Abnormality prediction method and working device

Abstract

To determine deterioration of a moving mechanism.SOLUTION: An abnormality prediction method of a working device including a ball screw unit having a motor, a ball screw rotated by the motor, a nut screwed with the ball screw, and a slider to which the nut is fixed, and an alarm transmission unit includes: a data acquisition step 301 of acquiring change data of a torque value of the motor while moving the motor and moving the slider; a scoring step 302 of scoring the acquired change data; a determination step of determining whether or not it is in an abnormal pre-stage on the basis of the scored change data; and an alarm transmission step of transmitting an alarm when it is determined in the determination step that it is in the abnormal pre-stage.SELECTED DRAWING: Figure 3

Description

[Technical Field]

[0001] The present invention relates to a method for predicting an abnormality in a machining device equipped with a ball screw unit, and to the machining device. [Background technology]

[0002] A ball screw unit having a motor, a ball screw rotated by the motor, a nut that screws onto the ball screw, and a slider to which the nut is fixed is widely used as a movement mechanism for moving the machining table or machining tool of a machining device.

[0003] However, if the gap between the ball screw and the nut or the gap between the groove in the nut and the balls widens due to the intrusion of foreign matter or deterioration over time, overshoot occurs, causing the slider and nut to vibrate, which becomes a problem.

[0004] Therefore, a processing device has been proposed that measures the torque of a motor while moving a slider at a predetermined speed, and transmits a signal if the measured torque falls outside a threshold value (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Laid-Open No. 2017-185579 Summary of the Invention [Problem to be solved by the invention]

[0006] However, in the processing device shown in Patent Document 1, the average torque value varies depending on the axis, making it difficult to set the threshold value. In addition, the timing at which the torque actually starts to oscillate after it exceeds the threshold value also varies depending on the axis, making it difficult to predict axis oscillation in advance and determining deterioration of the moving mechanism.

[0007] An object of the present invention is to provide an abnormality prediction method and processing apparatus that can determine deterioration of a moving mechanism. [Means for solving the problem]

[0008] In order to solve the above-mentioned problems and achieve the object, the abnormality prediction method of the present invention is a method for predicting abnormalities in a processing device that includes a ball screw unit having a motor, a ball screw rotated by the motor, a nut threaded onto the ball screw, and a slider to which the nut is fixed, and an alarm issuing unit, and is characterized by comprising a data acquisition step of acquiring change data in the torque value of the motor while operating the motor to move the slider, a scoring step of converting the acquired change data into a score, a judgment step of determining whether or not the change data is in a pre-abnormal stage based on the scored change data, and a warning issuing step of issuing a warning if the judgment step determines that the state is in a pre-abnormal stage.

[0009] In the abnormality prediction method, the scoring step may involve frequency analysis of the change data during the constant velocity movement of the slider to decompose it into wavelength data of a plurality of frequency bands, and scoring the amplitude spectrum in a specific frequency band among the decomposed wavelength data of the plurality of frequency bands.

[0010] In the abnormality prediction method, the scoring step may score the number and magnitude of overshoots of the torque value after the movement of the slider has stopped, and the scored amplitude spectrum, the scored number of overshoots, and the scored magnitude of overshoots may be weighted and added together.

[0011] The processing apparatus of the present invention is a processing apparatus comprising a ball screw unit having a motor, a ball screw rotated by the motor, a nut threaded onto the ball screw, and a slider to which the nut is fixed, an alarm issuing unit, and a controller for controlling the ball screw unit, wherein the controller comprises a torque value change data acquisition unit that acquires change data of the motor's torque value while operating the motor to move the slider, a scoring unit that converts the change data acquired by the torque value change data acquisition unit into a score, a judgment unit that judges whether or not the change data is in a pre-abnormal stage based on the scored change data, and an alarm issuing unit that causes the alarm to be issued from the alarm issuing unit if the judgment unit judges that the data is in a pre-abnormal stage.

[0012] In the processing device, the scoring unit may perform frequency analysis on the change data during the constant velocity movement of the slider to decompose it into wavelength data of a plurality of frequency bands, and score an amplitude spectrum in a specific frequency band among the decomposed wavelength data of the plurality of frequency bands.

[0013] In the processing device, the scoring unit may score the number and magnitude of overshoots of the torque value after the movement of the slider has stopped, and may weight and add up the scored amplitude spectrum, the scored number of overshoots, and the scored magnitude of overshoots. [Effects of the Invention]

[0014] The present invention provides an advantage in that it is possible to determine the deterioration of a moving mechanism. [Brief explanation of the drawings]

[0015] [Figure 1] FIG. 1 is a perspective view schematically illustrating an example of the configuration of a processing device according to the first embodiment. [Figure 2] FIG. 2 is a side view schematically showing an X-axis moving unit and the like of the processing apparatus shown in FIG. [Figure 3]FIG. 3 is a flowchart showing the flow of preparation steps of the abnormality prediction method according to the first embodiment. [Figure 4] FIG. 4 is a diagram showing an example of change data acquired in the data acquisition step of the preparation step of the abnormality prediction method shown in FIG. [Figure 5] FIG. 5 is a diagram showing an example of partial data of the variation data that is subjected to short-time Fourier transform in the scoring step of the abnormality prediction method shown in FIG. [Figure 6] FIG. 6 is a diagram schematically illustrating an example of transformed partial data after the partial data is subjected to short-time Fourier transform in the scoring step of the abnormality prediction method shown in FIG. [Figure 7] FIG. 7 is a diagram showing an example of the judgment data calculated in the scoring step of the abnormality prediction method shown in FIG. [Figure 8] FIG. 8 is a flowchart showing the flow of the abnormality prediction step of the abnormality prediction method according to the first embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0016] Modes (embodiments) for carrying out the present invention will be described in detail with reference to the drawings. The present invention is not limited to the contents described in the following embodiments. Furthermore, the components described below include those that can be easily imagined by a person skilled in the art and those that are substantially the same. Furthermore, the configurations described below can be combined as appropriate. Furthermore, various omissions, substitutions, or modifications of the configuration can be made within the scope of the gist of the present invention.

[0017] [Embodiment 1] A processing apparatus according to a first embodiment of the present invention will be described with reference to the drawings. Fig. 1 is a perspective view schematically showing an example of the configuration of the processing apparatus according to the first embodiment. Fig. 2 is a side view schematically showing an X-axis moving unit and the like of the processing apparatus shown in Fig. 1.

[0018] (workpiece) The processing apparatus 1 according to the first embodiment is a cutting apparatus that cuts a workpiece 200. The workpiece 200 to be processed by the processing apparatus 1 shown in Fig. 1 is a wafer such as a disk-shaped semiconductor wafer or an optical device wafer, which has a base material such as silicon, gallium arsenide, SiC (silicon carbide), or sapphire. The workpiece 200 has devices 203 formed in areas partitioned in a grid pattern by a plurality of planned dividing lines 202 formed in a grid pattern on a surface 201.

[0019] The device 203 is, for example, an integrated circuit such as an IC (Integrated Circuit) or an LSI (Large Scale Integration), an image sensor such as a CCD (Charge Coupled Device) or a CMOS (Complementary Metal Oxide Semiconductor), a MEMS (Micro Electro Mechanical Systems), or various types of memory (semiconductor memory device).

[0020] Furthermore, the workpiece 200 of the present invention may be a so-called TAIKO (registered trademark) wafer having a thin central portion and a thick peripheral portion, or may be a resin package substrate such as a rectangular QFN (Quad Flat No leaded) package substrate having a plurality of devices sealed with resin, a ceramic substrate, a ferrite substrate, a substrate containing at least one of nickel and iron, a glass substrate, etc. In embodiment 1, the workpiece 200 has an adhesive tape 206 attached to a back surface 204 on the back side of the front surface 201, and is supported by the annular frame 205.

[0021] (Processing equipment) 1 is a cutting device that holds a workpiece 200 on a chuck table 10 and cuts it with a cutting blade 21 along a planned division line 202. As shown in FIG. 1, the processing device 1 includes the chuck table 10 that holds the workpiece 200 by suction on a holding surface 11, a cutting unit 20 that cuts the workpiece 200 held on the chuck table 10 with the cutting blade 21 while supplying cutting water, an imaging unit 30 that takes an image of the workpiece 200 held on the chuck table 10, and a controller 100.

[0022] 1, the processing apparatus 1 also includes a moving unit 40 that moves the chuck table 10 and the cutting unit 20 relative to each other. The moving unit 40 includes at least an X-axis moving unit 41, which is a processing feed unit that feeds the chuck table 10 in the X-axis direction, which is a cutting direction parallel to the horizontal direction; a Y-axis moving unit 42, which is an indexing feed unit that indexes and feeds the cutting unit 20 in the Y-axis direction, which is parallel to the horizontal direction and perpendicular to the X-axis direction; a Z-axis moving unit 43, which is a cutting feed unit that feeds the cutting unit 20 in the Z-axis direction, which is parallel to the vertical direction and perpendicular to both the X-axis and Y-axis directions; and a rotational moving unit 44 that rotates the chuck table 10 around an axis parallel to the Z-axis direction. The X-axis moving unit 41, the Y-axis moving unit 42, and the Z-axis moving unit 43 correspond to ball screw units.

[0023] The X-axis moving unit 41 moves the moving plate 4 (corresponding to a slider and shown in FIG. 2) that supports the chuck table 10 and the rotational moving unit 44 in the X-axis direction, which is the processing feed direction, thereby processing-feeding the chuck table 10 and the cutting unit 20 relatively along the X-axis direction. The X-axis moving unit 41 is also a cutting feed unit that is installed on the device main body 2 and moves the chuck table 10 back and forth in the X-axis direction, which is the cutting direction.

[0024] The Y-axis moving unit 42 is installed on the support frame 3 erected from the device main body 2, and moves the second moving plate 5 (corresponding to a slider) in the Y-axis direction, which is the indexing feed direction, thereby moving the cutting unit 20 in the Y-axis direction, and indexing-feeding the chuck table 10 and the cutting unit 20 relatively along the Y-axis direction. The Z-axis moving unit 43 is installed on the second moving plate 5, which is movable in the Y-axis direction by the Y-axis moving unit 42, and moves the third moving plate 6 (corresponding to a slider) in the Z-axis direction, which is the cutting feed direction, thereby moving the cutting unit 20 in the Z-axis direction, and indexing-feeding the chuck table 10 and the cutting unit 20 relatively along the Z-axis. The rotational moving unit 44 is disposed on the moving plate 4.

[0025] 2, the X-axis moving unit 41, the Y-axis moving unit 42, and the Z-axis moving unit 43 each include a motor 45 fixed to either the device main body 2, the support frame 3, or the second moving plate 5, a well-known ball screw 46 rotatably provided about its axis and rotated about its axis by the motor 45, a nut 47 threadedly engaged with the ball screw 46, one of the moving plates 4, 5, or 6 to which the nut 47 is fixed, and a well-known guide rail (not shown) that supports one of the moving plates 4, 5, or 6 movably in the X-axis, Y-axis, or Z-axis directions. The rotational moving unit 44 includes a well-known motor and the like that rotates the chuck table 10 about its axis.

[0026] Since the moving units 41, 42, and 43 have substantially the same configuration, Fig. 2 shows only the X-axis moving unit 41 as a representative. The motor 45 of each moving unit 41, 42, and 43 measures the torque of the output shaft that rotates the ball screw 46 around its axis, and outputs the measured torque (hereinafter referred to as measured torque) to the controller 100 at predetermined time intervals (several milliseconds in the first embodiment).

[0027] The chuck table 10 is disk-shaped, and a holding surface 11 that holds the workpiece 200 is formed from porous ceramic or the like. The chuck table 10 is provided so as to be movable in the X-axis direction by an X-axis movement unit 41 between a processing area below the cutting unit 20 and a carry-in / out area that is spaced from below the cutting unit 20 and where the workpiece 200 is carried in and out. The chuck table 10 is supported by a rotational movement unit 44, and is provided so as to be rotatable by the rotational movement unit 44 about an axis parallel to the Z-axis direction.

[0028] The chuck table 10 is connected to a vacuum suction source (not shown), and is sucked by the vacuum suction source to suck and hold the workpiece 200 placed on the holding surface 11. In the first embodiment, the chuck table 10 sucks and holds the back surface 204 of the workpiece 200 via adhesive tape 206. Also, as shown in FIG. 1, a plurality of clamp units 12 that clamp an annular frame 205 are provided around the periphery of the chuck table 10. Note that in the present invention, the adhesive tape 206 does not have to be attached to the workpiece 200, and the workpiece 200 may be held directly by the chuck table 10, and the chuck table 10 does not have to be disk-shaped.

[0029] The cutting unit 20 is a processing unit in which a cutting blade 21 is fixed to the tip of a spindle 22 and cuts a workpiece 200 held on the chuck table 10. The cutting unit 20 is provided so as to be movable in the Y-axis direction by a Y-axis moving unit 42 relative to the workpiece 200 held on the chuck table 10, and is provided so as to be movable in the Z-axis direction by a Z-axis moving unit 43.

[0030] 1, the cutting unit 20 is mounted on a support frame 3 that stands upright on the device main body 2 via a Y-axis moving unit 42, a Z-axis moving unit 43, etc. The cutting unit 20 is capable of positioning the cutting blade 21 at any position on the holding surface 11 of the chuck table 10 by the Y-axis moving unit 42 and the Z-axis moving unit 43.

[0031] The cutting unit 20 comprises a cutting blade 21, a spindle 22 to which the cutting blade 21 is fixed at its tip, a spindle housing 23 that is movable in the Y-axis direction and the Z-axis direction by a Y-axis moving unit 42 and a Z-axis moving unit 43, and a cutting water supply nozzle that supplies cutting water to the cutting blade 21.

[0032] The cutting blade 21 is an extremely thin cutting grindstone having a substantially ring shape. In the first embodiment, the cutting blade 21 is a so-called hub blade that includes an annular circular base and an annular cutting edge that is disposed on the outer periphery of the circular base and cuts the workpiece 200. The cutting edge is made of abrasive grains such as diamond or CBN (Cubic Boron Nitride) and a bonding material such as metal or resin, and is formed to a predetermined thickness. The cutting edge of the cutting blade 21 wears when cutting the workpiece 200. Note that in the present invention, the cutting blade 21 may be a so-called washer blade that is composed only of a cutting edge.

[0033] The spindle 22 is rotated about its axis by a spindle motor provided in a spindle housing 23, thereby rotating the cutting blade 21.

[0034] The spindle housing 23 supports the spindle 22 rotatably about its axis and incorporates a spindle motor (not shown) that rotates the spindle 22 about its axis. The spindle housing 23 is fixed to the lower end of the third moving plate 6.

[0035] The axes of the cutting blade 21 and spindle 22 of the cutting unit 20 are set parallel to the Y-axis direction. The cutting unit 20 cuts the workpiece 200 with the cutting blade 21 fixed to the tip of the spindle 22, which rotates around its axis, while supplying cutting water to the cutting blade 21 from a cutting water supply nozzle.

[0036] The imaging unit 30 is fixed to the spindle housing 23 of the cutting unit 20 so as to move integrally with the cutting unit 20. The imaging unit 30 is equipped with an imaging element that captures an image of an area to be divided of the workpiece 200 held on the chuck table 10 before cutting. The imaging element is, for example, a CCD (Charge-Coupled Device) imaging element or a CMOS (Complementary MOS) imaging element. The imaging unit 30 captures an image of the workpiece 200 held on the chuck table 10 to obtain an image for performing alignment between the workpiece 200 and the cutting blade 21, and outputs the obtained image to the controller 100.

[0037] The machining apparatus 1 also includes an X-axis position detection unit (not shown) for detecting the position of the chuck table 10 in the X-axis direction, a Y-axis position detection unit (not shown) for detecting the position of the cutting unit 20 in the Y-axis direction, and a Z-axis position detection unit for detecting the position of the cutting unit 20 in the Z-axis direction. The X-axis position detection unit and the Y-axis position detection unit may be configured with a linear scale parallel to the X-axis direction or the Y-axis direction, and a read head. The Z-axis position detection unit detects the position of the cutting unit 20 in the Z-axis direction using motor pulses. The X-axis position detection unit, the Y-axis position detection unit, and the Z-axis position detection unit output the position of the chuck table 10 in the X-axis direction and the position of the lower end of the cutting blade of the cutting unit 20 in the Y-axis direction or the Z-axis direction to the controller 100.

[0038] In the first embodiment, the positions of the chuck table 10 and cutting unit 20 of the processing device 1 in the X-axis direction, Y-axis direction, and Z-axis direction are determined based on a predetermined reference position (not shown). In the first embodiment, the reference position of the cutting unit 20 in the Z-axis direction is the position where the holding surface 11 of the chuck table 10 and the lower end of the cutting edge of the cutting blade 21 are located on the same plane.

[0039] The controller 100 controls each component of the machining apparatus 1 to cause the machining apparatus 1 to perform a machining operation on the workpiece 200. That is, the controller 100 controls at least the movement units 41, 42, and 43, which are ball screw units. The controller 100 is a computer having an arithmetic processing unit having a microprocessor such as a central processing unit (CPU), a storage device having memory such as a read only memory (ROM) or a random access memory (RAM), and an input / output interface device. The arithmetic processing unit of the controller 100 performs arithmetic processing in accordance with a computer program stored in the storage device, and outputs control signals for controlling the machining apparatus 1 to each component of the machining apparatus 1 via the input / output interface device.

[0040] The processing device 1 also includes a display unit 110 configured with a liquid crystal display device or the like for displaying the status and images of the processing operation and connected to the controller 100, an input unit 120 used by the operator to register processing content information and the like and connected to the controller 100, and an alarm issuing unit 130 connected to the controller 100. The input unit 120 is configured with at least one of a touch panel provided on the display unit 110 and an external input device such as a keyboard. The alarm issuing unit 130 issues an alarm to the operator by emitting at least one of sound and light.

[0041] 1, the controller 100 includes a processing control unit 101, a torque value change data acquisition unit 102, a scoring unit 103, a determination unit 104, and an alarm issuing unit 105. The processing control unit 101 controls each component of the processing device 1 to cause the processing device 1 to perform a processing operation on the workpiece 200.

[0042] The torque value change data acquisition unit 102 acquires change data 500 (shown in FIG. 4) of the torque value of the motor 45 while moving the movable plates 4, 5, and 6 by operating the motor 45. The scoring unit 103 scores the change data 500 acquired by the torque value change data acquisition unit 102. The judgment unit 104 judges whether or not the state is in a pre-abnormal stage or an abnormal state based on the scored change data. The alarm issuing unit 105 issues an alarm from the alarm issuing unit 130 when the judgment unit 104 judges that the state is in a pre-abnormal stage or an abnormal state.

[0043] The functions of the processing control unit 101, torque value change data acquisition unit 102, scoring unit 103, judgment unit 104, and alarm issuing unit 105 are realized by the arithmetic processing unit performing arithmetic processing in accordance with a computer program stored in the storage device.

[0044] (Machining operation) The processing device 1 having the above-described configuration starts a processing operation when the operator registers processing conditions in the controller 100, and the workpiece 200 before cutting is placed on the holding surface 11 of the chuck table 10, and the controller 100 receives a command from the operator to start the processing operation. When the processing device 1 starts a processing operation, the processing control unit 101 of the controller 100 sucks and holds the back surface 204 side to the holding surface 11 of the chuck table 10 via the adhesive tape 206, and clamps the annular frame 205 with the clamp unit 12.

[0045] In the machining operation, the machining control unit 101 of the controller 100 controls the moving unit 40 to move the chuck table 10 toward the machining area, the imaging unit 30 captures an image of the workpiece 200, and performs alignment based on the image captured by the imaging unit 30. In the machining operation, the machining control unit 101 of the controller 100 rotates the cutting blade 21 around its axis while relatively moving the workpiece 200 and the cutting unit 20 along the planned division lines 202, and divides the workpiece 200 into individual devices 203 by causing the cutting blade 21 to cut into each planned division line 202 while supplying cutting water from a cutting water supply nozzle.

[0046] In the processing operation, the processing device 1 has the processing control unit 101 of the controller 100 cut all of the planned division lines 202 of the workpiece 200 and divide the workpiece 200 into individual devices 203, and then moves the workpiece 200 divided into individual devices 203 toward the loading / unloading area, releases the suction holding of the holding surface 11 and the clamping of the clamping unit 12 in the loading / unloading area, and completes the processing operation.

[0047] (Method of predicting abnormalities) Next, an abnormality prediction method according to embodiment 1 will be described with reference to the drawings. The abnormality prediction method according to embodiment 1 is a method for predicting an abnormality in the processing device 1 described above, and in embodiment 1, is a method for predicting an abnormality in each of the moving units 41, 42, and 43. The abnormality prediction method according to embodiment 1 includes a preparation step 300 shown in Fig. 3 and an abnormality prediction step 400 shown in Fig. 8. Note that, below, a method for predicting an abnormality in the X-axis moving unit 41 will be described as a representative of the moving units 41, 42, and 43.

[0048] (Preparation step) First, the preparation step 300 will be described. FIG. 3 is a flowchart showing the flow of the preparation step of the anomaly prediction method according to the first embodiment. FIG. 4 is a diagram showing an example of change data acquired in the data acquisition step of the preparation step of the anomaly prediction method shown in FIG. 3. FIG. 5 is a diagram showing an example of partial data of the change data that is subjected to a short-time Fourier transform in the scoring step of the anomaly prediction method shown in FIG. 3. FIG. 6 is a diagram showing an example of converted partial data after the partial data is subjected to a short-time Fourier transform in the scoring step of the anomaly prediction method shown in FIG. 3. FIG. 7 is a diagram showing an example of judgment data calculated in the scoring step of the anomaly prediction method shown in FIG. 3.

[0049] 3 is a step of setting a first threshold value 531 (shown in FIG. 7) and a second threshold value 532 (shown in FIG. 7), which are criteria for determining whether there is an abnormality in the X-axis moving unit 41 of the processing device 1. As shown in FIG. 3, the preparation step 300 includes a data acquisition step 301, a scoring step 302, and a threshold value setting step 303.

[0050] The data acquisition step 301 is a step of acquiring torque value change data 500 (shown in FIG. 4) of the motor 45 while moving the movable plate 4 by operating the motor 45. In the first embodiment, in the data acquisition step 301, the processing apparatus 1 causes the X-axis moving unit 41 to move the movable plate 4 within a predetermined range, and the torque value change data acquisition unit 102 of the controller 100 acquires the measured torque from the motor 45 while the movable plate 4 is moving at predetermined time intervals. Note that in the data acquisition step 301, when the moving plate 4 is moved, the processing apparatus 1 accelerates the moving plate 4 from a stopped state to a predetermined speed, moves it at a constant speed in the X-axis direction at the predetermined speed for a predetermined time, and then decelerates and stops the moving plate 4.

[0051] In the data acquisition step 301, the torque value change data acquisition unit 102 of the controller 100 of the processing device 1 calculates the torque value (TV) based on the following equation 1, using each measured torque acquired from the motor 45 as the measured torque (TM). Torque value (TV) = Measured torque (TM) / Rated torque (TR) Formula 1

[0052] The rated torque (TR) is the rated torque of the motor 45, and refers to the driving torque of the motor 45 when the rated output is generated after the operation of the motor 45 has stabilized at the rated voltage and rated frequency, and is also called the full load torque.

[0053] In the data acquisition step 301, the torque value change data acquisition unit 102 of the controller 100 of the processing device 1 generates change data 500 shown in Fig. 4 from the torque value (TV) while the motor 45 is being driven. Note that in the change data 500 shown in Fig. 4, the horizontal axis indicates the time from when the moving plate 4 starts to move until it stops, and the vertical axis indicates the torque value (%) calculated from the measured torque (TM) acquired from the motor 45 at predetermined time intervals.

[0054] 4, the change in torque value during acceleration 501 and deceleration 503 of the moving plate 4 is larger than the change in torque value (TV) during constant velocity movement 502 of the moving plate 4. In the change data 500 shown in FIG. 4, an overshoot 504 (shown in FIG. 4) in which the torque value (TV) increases or decreases may occur after the moving plate 4 stops after deceleration 503.

[0055] Also, in embodiment 1, in the data acquisition step 301, the torque value change data acquisition unit 102 of the controller 100 moves the movable plate 4 several thousand times using the motor 45 of the X-axis moving unit 41, and generates several thousand pieces of change data 500 shown in Figure 4 for each movement of the movable plate 4, and then proceeds to the scoring step 302.

[0056] The scoring step 302 is a step of scoring the acquired change data 500. In the first embodiment, in the scoring step 302, the scoring unit 103 of the controller 100 of the processing device 1 divides the uniform velocity movement times 502 of each change data 500 into time intervals 505 that are shorter than the uniform velocity movement times 502, to generate partial data 510, an example of which is shown in FIG. 5. In generating the partial data 510, the scoring unit 103 of the controller 100 of the processing device 1 divides the uniform velocity movement times 502 of the change data 500 into time intervals 505 such that parts of the time intervals 505 overlap with each other and all of the uniform velocity movement times 502 are included in one of the partial data 510. In the partial data 510, an example of which is shown in FIG. 5, the horizontal axis indicates time and the vertical axis indicates torque value.

[0057] In the scoring step 302, the scoring unit 103 of the controller 100 of the processing device 1 performs a short-time Fourier transform on each piece of partial data 510, an example of which is shown in Fig. 5, based on the following equation 2, to generate a plurality of pieces of converted partial data 520, an example of which is shown in Fig. 6. Note that there is a one-to-one correspondence between the partial data 510 and the converted partial data 520, i.e., when the short-time Fourier transform is performed on one piece of partial data 510, one piece of converted partial data 520 is generated.

[0058]

number

[0059] The short-time Fourier transform is a technique in which a window function is applied to waveform data to extract a time width, and then a discrete Fourier transform is performed within that time width, and this is repeated for the entire time period being analyzed. In Equation 2, e is the natural logarithm, x is the frequency, i is the imaginary number, and w(t) is the window function.

[0060] The result of the short-time Fourier transform is a complex number, and the absolute value (magnitude) of this complex number is called the amplitude spectrum. In the example of transformed partial data 520 shown in FIG. 6, the horizontal axis represents frequency and the vertical axis represents amplitude spectrum. Thus, in the scoring step 302 of the first embodiment, the scoring unit 103 generates the transformed partial data 520, thereby performing frequency analysis on the change data 500 during the constant velocity movement of the moving plate 4 and decomposing the change data 500 into the transformed partial data 520, which is wavelength data of a plurality of frequency bands.

[0061] In the first embodiment, in the scoring step 302, the scoring unit 103 of the controller 100 of the machining device 1 overlaps the multiple converted partial data 520 at overlapping portions of the variation data 500, and calculates the average value (A) of the amplitude spectrum in a specific frequency band (for example, 90 Hz or more and 200 Hz or less in the first embodiment). The specific frequency band is a band that includes the frequency of vibrations that occur when an abnormality occurs in the X-axis moving unit 41 that is the target of abnormality prediction. Thus, in the first embodiment, in the scoring step 302, the scoring unit 103 calculates the average value (A) of the amplitude spectrum, thereby scoring the amplitude spectrum in the specific frequency band of the converted partial data 520, which is the wavelength data of the decomposed multiple frequency bands.

[0062] In the scoring step in the first embodiment, the scoring unit 103 of the controller 100 of the processing device 1 counts the magnitude (B) of the overshoot 504 after the moving plate 4 stops during deceleration 503 of each change data 500 and the number (C) of overshoots 504 after the moving plate 4 stops. In the first embodiment, in the scoring step, the scoring unit 103 of the controller 100 of the processing device 1 counts the magnitude (B) of the overshoot 504 as the sum of the torque values ​​of each overshoot 504.

[0063] In the case of the variation data 500 shown in Fig. 4, the torque value of the first overshoot 504 is "28%" and the torque value of the second overshoot 504 is "5%," so the magnitude (B) of the overshoot 504 is counted as "28 + 5" = "33". In addition, in the case of the variation data 500 shown in Fig. 4, the overshoot 504 occurs twice, so the number (C) of the overshoots 504 is counted as "2".

[0064] In the first embodiment, in the scoring step 302, the processing device 1 calculates a judgment value (X) based on the average value (A) of the amplitude spectrum calculated by the scoring unit 103 of the controller 100, the magnitude (B) of the counted overshoots 504, the number (C) of the counted overshoots 504, and Equation 3. The judgment value (X) is the scored change data.

[0065]

number

[0066] In Equation 3, α, β, and γ are coefficients, and are values ​​that are set appropriately depending on the target of abnormality prediction. In the first embodiment, for example, when the target of abnormality prediction is the X-axis moving unit 41, the values ​​of α, β, and γ are set so that the average value (A) of the amplitude spectrum is weighted most heavily (for example, α is set larger than β and γ). Also, in the first embodiment, when the target of abnormality prediction is the Y-axis moving unit 42, the values ​​of α, β, and γ are set so that the number (C) of overshoots 504 is weighted more heavily than the average value (A) of the amplitude spectrum (for example, γ is set larger than α).

[0067] Thus, in the first embodiment, in the scoring step 302, the scoring unit 103 calculates a judgment value (X) to score the number (C) and magnitude (B) of overshoots 504 of the torque value after the movement of the moving plate 4 has stopped, and then weights and sums up the scored average value (A) of the amplitude spectrum, the scored number (C) of overshoots 504, and the scored magnitude (B) of overshoots 504 to calculate several thousand judgment values ​​(X) (i.e., corresponding one-to-one to the change data 500).

[0068] Also, in embodiment 1, in the scoring step 302, the scoring unit 103 of the controller 100 of the processing device 1 calculates the minimum value of the torque value (TV) of each change data 500, and stores the calculated minimum value of the torque value of each change data 500 in a one-to-one correspondence with the calculated judgment value (X) in the storage device.

[0069] In the first embodiment, in the scoring step 302, the scoring unit 103 of the controller 100 of the processing device 1 generates judgment data 530, an example of which is shown in FIG. 7, from the minimum torque value (TV) of each variation data 500 stored in the storage device and a judgment value (X) calculated from each variation data 500, and then proceeds to the threshold setting step 303. In the judgment data 530 shown in FIG. 7, the horizontal axis indicates the minimum torque value, and the vertical axis indicates the average value (A) of the amplitude spectrum. In other words, in the judgment data 530 shown in FIG. 7, the vertical axis indicates the judgment value (X) when the above-mentioned β and γ are zero.

[0070] Also, in embodiment 1, in the scoring step 302, the processing device 1 standardizes the thousands of calculated judgment values ​​(X) by the scoring unit 103 of the controller 100 into values ​​between "0" and "100" and scores them.

[0071] In addition, since the judgment value (X) and the average value (A) of the amplitude spectrum are calculated by performing a short-time Fourier transform on the change data 500 of the torque value (TV) of the motor 45, there is less variation for each processing device 1, i.e., each X-axis moving unit 41, than there is for the torque of the motor 45.

[0072] The threshold setting step 303 is a step of setting a first threshold 531 (shown in FIG. 7) and a second threshold 532 (shown in FIG. 7) which are judgment criteria for judging an abnormality in the X-axis moving unit 41 of the processing device 1 that is the target of abnormality prediction. In the first embodiment, the threshold setting step 303 sets the first threshold 531 and the second threshold 532 which are judgment criteria for the processing device 1 that is the target of abnormality prediction based on the judgment value (X) of the judgment data 530, i.e., the average value (A) of the amplitude spectrum when β and γ are zero.

[0073] The second threshold 532 is a value that can be used to determine that the X-axis moving unit 41, which is the target of abnormality prediction, is in an abnormal state unsuitable for machining when the average value (A) of the amplitude spectrum exceeds the second threshold 532 when the judgment value (X), i.e., β and γ, are zero. The first threshold 531 is a value smaller than the second threshold 532, and can be used to determine that the X-axis moving unit 41, which is the target of abnormality prediction, is in a pre-abnormal stage just before entering an abnormal state unsuitable for machining when the average value (A) of the amplitude spectrum exceeds the first threshold 531 when the judgment value (X), i.e., β and γ, are zero. In the case of judgment data 530, an example of which is shown in FIG. 7, the first threshold 531 is 9.26 and the second threshold 532 is 12.55.

[0074] The processing device 1 used to generate the judgment data 530 in the preparation step 300 may be used only to generate the judgment data 530 without cutting the workpiece 200, or may be used to cut the workpiece 200 after being used to generate the judgment data 530.

[0075] (Abnormality prediction step) Next, the abnormality prediction step 400 will be described. Fig. 8 is a flowchart showing the flow of the abnormality prediction step of the abnormality prediction method according to the first embodiment. The abnormality prediction step 400 shown in Fig. 8 is a method for predicting an abnormality in the X-axis moving unit 41 of the processing apparatus 1 (hereinafter, designated by the reference symbol 1-1 to distinguish it from the others) that is the target of the abnormality prediction. The processing apparatus 1-1 that performs the abnormality prediction step 400 may be the processing apparatus 1 that performed the preparation step 300, or may be another processing apparatus 1-1 that is the same model as the processing apparatus 1 that performed the preparation step 300.

[0076] The processing device 1-1 performs an abnormality prediction step 400 shown in Fig. 8 at a predetermined timing except during operation, such as during cutting of the workpiece 200 or during transport of the workpiece 200. In the abnormality prediction step 400 shown in Fig. 8, the same parts as those in the preparation step 300 shown in Fig. 3 are denoted by the same reference numerals, and their explanations will be omitted. As shown in Fig. 8, the abnormality prediction step 400 includes a data acquisition step 301, a scoring step 302, a judgment step 401, and a warning transmission step 402.

[0077] In the first embodiment, in the data acquisition step 301 of the abnormality prediction step 400, the torque value change data acquisition unit 102 of the controller 100 of the processing device 1-1 acquires the change data 500 shown in Fig. 3, similar to the preparation step 300. Note that in the first embodiment, in the data acquisition step 301 of the abnormality prediction step 400, the torque value change data acquisition unit 102 of the controller 100 of the processing device 1-1 moves the moving plate 4 only once using the motor 45 of the X-axis moving unit 41 to generate only one piece of change data 500 shown in Fig. 3, and then proceeds to the scoring step 302.

[0078] In embodiment 1, in scoring step 302, the scoring unit 103 of the controller 100 of the processing device 1-1 calculates the average value (A) of the amplitude spectrum of the variation data 500 acquired in the data acquisition step 301, as in the preparation step 300, counts the magnitude (B) and number (C) of the overshoots 504, calculates a judgment value (X) based on these and equation 3, and proceeds to judgment step 401.

[0079] Determination step 401 is a step of determining whether the processing device 1-1 is in a pre-abnormal stage or an abnormal state based on the determination value (X) calculated in scoring step 302, which is the scored change data. In embodiment 1, in determination step 401, the determination unit 104 of the controller 100 of the processing device 1-1 determines that the processing device 1-1 is in an abnormal state when the determination value (X) calculated in scoring step 302 exceeds the second threshold value 532, and determines that the processing device 1-1 is in a pre-abnormal stage when the determination value (X) calculated in scoring step 302 exceeds the first threshold value 531 and is equal to or less than the second threshold value 532. In embodiment 1, in determination step 401, when the determination unit 104 of the controller 100 determines that the processing device 1-1 is in a pre-abnormal stage or an abnormal state (Yes), the processing device 1-1 proceeds to warning transmission step 402.

[0080] The warning issuing step 402 is a step of issuing a warning when it is determined in the judgment step 401 that the state is in a pre-abnormal stage or an abnormal state. In the first embodiment, in the warning issuing step 402, the alarm issuing section 105 of the controller 100 of the processing device 1-1 operates the alarm issuing unit 130 to issue an alarm to the operator, thereby terminating the abnormality prediction step 400 of the abnormality prediction method. Also, in the judgment step 401, if the judgment section 104 of the controller 100 determines that the state is not both in a pre-abnormal stage and an abnormal state (No), the processing device 1-1 terminates the abnormality prediction step 400 of the abnormality prediction method.

[0081] As described above, the processing device 1, 1-1 and abnormality prediction method according to embodiment 1 determine the pre-abnormal stage based on the average value (A) of the amplitude spectrum, which has less variation for each processing device 1, 1-1 compared to the average value of the torque of the motor 45. This has the effect of being able to predict the oscillation of the X-axis moving unit 41 before it reaches an abnormal state and determining the deterioration of the X-axis moving unit 41, which is the moving mechanism.

[0082] Furthermore, the processing apparatus 1, 1-1 and the abnormality prediction method according to the first embodiment set the first threshold value 531 and the second threshold value 532, which are criteria for determining whether or not the state is in the pre-abnormal stage or abnormal state, based on the average value (A) or judgment value (X) of several thousand amplitude spectra, thereby improving the accuracy of determining whether or not the state is in the pre-abnormal stage or abnormal state.

[0083] Furthermore, the processing apparatus 1, 1-1 and the abnormality prediction method according to the first embodiment calculate a judgment value (X) for determining whether or not the state is in the pre-abnormal stage by weighting and adding up the average value (A) of the amplitude spectrum, the number (C) of overshoots 504, and the magnitude (B) of the overshoots 504, thereby improving the accuracy of the judgment as to whether or not the state is in the pre-abnormal stage or an abnormal state.

[0084] As described above, in the present invention, the determination of whether the X-axis moving unit 41 of the processing device 1, 1-1 is in a pre-abnormal stage or an abnormal state may be made based on either the determination value (X) when at least one of β and γ in Equation 3 is a number other than zero, or the determination value (X) when both β and γ in Equation 3 are zero, i.e., the average value (A) of the amplitude spectrum. That is, in the present invention, in both the preparation step 300 and the abnormality prediction step 400, at least one of β and γ in Equation 3 may be a number other than zero, or both β and γ in Equation 3 may be zero.

[0085] The present invention is not limited to the above-described embodiment. In other words, various modifications can be made without departing from the gist of the present invention. In the present invention, abnormality prediction may be performed not only on the X-axis moving unit 41 but also on a moving mechanism equipped with a ball screw, such as the Y-axis moving unit 42 and the Z-axis moving unit 43. Furthermore, in the present invention, the processing apparatus 1 is not limited to a cutting apparatus that cuts the workpiece 200, but may also be a grinding apparatus that grinds the workpiece 200, a polishing apparatus that polishes the workpiece 200, a bite cutting apparatus that cuts the workpiece 200 with a bite, or a laser processing apparatus that laser processes the workpiece 200. [Explanation of symbols]

[0086] 1,1-1 Processing equipment 4 Moving plate (slider) 5 Second moving plate (slider) 6 Third moving plate (slider) 41 X-axis movement unit (ball screw unit) 42 Y-axis movement unit (ball screw unit) 43 Z-axis movement unit (ball screw unit) 45 motor 46 Ball screw 47 Nut 100 Controllers 102 Torque value change data acquisition unit 103 Scoring part 104 Judgment Department 105 Alarm transmission unit 130 Alarm transmission unit 200 Workpiece 301 Data Acquisition Step 302 Scoring Steps 401 Decision Step 402 Warning Steps 500 change data 504 Overshoot X Judgment value (scored change data)

Claims

1. A method for predicting an abnormality in a processing device including a ball screw unit having a motor, a ball screw rotated by the motor, a nut screwed onto the ball screw, and a slider to which the nut is fixed, and an alarm issuing unit, a data acquisition step of acquiring data on changes in torque value of the motor while moving the slider by operating the motor; a scoring step of scoring the acquired change data; a determining step of determining whether or not the state is in a pre-abnormal stage based on the scored change data; and a warning issuing step of issuing a warning when the determining step determines that the state is in a pre-abnormal stage.

2. In the scoring step, the change data during the constant velocity movement of the slider is frequency analyzed and decomposed into wavelength data of a plurality of frequency bands; The abnormality prediction method according to claim 1 , wherein an amplitude spectrum in a specific frequency band among the wavelength data of the decomposed multiple frequency bands is converted into a score.

3. 3. The abnormality prediction method according to claim 2, wherein in the scoring step, the number and magnitude of overshoots of the torque value after the movement of the slider has stopped are scored, and the scored amplitude spectrum, the scored number of overshoots, and the scored magnitude of overshoots are weighted and added together.

4. A processing apparatus comprising: a ball screw unit having a motor, a ball screw rotated by the motor, a nut screwed onto the ball screw, and a slider to which the nut is fixed; an alarm issuing unit; and a controller that controls the ball screw unit, the controller includes a torque value change data acquisition unit that acquires data on change in torque value of the motor while operating the motor to move the slider; a scoring unit that scores the change data acquired by the torque value change data acquisition unit; a determination unit that determines whether or not the change data is in a pre-abnormal stage based on the scored change data; and an alarm issuing section that issues an alarm from the alarm issuing unit when the determining section determines that the condition is in a pre-abnormal stage.

5. the scoring unit performs frequency analysis on the change data during the constant velocity movement of the slider and decomposes it into wavelength data of a plurality of frequency bands; The processing device according to claim 4 , wherein an amplitude spectrum in a specific frequency band among the wavelength data of the decomposed frequency bands is converted into a score.

6. 6. The processing device according to claim 5, wherein the scoring unit scores the number and magnitude of overshoots of the torque value after the movement of the slider has stopped, and weights and sums up the scored amplitude spectrum, the scored number of overshoots, and the scored magnitude of overshoots.

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