Catherine Delamare

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Keywords: accelerometer, flank wear, signal processing, turning, vibration ... normal machining conditions, flank wear is regarded as the most preponderant.

EVALUATION OF CUTTING TOOL WEAR DURING LATHE DRY TURNING PROCESS FROM ACCELEROMETER DATA

ROGER SERRA1 AND WAFAÂ RMILI2 AND ABDELJALIL OUAHABI3 ENI Val de Loire, Laboratoire de Mécanique et Rhéologie E.A.2640, Rue de la chocolaterie, BP 3410 - 41034 Blois Cedex - France 2 Université de Tours, Laboratoire de Mécanique et Rhéologie E.A.2640, 7 Avenue Marcel Dassault, 37200 Tours – France 3 Université de Tours, Groupe Signal et Image, 7 Avenue Marcel Dassault, 37200 Tours - France 1

Abstract

In this article, an evaluation of cutting tool wear from accelerometer data is made in order to increase machining performance. To achieve this objective, the vibratory signatures produced during lathe dry turning process were measured from a tri-axial accelerometer mounted on the tool holder. Signal processing techniques are developed and validated by tool wear measurements under binocular optical microscope and white light interferometer. Therefore, we have quantified that the changes could be observed in vibration signatures during turning operation throughout the tool life and to extract a set of parameters which will be considered as tool wear indicators. The analysis of results indicates a good correlation between the evolution of accelerometer signals and flank wear. Finally, the significant parameters will be used as a cutting tool wear descriptor. Keywords: accelerometer, flank wear, signal processing, turning, vibration 1 INTRODUCTION In the machining process, the quality of the workpiece, like a dimensional accuracy and surface roughness, depends mainly on the state of the cutting tool. Monitoring of the cutting tool condition therefore plays a significant role in achieving consistent quality and controlling the overall cost of manufacturing. High performance machining consequently requires an evaluation of the cutting tool wear [1]. A wide variety of sensors, modeling and data analysis techniques have been developed for this purpose [2]. In general, the wear phenomenon on the cutting tool insert appears in several forms (e.g. flank wear, crater wear, chipping …). These forms depend essentially on cutting tool characteristics, workpiece material, cutting conditions and types of machining. Under normal machining conditions, flank wear is regarded as the most preponderant. Measurement of the width of flank wear (VB) is the most important parameter used to evaluate cutting tool lifespan [3, 4]. Flank wear results of the friction between the flank face of the tool and the machined surface. At the tool flank-workpiece interface, tool particles adhere to the workpiece surface and are periodically sheared off. The development of this wear form on the cutting tool is not a random phenomenon, and three phases can be observed during its lifetime: initial wear zone, stabilization wear zone and acceleration wear zone [5] as illustrated in figure 1.

4th International Conference on Tribology in Manufacturing Processes - ICTMP 2010

Figure 1: Flank wear related to cutting time [6] Generally, the evaluation of cutting tool wear can be made by two ways: direct and indirect methods. The direct methods consist into the measurement of the state of the tool wear by the classical optical systems such as CCD based cameras equipped binocular optical microscope and/or white light interferometer. Indirect techniques available in the literature are based on acoustic emission, cutting force measurement or vibration measurement [1-6]. The main objective of this work is to develop original signal processing techniques from accelerometer data in order to perform an evaluation of the cutting tool wear. The approach is based on vibratory signatures produced during lathe dry turning process and measured from a tri-axial accelerometer mounted on the tool holder. 2 PROPOSED SIGNAL PROCESSING TECHNIQUES Exploiting vibratory signals acquired during machining allows the estimation of the cutting tool state and the follow up of its evolution by calculating several parameters. Signal processing techniques based on statistical (variance), temporal (envelope) and frequency analysis (smoothed mean periodogram) are studied to extract a set of parameters which will be considered as tool wear indicators. A variance of signal X t  is defined by the equation:

 

 2   X 2  X  2 . The envelope is calculated from the analytic signal modulus related to the vibratory signal: ~ Z (t )  X (t )  j X (t )

with:

~ 1 X (t ) 

X  

  t 

d  TH X t 

Evaluation of cutting tool wear during lathe dry turning process from accelerometer data

Where: X t  is the random signal, Z t  is the analytic signal associated with X t  and ~ X (t )  THX t  is the Hilbert transform of signal X t  .

Finally, in frequency domain, the smoothed mean periodogram is determined by the following relation: g   X t 

FFT

2

FFT 

-1 CX  

×

FFT

SX  f 

where FFT is the Fast Fourier Transform. 3 EXPERIMENTAL SET-UP AND DATA ACQUISITION Long term tests according to ISO 3685-77 standard [7] have been conducted in order to evaluate the tool life. Thirty cutting tool inserts selected from the same production batch were used for a statistical study. We note that the experimental conditions for each cutting tool insert were strictly identical. 3.1

MACHINING DETAILS

In this study, experiments were conducted in the case of turning lathe process and the machining operations have been achieved on a 2.4kW power SOMAB model 500 lathe (CNC) as shown in figure 2. The workpiece material is a gray cast iron (FGL 250) and the cutting tool insert product by Safety Company of the standard designation CNMG 1204 08 5B (OR2500) is mounted on DCLNL 2525M 12 tool holder. Cutting operations were realized in dry conditions (without an applying cutting fluid) and all cutting experiments were performed under the following cutting conditions according with manufacturer recommendations [8]: cutting speed Vc = 340 m/mn, feed rate Vf = 0.18 mm/rev and depth of cut ap = 1.5 mm.

Figure 2: Machine tool used, Data acquisition system and Directions of tri-axial accelerometer mounted on tool holder

4th International Conference on Tribology in Manufacturing Processes - ICTMP 2010 3.2

VIBRATORY SIGNATURE ACQUISITION

The three-axis piezoelectric accelerometer was fixed on the tool holder to carry out measurement according the three directions x, y and z (figure 2). All vibratory signatures produced during lathe dry turning process have been measured in real time, recorded and analyzed with Multi-channel analyzer in the feeding, tangential (to the rotating workpiece) and radial directions (figure 3). This generates a large number of features, which was helpful to acquire maximum information about the tool wear state [9].

Figure 3: Accelerometer data in each direction Signals issued from accelerometer were acquired for a 70 seconds observation time (including 60 seconds of cutting time) and sampled at 16384Hz. Each signal contained 1146600 samples. Collected data was stored directly on the PC hard drive. Signal processing was performed using our suggested interactive interface. 3.3

DIRECT CONTROL OF CUTTING TOOL WEAR

From the first use up to end of its lifespan, we control the cutting tool state over regular intervals (after each cutting experiment). Tool wear has been measured using a CCD Camera SONY equipped binocular optical microscope as shown in figure 4.

Figure 4: Binocular optical microscope of new insert (a) and typical flank wear of worn insert (b).

Evaluation of cutting tool wear during lathe dry turning process from accelerometer data

A specific optical technique based on white light interferometer is used for more precision. This technique uses the vertical scanning interferometer (VSI) performed on a Wyko® NT-2000 optical profiler. To evaluate the tool wear degree, the mean of the flank wear width (VB) and the crater wear (KT) were measured by scanning the major flank (scanning size is 0.60×0.46mm²) as illustrated in figure 5.

Figure 5: 3D interferometer scanning of new insert (a) and typical flank wear VB (b). 4 RESULTS AND DISCUSSION The lifespan dispersion of the thirty cutting tool inserts studied is shown in figure 6. This result shows that although the cutting tool inserts belong to the same production batch and used under the same experimental conditions, their end of lifetime varies from 4 to 13 minutes which shows the complexity of the phenomenon of wear in an industrial context and the manufacturing process dispersion. According to figure 6, cutting tool insert lifespan dispersion permitted to identify four principal groups: 10, 11, 12 and 13 minutes (insert which lasted 4 minutes was considered as anomaly and it’s not taken into account in this study). 13 min mn 12 min mn 11 min mn 10 min mn 4 min mn

1 cutting tool insert 1 tool inserts 5 cutting 5 cutting tool inserts 15 15cutting cuttingtool inserts inserts 5

cutting tool inserts 4 cutting4tool inserts 5 cuttingtool inserts g5 cutting tool inserts

Figure 6: Lifespan of cutting tool inserts.

4th International Conference on Tribology in Manufacturing Processes - ICTMP 2010 4.1

TOOL WEAR CONTROL

The measured parameters (width and depth) of crater wear versus experiments indicate that the crater wear (KT) was not affected by wear mechanisms except some frictions due to chips contact during cutting process. It is relatively weak comparing to flank wear (VB) therefore the principal criterion of tool life is the flank wear (VB) resistance. In these experimental conditions, an allowable flank wear value (VB) of 0.3mm is adopted for the insert tool life, synonym of the end of tool life. Then, we stopped experiments when VB reached or exceeded this value. Flank wear evolution was tracked by plotting a flank wear widths (VB) versus cutting experiments as illustrated in figure 7 for the four principal groups. It can be clearly seen that the wear trend obey the universal wear law of any mechanical workpiece (initial wear or wearing zone, normal wear zone and accelerated wear zone) according with Figure 1. 5 inserts – 10 -min mn 4 plaquettes 10 min 15 inserts plaquettes 11min – 11 -min mn 5 plaquettes 12 min 5 inserts – 12 -min mn 4 plaquettes 13 min 4 inserts – 13 -min mn

in Breaking

Breaking-in

Wear stabilization Wear

stabilization

Wear Wear acceleration acceleration

Cutting time [min mn] ]

n

Figure 7: Mean flank wear (Vb) according to cutting experiment for each insert group In this figure, the three domains could be distinguished: breaking-in phase of the insert, from the first experiment up to first wear transition (cutting time between 2 nd and 3rd experiments), wear stabilization zone where the flank wear progressed uniformly, from the first wear transition up to second transition (cutting time between 8th and 10th experiments) and tool wear acceleration phase where the wear rate increases until rapid breakdown of the tool occurs. Furthermore, all cutting tool inserts had the same behaviour before reaching the second transition from the wear stabilization to the wear acceleration. Each group was characterized by its own local and specific stabilization/acceleration transition. However, using the direct control, all these transitions could be localized between 9 and 10 minutes of cutting time. In the following part, we will show how the vibratory analysis could be used to determine precisely, using an automatic detection, the transition to acceleration wear for each group which is

Evaluation of cutting tool wear during lathe dry turning process from accelerometer data

helpful in industrial applications to predict the end of tool life and then preserve a good quality of the product. 4.2

VIBRATORY ANALYSIS

The evaluation of the cutting tool wear development was conducted by analyzing the vibratory signature generated during lathe dry turning process. It shows an evolution of a vibration signature in the radial direction for an 11 minutes insert group.

Figure 8: Complete temporal observation of cutting process The estimation of the cutting tool state is obtained by calculating several parameters like variance, envelope and smoothed mean periodogram in order to extract a set of parameters which will be considered as tool wear indicators. Figure 9 correspond to the variance of vibratory signals acquired in X, Y, Z directions.

Figure 9: Variance versus experiments for each insert group

4th International Conference on Tribology in Manufacturing Processes - ICTMP 2010

On this figure the direction Y is difficult to exploit because of high levels recorded. According to X and Z directions, the evolution of the variance from beginning to the end of machining is very close, all the groups have the same behavior. The transition, or collapse, can be estimated at the 10th minute. From this state, each group has its own evolution up to the end of the tool life. Consequently, the variance seems to be a significant parameter of the cutting tool wear. Figure 10; 11, 12 and 13 correspond respectively to the envelope of vibratory signals acquired in X, Y, Z directions, the smoothed mean periodogram (DSP) for each insert group according to X, Y and Z directions. As for the variance, the levels recorded in the direction Y for the envelope parameter are raised and do not allow to distinguish the transition or the acceleration of the cutting tool wear. In addition, the level of the group of 13 minutes is definitely different from the other groups whereas the tests were strictly identical. As we can note it, the groups which last longest are also those whose level is lowest. Lastly, of the three directions, direction X seems to be the most adapted to the evaluation of the wear of the cutting tool. The evolution of this envelope according to the X direction of acquisition was sensitive to the deterioration of tool state. The three conventional phases of tool life (tool breaking-in, stabilization and acceleration of wear) could be distinguished.

Figure 10: Envelope versus experiments for each insert group

Figure 11: DSP versus experiments for each insert group according to X direction

Figure 12: DSP versus experiments for each insert group according to Y direction

Figure 13: DSP versus experiments for each insert group according to Z direction

Evaluation of cutting tool wear during lathe dry turning process from accelerometer data

In order to characterize the evolution of vibratory energy according to the cutting tool wear, the smoothed mean periodogram spectra 3D are represented in figures 11, 12 and 13, respectively in X, Y and Z directions. In these figures, we distinguish two frequential bands very clearly, one to 4200Hz and the other to 5100Hz. A third is slightly visible on direction X of the 11 minutes group (figure 11). A modal analysis of the cutting tool (tape test) has showed that these three frequencies correspond to the first three natural frequencies of the cutting tool. As illustrated figure12, the Y direction imposes highest levels compared to the other directions. That is in agreement with the literature because it corresponds to the direction of cut where the cutting energy is highest. The magnitude of vibration is more in the direction of main cutting direction Y than that in the radial direction X. The evolution of these periodogram spectra according to the X direction of acquisition was significant to the deterioration of tool state. The three conventional phases of tool life (tool breaking-in, stabilization and acceleration of wear) can be distinguished. Finally, we can note that the amplitude of vibration increases with the flank wear as it was established for the variance or envelope parameters. 5 CONCLUSIONS The present study investigates the use of vibration measurement to perform the evaluation of cutting tool wear during lathe dry turning process. To achieve this purpose, thirty cutting tools were studied under the same cutting conditions. The flank wear width of the cutting tool insert was measured using a binocular optical microscope and 3-D optical profiler after each machining. This allowed us to classify the thirty inserts used under the same experimental protocol into four groups associated with different lifespan, which demonstrated the complexity of the wear phenomenon in an industrial context. Generally, all cutting tool inserts had the same behavior according to tool life law. The level progressively increases with the time of machining. The cutting tool wear may be split then into three regions as expected. From accelerometer data acquired during the lathe dry turning process, we evaluated an analysis methods based on the calculation of the variance, the envelope and the smoothed mean periodogram of the signals. These analyses then demonstrated that the variance, the envelope and the smoothed mean periodogram are relevant parameters for use as a cutting tool wear descriptor. For any parameter selected, each group respects a certain order. Indeed, the groups which last longest are also those whose vibratory level is lowest. In addition, the highest levels are obtained in the cut direction in agreement with the literature. These descriptors should be used then to implement a binary detector of the cutting tool collapse. The effective sensitivity of the detector to automatically predict transitions between the three phases of tool life (tool breaking-in/stabilization and stabilization/acceleration of wear) is a project for our future work.

4th International Conference on Tribology in Manufacturing Processes - ICTMP 2010

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L. Dan and J. Mathew, “Tool wear and failure monitoring techniques for turning: a review”, International Journal of Machine Tools & Manufacture, vol. 30 (1990) pp. 79-598.

[2]

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[3]

C. Scheffer and P.S. Heyns, “Wear monitoring in turning operations using vibration and strain measurements”, Mechanical Systems and Signal Processing, vol. 15 (2001) pp. 1185-1202.

[4]

G.H. Lim, “Tool wear monitoring in machine turning”, Journal of Materials Processing Technology, vol. 51, N°1-4 (1995) pp. 25-36.

[5]

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[6]

Y. Altintas, “Manufacturing automation”, Cambridge University Press, 2000.

[7]

ISO 3685-77 Standard, “Tool-life testing single-point turning tools”, 1st edition (1977) pp. 5-15.

[8]

SANDVICK Coromant, “Turning tools catalogue”, Pratical handbook, English edition, 2007.

[9]

W. RMILI, “Analyse vibratoire pour l'étude de l’usure des outils de coupe en tournage”, PhD Dissertation, University of François-Rabelais, France (2007).