though the torque-power technique is suitable for on-line measurement of tool wear, the control limits do not account for the variation in cutting process from none set-up to another. Also torque and power could be influenced by any malfunction of the machine or its elements.

It is clear from the above discussion that none of the existing methods is likely to be effective in the factory of the future. A better technique needs to be developed. One such new technique attempts the direct measurement of tool wear using an ITV camera (Iwata and Moriwaki 1977). Another development is the AE method which holds promise of being suitable in a CIM environment- its first implementation on shop-floor has already been made by Osaka Kiko Company of Japan (Tlusty and Andrews 1983). This technique and its advantages over other are discussed in the following sections.

Fig. 2. VARIOUS METHODS OF TOOL WEAR MONITORING


4. ACOUSTIC EMISSION TECHNIQUE

Acoustic Emission Technique (AET) with potential for many important applications has already become an important non-destructive resting technique. Its origin lies in the phenomenon of rapid release of energy within a material in the form of a transient elastic wave resulting from dynamic changes like deformation, crack initiation and propagation, leakage etc. It is real time technique which can detect initiation and growth of cracks. Plastic deformation, fatigue failure, leaks etc, which are not amenable for detection by ultrasonics and other NDT methods, due to access considerations and very small sizes of the early stage cracks.

Acoustic emissions are sound or ultrasound pulses generated by events, which are detected by transducers on the surface of the specimen, which in turn generate electrical signals. The emission is thought to originate form grain boundaries sliding over one another during stressing, from plastic deformation, from inclusion cracking, from crack growth: basically, a burst of elastic energy is emitted. External factors such as mechanical impacts, friction, machinery vibration, and welding operations can also produce acoustic emission.

There are three basic behind using acoustic emission as a non destructive testing method:

(1) To use several detectors and timing circuits, together with three dimensional geometry, to locate the source of the AE, to locate where stress are causing something to happen, such as a crack propagating

(2) To monitor the rate of emission during stressing, to discover any sudden changes in rate which might be indicative of the formation of new defects, such as cracks.

(3) To monitor the rate of emission and attempt to relate this to the size, of a defect, such as a propagating crack, to determine the remaining sage life of a structure.



4.1 Principle of acousitc emission testing

Acoustic emission inspection detects and analyses minute AE signals generated by growing discontinuities in material under a stimulus such as stress, temperature etc. Proper analysis of these signals can provide information concerning the detection and location of discontinuities and the structural integrity. Depending on the nature of energy release, two types of AE are observed. These are: (1) Continuous and (2) Burst. Continuous emission is characterized by low amplitude emissions. The amplitude varies with AE activity. In metal and alloys, this type of emission occurs during plastic deformation by dislocation movement, diffusion controlled phase transformations and fluid leakage. Burst emission are characterized by short duration (10 microseconds to a few milliseconds) and high amplitude pulses due to discrete release of strain energy. This type of emission occurs during diffusion less phase transformations, crack initiation and propagation, stress corrosion cracking etc.

4.2 Technique

It is difficult to use a single all-encompassing parameter to describe an experimental result uniquely. Hence a number of AE parameters are used for interpreting the experimental results. Some of the parameters are used to identify the change in source of AE during the progress of a test, while others are used to eliminate background noise.

Figure 3 shows a typical AE signal and the various parameters used for interpretation. ‘Ringdown counts’ is the number of times the signal crosses a threshold level set for eliminating background noise. This could be used independently or as the cumulative counts with respect to time, load or any other parameter. Count rate is another parameter commonly used.
The most common ways in which AE signals can be processed are:
1. Counting: Ringdown counts, Ringdown rates, Events
2. Energy analysis: Used for both continuous and burst type emissions.
3. Amplitude analysis: Used to characterize emission from different processes
4. Frequency analysis: Used to identify different types of failures.


Fig. 3. AE SIGNAL PARAMETER

4.3 Equipment

The basic equipment is shown in Fig 4, and a typical signal in fig 5. The transducer must have very high sensitivity and usually consists of a PZT piezoelectric disc. There has been much unresolved argument as to whether it is better to use a transducer with a limited frequency range, so as to minimize background noise problems, or one with a flat bandwidth, so as to obtain data on the shape of the pulses. The former type can operate at resonance, usually between 150 and 250 kHz, and can maximize the signal-to-noise ratio.

The transducer is connected to the counting and display circuitry by special low-interference cable with multiple-layer shielding to produce immunity from electromagnetic interference. This allows long cable lengths, up to 100 m, between the transducer and preamplifier. The signals, but can also be displayed on a CRT. Since the range of amplitudes is very large, amplifiers with extremely low inherent noise levels are necessary. High-pass filters are widely used with a cut off frequency around 30 kHz.

If the signals are studied in terms of energy-which is proportional to (amplitude)- a dynamic range of more than 109 is possible. The emission, as received at the transducer, can be:

1. Counted in relation to time: a typical method is to count the number of pulses with an amplitude above a preset value, V1 say (figure 5) this is called ‘ring-down’counting, and is not a true count of the number or pulses may be counted several times, depending on the value of V1 thus a total count with time and a count-rate are obtained.

2. Each counted once, ie. discrete counting

3. Assessed for energy content by taking the square of the amplitude for each pulse, or measuring the area under the envelop of the amplitude-time curve.

4. Analyzed for amplitude distribution of the peak value of each emission

5. Analyzed for frequency content (Fourier analysis of spectrum analysis).













FIGURE. 4.3(a). BLOCK DIAGRAM OF A E EQUIPMENT




FIGURE. 4.3(b). AE PULSES RING DOWN COUNTING

4.3.1 Micro Computer Based Acoustic Emission System

Acoustic emission referes to the propagation of stress waves generated within the material when it is deformed. Application of AET in tool health Moldering was proposed in 1972 by Jwata ad Moriwaki, when they reported a close correlation between tod wear and total count of acoustic emission. Later, Dornfeld (1979) deserved an analytical micro-computer to measure the number of pulses generated during a set interval of time. A basic program reads the count rate and compares the cumulative count with limiting value for the given cutting condition and gives a warning signal, if required, to the operator to stop the machining and to replace the tool.

The experimental setup of system is shown in figure. It consist of a piezoelecrtric transducer to pick up AE signal which is then amplified and filtered using a wide band conditioning amplifier and with filter circuit respectively. A 16 bit pulse counter was built in house as a part of the development. It is plagged in the personal computer. A program writer on BASIC will analyze the count rate and give necessary alarms for the operator. They doing the work of total health monitoring.

4.4 Sources of AE in metal cutting

During metal cutting, AE is generated by the deformation process in the cutting zone. High frequency AE signals are emitted during tool fracture which are sensitive to the type of fracture. Five different sources of AE have been identified in orthogonal metal cutting (Domfeld and Kannatey-Asibu 1980). As shown in Fig.6.these are:

a) material deformation in the shear zone during chip formation;
b) chip motion, sliding and sticking along the tool rake face;
c) chip breaking;
d) impact of broken chips on tool/workpiece, or entanglement of continuous chips with toollworkpiece; and
e) tool-work rubbing ,i.e. friction on the flank face.



Fig. 5. BLOCK DIAGRAM OF THE MICROCOMPUTER-BASED AE SYSTEM


Fig. 6. THE FIVE SOURCES OF AE IN METAL CUTTING


4.5 Characteristics of AE signature

The AE signals emitting during metal cutting are of two types: burst and continuous (Iwata and Moriwaki 1977). The bust type signals are generated during discontinuous or segmented chip formation and are characterized by rapid rise time and exponential decay. Such emissions are associated with crack and fracture. The continuous -type signals are generated when continuous chips are formed. These generally represent low amplitude events and are due to visco-elastic and plastic yielding. A typical AE signal is shown in Fig.7 where burst emission are denoted by (b) and continuous ones by ©. The transients/bursts occur at frequent intervals and are superimposed on the continuous-type signals.

The severity of AE depends on strain, strain rate, and volume of deformed material which, in turn, are dependent on basic cutting parameters, like rake angle, clearance angle, feed and cutting speed. The magnitude of AE signals in the beginning of machining is low which increases gradually until failures are encountered. When a tool breaks, defmite peaks in AE have been noticed over 100 kHz. These peaks are detected mainly in the frequency range of 100-300 kHz, but can sometimes be as high as 400 kHz.

Fig. 7. A SAMPLE OF AE SIGNAL

4.6 Relative advantages of AE technique

Acoustic emission technique has several distinct advantages over others. The major ones are:

(a) Changes in AE signal level occur almost at the instant of tool fracture where as that in the force level occurs only after the tool has broken or chipped-off. Because of this, AE based methods can detect tool fracture quickly, thus being suitable for timely action.
(b) The frequency range of AE signals is well above that of mechanical vibrations and noises, and therefore, no chance of contamination by the latter. This is, probably the biggest attraction of AE method over others.
© Besides the tool wear, AE technique can also detect tool fracture. AE can show through its signature whether a chipping or fracture has taken place
(d) In addition to detecting the occurrence of fracture, the location of fracture can also be found out.
(e) According to Iwata and Moriwaki( 1977) AE signals for different cutting materials are basically similar inspite of the differences in their mechanical properties and cutting conditions’.
(f) The AE transducer can easily be attached to the tool shank without being an obstacle to the cutting set-up.


5. PAST WORK ON AE METHOD

Most of the work on AE in metal cutting has, so far, been of the experimental type. In the short span of less than a decade some useful results (as described below) have already been obtained. The research in this fields is becoming hectic because of the urgent need for a successful shop-floor method for on -line monitoring of tool condition within FMS. Some of the quantifiable characteristics of AE and AE and their relationships with tool wear and cutting parameters are as below.

5.1. Pulse Count

The total count of AE has been found to be good indicator of tool wear (Iwata and Moriwaki 1977). It is negligibly small in the beginning until the flank wear reaches 120-140 µm afterwards it increases linearly or quadratically depending on the threshold voltage.

5.2. AE energy

Rms-value of the AE signal is a measure of its energy content. For a given workpiece material and rake angle of the tool, the rms-value of a continuous AE signal increases almost linearly with cutting speed (Kannatey-Asibu and Domfeld 1981). It also grows with the rake angle, Chip-tool contact length and shear angle but hardly changes with the depth of cut and the feed rate (Moriwaki 1983).

As far as its variation with tool wear is concerned, it increases linearly with the growth in tool wear is concerned, it increases linearly with the growth in tool wear. Such a relationship is encouraging from the viewpoint of application potential of AE technique for on-line assessment of tool wear. However, the increase in AE energy with tool wear is direct function of the cutting speed. The magnitude increases abruptly when the flank wear is in the range of 160-180 urn, thus showing a similar characteristic as with the tool pulse count.


5.3. Tool Fracture Detection

The AE generated at the time of fracture (cracking and chipping) is of the burst type (Moriwaki 1980) and of large magnitude. According to Lakino (1982), the amplitude is approximately proportional to the second-order root of the surface area generated by the fracture. The rise time of the rms-value of AE due to fracture is generally 3-10 ms depending on the magnitude of the signal (Lan and Dornfeld 1984). Chipping of the cutting tool causes a substantial increase in the ims- level but the resulting amplitude is not of the burst- type as in fracture (it contradicts the work of Moriwaki 1980). This characteristics could be helpful in distinguishing chipping from fracture. Detection of chipping is, ho more difficult since an increase in rms value of AE can aslo take place due to other reasons such as an increase in cutting speed.


6. PRESENT WORK

In the previous section the results of other investigators on AE in metal cutting have been presented This section describes the work carried out at the University of Windsor, Canada.

6.1. Development of a microcomputer-based AE system

The objective was to develop a low-cost AE system so that it is affordable to small and medium-size manufacturers. The system is microcomputer-based and is complete on its own. Since the capabilities of a microcomputer are normally resident in the machining centres, these can easily be tapped, if required, for implementing this system at the shop floor.

The system monitors the progressive wear of a cutting tool using the count and count rate method for the analysis of AE. The general set-up of the system is shown in Fig.5. It consists of a piezo-electric transducer to pickup the AE signal which is then amplified and filtered using a wide-band conditioning amplifier. A 16-bit pulse counter was built in-house as a part of the development. It is plugged into the computer. A program written on BASIC will analyse the cant rate and give necessary alarms for the operator.



7. CONCLUSION

The present shop-floor practice of tool replacement based on fixed tool life may not be the most economic since a tool can get replaced prematurely or, in the other extreme, only after damage has been done. There is obviously a need for on-line monitoring of tool-condition. This has become more important within the context of computer-integrated manufacturing. The state-of-the-art in tool wear monitoring in general, and that of the AE technique in particular, has also been discussed.


8. REFERENCES

1. C.V.Subramanyan, “Non Destructive Testing Techniques”, Narosa Publications, New Delhi, 2000, pp. 183 – 197.
2. Dorn Feld.D.A, “Investigation of Orthogonal cutting via AE signal analysis”, Dearborn, Michigan, 1979, pp. 268 – 272
3. Drozda.T.J, “Tool manufacturing Engineers”, Dearborn Michigan,1983, pp. 05 – 69
4. R Halm Shaw, “Non Destrective Testing Techniques”, Edward Arnold Publications, UK, 1987, pp. 282 – 300.
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summer project pal
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16-01-2011, 07:04 PM

[b]TOOL HEALTH MONITORING

Presented By:
Namraz P N[/b]



.ppt   TOOL HEALTH MONITORING 1.ppt (Size: 325 KB / Downloads: 107)

INTRODUCTION
Flexible machining, flexible assembly, computer-aided inspection and associated manufacturing systems are proving to be superior to conventional production systems.

It is the concept of CIM that will lead us to the unmanned factory of the future. Within the CIM philosophy, the entire operation, from design through production to marketing and service, will be integrated together as a global system.

The objective of this paper is to (a) highlight the importance of tool health monitoring in an automated manufacturing system, (b) summarize, and critically examine, the state-of-the-art in this area, and © discuss the micro computer-based tool wear monitoring system that has been developed at the University of Windsor, Canada.
ROLE OF TOOL MANAGEMENT IN FMS
As a subsystem of CIM, FMS integrated machine tools and automated storage and retrieval system (AS/RS) to provide flexibility for meeting varied demands

Each of the machine centers within a machining cell is normally equipped with a tool magazine consisting of a large number of different tools for a variety of operations.

The principal function of TMS is to ensure the availability of the right tool at the right time and at the right station for carrying out the required machining operation.


The TMS itself includes tool health monitoring (THM) of which acoustic emission (AE), or any such method, is one of the elements.

Most subsystems within FMS including tool management are centered around manufacturing process.

Non-availability of a tool or its improper replacement within the subsystem will halt machining operations and other dependent process, there by hindering the smooth flow of work-in- process.
TOOL HEALTH MONITORING
An interruption of TMS due to excessive tool wear/fracture could be detrimental to the entire operation.

The cutting tool could very well become the weakest link in the long and complicated chain of FMS.

Tool monitoring is concerned with assessing the condition of the tool as machining progresses.

It involves measuring direct or indirect parameter(s) that affect tool condition (wear and fracture) and comparing with pre-set levels to initial changes in the system.

Benefits of tool health monitoring include effect tool replacement policies, improved product quality and lower tool costs.
Tool health monitoring as an element of CIM
TEHNIQUES FOR TOOL HEALTH MONITORING
The sharpness of a cutting tool is one of the important parameters affecting the accuracy of the machined surface.

It requires the development of highly reliable tool wear sensing technique for monitoring progressive tool wear as well as sudden breakage.

The method should also be capable of responding quickly to prevent any damage.

Thus, the reliability and speed of response are the critical parameters of the tool monitoring system.
TOOL WEAR CONDITION MEASUREMENT
Several sensing methods have been developed for tool wear measurement.

Depending on the sensors used, the methods could broadly be classified into two:
1) DIRECT
2)INDIRECT

DIRECT METHODS
(a) Electrical resistance method: This method measures the flank wear by sensing the electric resistance of a thin film coated on the tool flank face.

(b) Optical method: In this methods the flank wear is measured directly using an ITV camera.

© Radioactive sensing method: In this method an exceedingly small amount of radioactive material is implanted on the tool flank at a known distance from the cutting edge. As the flank wear progresses beyond this point the radioactive material is removed. At the end of each cycle the amount of radioactivity from the tool is measured to determine whether the limiting flank wear had been reached.

(d) Contact sensing method: Measurement of the tool edge position is done using touch probes. The stylus of the probe is brought in contact with the tool surface; the change in the co-ordinates measured determines the amount of tool wear .
INDIRECT METHODS
Cutting force methods: In this methods, the cutting force components and the ‘flank wear are measured and the two are plotted for any correlation. . Once a complete correlation has been established, the magnitude of the cutting force, measured while cutting, is used to predict the tool wear without interrupting machining.

Cutting temperature method:The temperature at the tool-work interface is sensed directly by infrared radiation or, indirectly, by thermocouples. It was found a correlation between tool wear and the variation of temperature field. Theoretical models have also been developed which predict an increase in temperature with that in wear.

Torque and power method. Torque and power control monitors are also used to measure the tool wear. The current, voltage and the rotational speed of the spindle drive motor are sensed to determine drive power and torque. The variation in the power consumption, or the torque generated, is related to the growth of tool wear. Control limits are set for allowable power or torque based on the maximum tool wear acceptable. The values, measured on-line, are compared with these limits and necessary action initiated to stop the spindle rotation.

Vibration method. As a tool wears, its vibration characteristics change. It is this change that is monitored in the vibration method for the measurement of tool wear. It has been found that the vibration spectral density initially decreases with increase of wear, reaches minimum corresponding to a critical tool wear, and then continues to increase.

ACOUSTIC EMISSION TECHNIQUE
Acoustic Emission Technique (AET) with potential for many important applications has already become an important non-destructive resting technique.

Its origin lies in the phenomenon of rapid release of energy within a material in the form of a transient elastic wave resulting from dynamic changes like deformation, crack initiation and propagation, leakage etc.

It is real time technique which can detect initiation and growth of cracks.

Acoustic emissions are sound or ultrasound pulses generated by events, which are detected by transducers on the surface of the specimen, which in turn generate electrical signals.

The emission is thought to originate form grain boundaries sliding over one another during stressing, from plastic deformation, from inclusion cracking, from crack growth: basically, a burst of elastic energy is emitted.

There are three basic techniques behind using acoustic emission as a non destructive testing method:

(1) To use several detectors and timing circuits, together with three dimensional geometry, to locate the source of the AE, to locate where stress are causing something to happen, such as a crack propagating.

(2) To monitor the rate of emission during stressing, to discover any sudden changes in rate which might be indicative of the formation of new defects, such as cracks.

(3) To monitor the rate of emission and attempt to relate this to the size, of a defect, such as a propagating crack, to determine the remaining sage life of a structure.
PRINCIPLE OF ACOUSTIC EMMISSION TESTING
Acoustic emission inspection detects and analyses minute AE signals generated by growing discontinuities in material under a stimulus such as stress, temperature etc. Depending on the nature of energy release, two types of AE are observed.
1. Continuous
2. Burst


BLOCK DIAGRAM OF A E EQUIPMENT
MICRO COMPUTER BASED ACOUSTIC EMMISSION
Acoustic emission referes to the propagation of stress waves generated within the material when it is deformed.

A basic program reads the count rate and compares the cumulative count with limiting value for the given cutting condition and gives a warning signal, if required, to the operator to stop the machining and to replace the tool.

The experimental setup of system is shown in figure. It consist of a piezoelecrtric transducer to pick up AE signal which is then amplified and filtered using a wide band conditioning amplifier and with filter circuit respectively.

A 16 bit pulse counter was built in house as a part of the development.

It is plagged in the personal computer.

A program writer on BASIC will analyze the count rate and give necessary alarms for the operator.



SOURCES OF METAL CUTTING
During metal cutting, AE is generated by the deformation process in the cutting zone. High frequency AE signals are emitted during tool fracture which are sensitive to the type of fracture.

Five different sources of AE have been identified in orthogonal metal cutting :
1. material deformation in the shear zone during chip formation
2.chip motion, sliding and sticking along the tool rake face

3.chip breaking
4.impact of broken chips on tool/workpiece, or entanglement of continuous chips with toollworkpiece
5. tool-work rubbing ,i.e. friction on the flank face.
CHARECTERISTICS OF AE SIGNATURE
The AE signals emitting during metal cutting are of two types:
1. burst
2. continuous
Burst : The bust type signals are generated during discontinuous or segmented chip formation and are characterized by rapid rise time and exponential decay.

Continous : The continuous -type signals are generated when continuous chips are formed. These generally represent low amplitude events and are due to visco-elastic and plastic yielding.

The severity of AE depends on strain, strain rate, and volume of deformed material which, in turn, are dependent on basic cutting parameters, like rake angle, clearance angle, feed and cutting speed.

The magnitude of AE signals in the beginning of machining is low which increases gradually until failures are encountered.
RELATIVE ADVANTAGE OF AE
Changes in AE signal level occur almost at the instant of tool fracture where as that in the force level occurs only after the tool has broken or chipped-off. Because of this, AE based methods can detect tool fracture quickly, thus being suitable for timely action.

The frequency range of AE signals is well above that of mechanical vibrations and noises, and therefore, no chance of contamination by the latter. This is, probably the biggest attraction of AE method over others.

Besides the tool wear, AE technique can also detect tool fracture. AE can show through its signature whether a chipping or fracture has taken place.


In addition to detecting the occurrence of fracture, the location of fracture can also be found out.

(e) According to Iwata and Moriwaki( 1977) AE signals for different cutting materials are basically similar inspite of the differences in their mechanical properties and cutting conditions.

(f) The AE transducer can easily be attached to the tool shank without being an obstacle to the cutting set-up.
DEVELOPMENT OF MICROCOMPUTER BASED AE SYSTEMS
The objective was to develop a low-cost AE system so that it is affordable to small and medium-size manufacturers. The system is microcomputer-based and is complete on its own.

Since the capabilities of a microcomputer are normally resident in the machining centres, these can easily be tapped, if required, for implementing this system at the shop floor.

The system monitors the progressive wear of a cutting tool using the count and count rate method for the analysis of AE.

It consists of a piezo-electric transducer to pickup the AE signal which is then amplified and filtered using a wide-band conditioning amplifier.

A 16-bit pulse counter was built in-house as a part of the development.

It is plugged into the computer. A program written on BASIC will analyse the cant rate and give necessary alarms for the operator.
CONCLUSION
The present shop-floor practice of tool replacement based on fixed tool life may not be the most economic since a tool can get replaced prematurely or, in the other extreme, only after damage has been done. There is obviously a need for on-line monitoring of tool-condition. This has become more important within the context of computer-integrated manufacturing. The state-of-the-art in tool wear monitoring in general, and that of the AE technique in particular, has also been discussed.

REFERENCES
Non Destructive Testing Techniques by C.V Subramanyan
Investigation of Orthogonal cutting via AE signal analysis by Dorn Feld.D.A
Tool manufacturing Engineers by Drozda.T.J
howstuffworks.com

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