Development of in-process Tool Wear Monitoring System for CNC Turning

Transcription

1 933 Development of in-process Tool Wear Monitoring System for CNC Turning Toshimichi MORIWAKI, Toshiroh SHIBASAKA and Somkiat TANGJITSITCHAROEN The aim of this research is to develop an in-process tool wear monitoring system for CNC turning machine. The exponential decay function is employed to represent the relation between the nominal specific cutting resistance and feed rate. An index value a in the exponential decay function is defined to estimate the flank wear, which is equivalent to the rate of increase in the nominal specific cutting resistance at zero feed rate as compared to that at infinite feed rate. In order to obtain the characteristic value a, the additional cutting cycles is proposed here to alter the feed rate deliberately during the normal cutting cycle to measure the cutting forces and identify the rate of increase in the nominal specific cutting resistance at smaller feed rates. Series of cutting tests were carried out to estimate the flank wear, and it is proved that the index mentioned above can be a good measure of tool wear, even though the depths of cut, the cutting speeds and the cutting tools, as well as the work materials are different. Key Words: Tool Wear, Cutting Force, Turning, CNC Turning Machine, Nominal Specific Cutting Resistance 1. Introduction Automated machining operation has been progressed intensively in the last few decades, and unattended operation of machine tools is widely introduced in many machine shops. However, the flank wear is still one of the main nuisances in manufacturing automation because it deteriorates not only the machined surfaces quality but also geometrical accuracy and causes the interruptions of machining operation. Therefore, the need for in-process tool monitoring system is much increased in order to guarantee high reliability of the systems. It is well known that the cutting force is affected by the amount of flank wear (1), and extensive efforts have been devoted to develop methodologies for tool monitoring systems based on cutting force signals (2) (6). Moriwaki and Shamoto (7) developed a milling condition Received 5th December, 2003 (No ) Faculty of Mechanical Engineering, Kobe University, 1 1 Rokkodaicho, Nada, Kobe, Hyogo , Japan. moriwaki@kobe-u.ac.jp Graduate School of Science and Technology, Kobe University, 1 1 Rokkodaicho, Nada, Kobe, Hyogo , Japan. shiba@mech.kobe-u.ac.jp, smart tee@hotmail.com monitoring system based on cutting force model. The width of flank wear land could be predicted from the measured maximum force. The maximum resultant cutting force corresponding to each flank wear was calculated by utilizing specific cutting resistance. The optimization method was used to determine the optimum specific cutting resistance for the states of tool wear. The parameters in the specific cutting resistance formula were defined in two parts. The first part was assumed to be constant regardless of the tool wear and the second one was the functions of tool wear. Since the tool wear does not affect the specific cutting resistance when the uncut chip thickness is large enough. Therefore, the parameters in the first part, which were constant, and the parameters in the second one, which were functions of tool wear, were obtained at the same time by the optimization, but the influences of workpiece material, cutting speeds, feed rate and depth of cut, which affect the specific cutting resistance, were not taken into consideration. Choudhury and Kishore (8) have developed a reliable model to predict the flank wear during the turning process. The relationship between the flank wear and the ratio of force components has been established on the basis of cutting data obtained from series of experiments as a function of force ratio, cutting speed, feed rate, depth of cut and diameter of workpiece JSME International Journal Series C, Vol. 47, No. 3, 2004

2 934 but the influence of the workpiece material was not considered. Cuppini and Errico (9) focused on the methods and devices of in-process tool wear monitoring in turning operations. The implementation of a continuous monitoring method based on the experimental relationships between the wear and the cutting powers has been described but such important parameters as workpiece properties, cutting speeds, feed and depth of cut, which influence tool wear largely, were not taken into account. Oraby and Hayhurst (10) have developed mathematical models to describe the wear versus the time and the wear versus the force relationships. Cutting forces have been found to correlate well with the progress of the tool wear and with the tool failure. Yellowley and Lai (11) suggested an approach that utilized force ratios for monitoring tool wear but a direct relationship between the tool wear and the force ratios was not produced. Elbestawi (12) presented an approach for on-line monitoring of the flank wear in milling. This approach was based on the variations of magnitude of cutting force harmonics with the flank wear. Moriwaki and Mori (13) presented an approach for in-process identification of the state of cutting process in turning operation via sensor fusion based on the neural network approach. The state of cutting tool wear, the onset of chatter vibration, and the tangling of chips are identified by sensing the cutting force components and the acoustic emission signal. However, in order to identify the state of cutting, which depends on the cutting conditions, preliminary experiments are required for the learning of the neural network. Choudhury, Kumar, Ghosh (14) developed a model to evaluate the exponent and the constant of Taylor s tool life equation using the minimum number of experiments. The model has been used for developing an adaptive control system for on-line monitoring of tool wear. The tool life was determined by correlating the increase in the cutting force and the tool wear, but the effect of other factors, such as the combinations of the work materials and the cutting conditions, were not taken into consideration. Lister and Barrow (15) showed that the main cutting force gives the best indication of tool wear at any given time, and that the feed and the radial forces are not suitable for in-process monitoring of tool wear. However there are not many systems being used in practice at present mainly due to lack of general applicability. The aim of this research is to develop an in-process tool condition monitoring system for CNC turning machine, which can be used in practice. The most specific feature of the methodology developed here is that the system changes the feed rate automatically during cutting and measures the cutting forces to actively sense the amount of the flank wear of the cutting tool. It is experimentally shown here that the nominal specific cutting resistance is increased with a decrease in the feed rate, and approaches to a certain value. The rate of Series C, Vol. 47, No. 3, 2004 increase in the nominal specific cutting resistance at zero feed rate is larger when the amount of flank wear is larger. A new index, or the ratio of nominal specific cutting resistance at zero feed rate to that at theoretical infinite feed rate, is introduced here to estimate the amount of flank wear. 2. In-Process Tool Monitoring System Proposed 2. 1 Relation between cutting force and feed rate The cutting force F is affected by the work material as well as the cutting conditions, such as the depth of cut d and the feed rate f. It is therefore necessary to distinguish the cutting force change due to the tool wear from those attributable to other effects for any combinations of the work materials and the cutting conditions. The relation between the feed rate and the cutting force is generally described as shown in Fig. 1 (a). The cutting force increases almost proportionally to the feed rate where the feed rate is relatively large. The rate of increase in the force generally becomes larger as the feed rate is decreased due to the wear at the tool flank. As the tool wear progresses, the cutting force is increased as shown in the figure mainly due to the increase in the force at the tool flank Nominal specific cutting resistance model The nominal specific cutting resistance k s = F/ fd depends on the workpiece material, the cutting speed v, the feed rate, the depth of cut, the tool wear, the tool geometry and so on. However, the nominal specific cutting resistance is considered to converge to a certain value when the feed rate is infinite and the tool wear does not affect Fig. 1 (a) Cutting force versus feed rate (b) k s /k versus feed rate Models of cutting force and k s versus feed rate JSME International Journal

3 935 the nominal specific cutting resistance when the feed rate is large enough (7). Hence, the ratio of nominal specific cutting resistances at zero feed rate and at theoretically infinite feed rate is defined here to give a measure of tool wear, which distinguish the effect of tool wear from any combinations of the work materials and the cutting conditions. The nominal specific cutting resistance becomes larger as the feed rate is decreased. The nominal specific cutting resistance k s at smaller feed rates is expected to be increased as the tool wear progresses as shown in Fig. 1 (b). The relation between k s /k and feed rate f is represented here by the exponential decay function for the sake of simplicity, or k s = k(1+ae bf ) (1) where k is the nominal specific cutting resistance in the steady state when the feed rate is large enough, a is the rate of increase of k s at zero feed rate as compared to k at the infinite feed rate, and b is the rate constant. The parameter values k, a, andb in Eq. (1) are obtained by utilizing the steepest descent method (7), (16) (18) based on the cutting force data measured. Therefore, it is expected that the index value a becomes larger as the tool wear progresses. Since the index value a does not represent the absolute value of the nominal specific cutting resistance but its ratio, it is expected to be independent of the material hardness and the cutting conditions other than the feed rate Additional cutting cycle In order to obtain the index value a, a method is proposed here to introduce additional cutting cycles to alter the feed rate deliberately during the normal cutting cycle to measure the cutting forces and identify the rate of increase in the nominal specific cutting resistance at smaller feed rates. The additional cutting cycles to change the feed rate are inserted to the NC program intermittently when the tool condition monitoring is required. It means that the normal feed rate is altered suddenly during the cutting cycle. A typical change in the feed rate is from 0.25 to 0.05 mm/rev or from 0.05 to 0.25 mm/rev in one pass of cut by stepping down or up at an interval of 0.05 mm/rev within 1.5 seconds approximately per step, and then the feed rate goes back to the normal feed rate again as shown in Fig. 2. The cutting time for the additional short cycles to alter the feed rate in one pass of cut is less than 20 seconds. Hence, the amount of flank wear is assumed not to change within this period. 3. Experimental Equipment and Procedure A commercially available small CNC turning machine is employed for the cutting experiments. Figure 3 shows photographs of the CNC turning machine and the close-up of the dynamometer attached to the tool turret. (b) (a) Fig. 2 The additional cutting cycle Open architecture CNC turning machine New tool dynamometer installed onto tool turret of CNC turning machine Fig. 3 Illustration of experimental setup The longitudinal turning of plain carbon steel (JIS S45C) and alloy steel (JIS SNCM 420) was adopted in the cutting experiments. The major cutting conditions are summarized in Table 1. The cutting forces are monitored by the tool dynamometer developed. The structure of tool dynamometer developed to measure the three cutting force components is shown in Fig. 4. The cutting tool shank is fixed on the jig. Four ring type of 3-force component quartz force sensors are inserted between the jigs installed onto the tool turret of CNC turning machine. The dynamometer is calibrated in advance (19) (21) and the cross interference after JSME International Journal Series C, Vol. 47, No. 3, 2004

4 936 Table 1 Major cutting conditions Fig. 5 Examples of experimentally obtained cutting forces measured at feed rates altered from 0.05 to 0.25 mm/rev at cutting speed 150 m/min, depth of cut 1 mm, and tool nose radius 0.8 mm for different stages of the flank wear V b ( 7 ) Calculate the nominal specific resistances and calculate the index value a. ( 8 ) Estimate the tool wear by referring to the calibrated relation between the index value a and the amount of flank wear V b, which is obtained at step (5). 4. Experimental Results and Discussions Fig. 4 Structure of tool dynamometer the static calibration is less than 5% in each axis. First, the following experimental procedures are adopted to obtain the relation between the amount of flank wear V b and the index value a; ( 1 ) Start cutting with a tool with known amount of flank wear and measure the cutting force during the period including the additional cutting cycle. ( 2 ) Calculate the nominal specific cutting resistances at varied feed rates, and fit the data to the nominal specific cutting resistance curve to obtain the index value a in Eq. (1). ( 3 ) Check the flank wear and take the average value of the flank wear before and the after the cutting as the nominal flank wear to be correlated with the index value a obtained. ( 4 ) Repeat the procedures (1) to (3) under the same cutting conditions for different flank wear. ( 5 ) Repeat the procedures (1) to (4) with another cutting tool for another cutting conditions and work materials. Second, in order to estimate the tool wear in actual cutting, the following procedures are adopted; ( 6 ) Insert the additional cutting cycle when the tool wear is to be estimated, and measured the cutting force. Series C, Vol. 47, No. 3, Experimentally obtained cutting forces and nominal specific cutting resistances Series of cutting experiments are carried out with the cutting tools having differentamounts of flank wear to obtain the relation between the cutting force and the feed rate under the major cutting conditions. Some examples of experimentally obtained three force components are shown in Fig. 5. All three components of cutting forces are measured here for different stages of the flank wear at a cutting speed of 150 m/min, a depth of cut of 1 mm, tool nose radius of 0.8 mm and feed rates altered from 0.05 to 0.25 mm/rev in one pass of cut by stepping up at an interval of 0.05 mm/rev within 1.5 seconds approximately per step. All three components of cutting forces increase with an increase in the feed rate. After the cutting tool is worn, the cutting forces increase due to the tool wear. Figure 6 shows examples of experimentally obtained nominal specific cutting resistances k s in the main force calculated, which are obtained from the cutting forces measured for different stages of the tool wear and at different levels of the depths of cut, but at cutting speed of 150 m/min, and tool nose radius of 0.8 mm. The value of k s for new tools and worn tools are different significantly. The k s becomes larger as the feed rate is decreased and also the tool wear progresses. In order to obtain the index values a, the experimentally obtained nominal specific cutting resistance curves are fitted to Eq. (1). Figure 7 shows examples of comparison between the identified k s after fitting and the measured k s in the main force obtained at cutting speed of 150 m/min JSME International Journal

5 937 Fig. 6 Examples of experimentally obtained k s in main force versus feed rate at cutting speed of 150 m/min, and tool nose radius 0.8 mm Fig. 8 Relation between index value a and flank wear Fig. 7 Comparison between fitted k s and measured k s in main force versus feed rate obtained at cutting speed 150 m/min, depth of cut 1.5 mm, and tool nose radius 0.8 mm and depth of cut of 1.5 mm. The normal lines indicate identified k s, while black circle, triangle and square marks represent the experimentally obtained k s. Each measured k s curve is obtained by one pass of cut by introducing the feed rate alteration. The results of identifications show that the identified k s well fits to the measured data Relation between flank wear and index a After fitting all of the experimentally obtained k s to Eq. (1), the value of index a is obtained for the cases tested, and summarized in Fig. 8. As it was stated before, a is defined here as the ratio of nominal specific cutting resistance at zero feed rate to that at theoretically infinite feed rate. The relation between the flank wear and the index value a is shown here. The index value a plotted against the flank wear shows the same trend, even though the depths of cut, the cutting speeds and the cutting tools, as well as the work materials are different, because the effect of tool wear is distinguished and independent from any combinations of the work materials and the cutting conditions by taking the ratio of nominal specific cutting resistances at zero feed rate and at theoretically infinite feed rate. Hence, the flank wear can be simply estimated by referring to the index value a regardless of the cutting conditions. Fig. 9 Comparison of calculated flank wear to measured flank wear versus time The relation between the flank wear and index value a is normalized and represented here by employing an exponential function for the sake of simplicity, or a = y e z V b (2) where y and z are constants. The values of parameters y and z in Eq. (2) are obtained by utilizing the least square method based on the values of index a and the amount of flank wear measured in Fig. 8. After fitting the curve, the amount of flank wear is obtained as follows; V b = lna ln1.06 (3) Validation of flank wear and index a model The validation of the flank wear and index a model was proved by series of cutting tests conducted separately with new cutting tools. Figure 9 shows two examples to compare the calculated flank wear to the measured flank wear. The white circle and triangle represent the measured flank wear, while the black circle and triangle represent the calculated flank wear based on the model represented by Eq. (3). The calculated flank wear is close to the measured one within plus and minus 10% allowance error lines, especially in the steady state of wear process until the amount of flank wear reaches to the permissible limit which is 0.3 mm. Hence, the flank wear and index a JSME International Journal Series C, Vol. 47, No. 3, 2004

6 938 model is concluded to be reliable and promising to identify the flank wear during the in-process monitoring. 5. Conclusions An index a, which is equivalent to the rate of increase of the nominal specific cutting resistance at zero feed rate as compared to that at infinite feed rate, is proposed to give a measure of tool wear. A method is also proposed to insert additional cutting cycles into the NC program to alter the feed rate to obtain the index value a based on the measured cutting forces. It is proved by series of cutting experiments that the experimentally obtained index values of a give good measures of tool wear. A fitted curve is obtained to correlate the index value a and the amount of flank wear. The largest potential advantage of the method proposed here is that the amount of flank wear can be readily estimated without carrying out experiments for specific cases, and the threshold of tool life can be obtained easily under any cutting conditions. References ( 1 ) Okushima, K. and Hitomi, K., Flank Wear Progress and Variation of Tool Forces, J. JSPE, (in Japanese), Vol.29, No.4 (1963), pp ( 2 ) Choudhury, S.K. and Ramesh, S., On Line Tool Wear Sensing and Compensation in Turning, J. Mater. Process. Tech., Vol.49, No.3-4 (1995), pp ( 3 ) Rao, S.B., Tool Wear Monitoring through Dynamics of Stable Turning, J. Eng. Ind., Vol.108 (1986), pp ( 4 ) Akgerman, N. and Frisch, J., The Use of Cutting Force Spectrum for Tool Wear Compensation during Turning, Proc. 12th Int. Mach. Tool Des. Res. Conf., UMIST, Manchester, (1971), pp ( 5 ) Danai, K. and Usloy, A.G., A Dynamic State Model for on-line Tool Wear Estimation in Turning, J. Eng. Ind., Vol.109, No.4 (1987), pp ( 6 ) Kaye, J.E., Yan, D.H., Popplewell, N. and Balakrishman, S., Predicting Tool Flank Wear Using Spindle Speed Change, Int. J. Mach. Tools & Manufacture, Vol.35, No.9 (1995), pp ( 7 ) Moriwaki, T. and Shamoto, E., Intelligent Tool Condition Monitoring for Milling, Proceeding of 29th CIRP International Seminar on Manufacturing Systems, New Manufacturing Era Adaptation to Environment, Culture, Intelligence and Complexity, (1997), pp ( 8 ) Choudhury, S.K. and Kishore, K.K., Tool Wear Measurement in Turning Using Force Ratio, Int. J. Mach. Tools & Manufacture, Vol.40 (2000), pp ( 9 ) Cuppini, D., Errico, G.D. and Rutelli, G., Tool Wear Monitoring Based on Cutting Power Measurement, Wear, Vol.139 (1990), pp (10) Oraby, S.E. and Hayhurst, D.R., Development of Models for Tool Wear Force Relationships in Metal Cutting, Int. J. Mech. Sci., Vol.33, No.2 (1991), pp (11) Yellowley, I. and Lai, C.T., The Use of Force Ratios in the Tracking of Tool Wear in Turning, J. Eng. Ind., Vol.115 (1993), pp (12) Elbestawi, M.A., Papazafiriou, T.A. and Diu, R.X., In-Process Monitoring of Tool Wear in Milling Using Force Signals, Int. J. Mach. Tools & Manufacture, Vol.31, No.1 (1991), pp (13) Moriwaki, T. and Mori, Y., Sensor Fusion for In- Process Identification of Cutting Process Based on Neural Network Approach, Proc. IMACS/SICE Int. Symp., (1992), pp (14) Choudhury, S.K., Kumar, E. and Ghosh, A., A Scheme of Adaptive Turning Operations, J. Mater. Process. Tech., Vol.87 (1999), pp (15) Lister, P.M. and Barrow, G.C., Tool Condition Monitoring System, Proc. 26th Int. J. Mach. Tool Des. Res. Conf., (1986), pp (16) Morse, P.M. and Feshbach, H., Asymptotic Series; Method of Steepest Descent, Methods of Theoretical Physics, Part I, (1953), pp , McGraw-Hill, New York. (17) Chong, E. and Zak, S.H., Steepest Descent Method, An Introduction to Optimization, (1996), pp , John Wiley & Sons, Inc., New York. (18) Shamoto, E. and Altintas, Y., Prediction of Shear Angle in Oblique Cutting with Maximum Shear Stress and Minimum Energy Principles, Journal of Manufacturing Science and Engineering, Vol.121 (1999), pp (19) Axinte, D.A., Belluco, W. and Chiffre, L.D., Evaluation of Cutting Force Uncertainty Components in Turning, Int. J. Mach. Tools & Manufacture, Vol.41 (2001), pp (20) Levi, R., Dynamometer Performance Evaluation, Annals of the CIRP, Vol.17 (1969), pp (21) Oraby, S.E. and Hayhurst, D.R., High-Capacity Compact Three-Component Cutting Force Dynamometer, Int. J. Mach. Tools & Manufacture, Vol.30, No.4 (1990), pp Series C, Vol. 47, No. 3, 2004 JSME International Journal