Tool wear monitoring device, tool wear monitoring system, and program

Abstract

To properly measure wear on a side surface of a tool by imaging the blade tip state of a tool after cutting processing by changing angles and analyzing the acquired image data in image processing.SOLUTION: A tool wear monitoring device 2 for monitoring wear of a cutting tool 3 by receiving input of a plurality of pieces of image data captured by changing angles with a microscope camera 8 comprises a data analysis unit 12 which analyzes the image data. The data analysis unit 12 binarizes the plurality of pieces of image data captured by changing angles, extracts data in which a wear region has the maximum area from the plurality of pieces of image data, and analyzes a wear amount from the extracted data with the maximum area.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a monitoring technique for monitoring the wear of a tool. [Background technology]

[0002] A device for monitoring a cutting tool using a camera is described in JP 9-57583 A (Patent Document 1). This publication states that "the entire or almost entire tool after cutting is imaged with an infrared camera, the position of the tool's cutting edge is recognized from the temperature distribution on the tool surface that can be identified from the image data captured by the infrared camera, a television camera with a high imaging magnification is moved to a position directly facing the tool cutting edge based on the information on the cutting edge position, the tool cutting edge is imaged by the television camera, and the amount of wear of the tool is measured from the image data of the tool cutting edge captured by the television camera" (see abstract). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 9-57583 Summary of the Invention [Problem to be solved by the invention]

[0004] An important task for an operator who operates a machine tool is to discover abnormalities in machining and replace cutting tools. Abnormalities in machining are basically judged from vibration sounds during machining and load meter values, which are the control current levels of the motor. In addition, when abnormalities occur, damage to the tool increases, leading to wear and breakage of the tool cutting edge. Worn or broken tools must be replaced with new ones. In the case of breakage, it can be clearly confirmed by visual inspection and easily noticed. On the other hand, wear can be difficult to judge visually in some cases, and it is basically observed under a microscope, and if it exceeds a certain wear width, it will be replaced. As tool wear progresses, the cutting performance decreases, the load during machining increases, leading to deterioration of the machined surface, deterioration of the dimensional accuracy of the machined object, and chipping and breakage of the tool. Especially in the case of machining large parts that are expensive and cannot tolerate failure, it is expected that the tool will break during machining and cause scratches on the parts that cannot be recovered. For this reason, it is necessary to properly organize the changes in wear and monitor the wear state.

[0005] Patent Document 1 discloses an automatic tool wear measurement device that uses an infrared camera to capture an image of the entire tool after cutting, recognizes the position of the tool's cutting edge from the temperature distribution on the tool surface, moves a high-magnification television camera to a position directly opposite the tool cutting edge based on the information on the recognized cutting edge position, captures an image of the tool cutting edge with the television camera, and measures the amount of tool wear from the image data of the tool cutting edge captured by the television camera. However, the device described in Patent Document 1 measures the amount of tool wear from a position directly opposite the tool cutting edge, and does not take into consideration appropriate measurement of wear on the side of the tool.

[0006] Therefore, the present invention aims to appropriately measure wear on the side of a tool by photographing the condition of the cutting edge of a tool after cutting from different angles and analyzing the acquired image data through image processing. [Means for solving the problem]

[0007] In order to solve the above problems, for example, the configurations described in the claims are adopted.

[0008] The present application includes a number of means for solving the above problems. To give an example of such means, With microscope camera In the direction of rotation of the cutting tool The photo was taken at a different angle , cutting tools A tool wear monitoring device that inputs a plurality of image data and monitors wear of a cutting tool, comprising: A data analysis unit that analyzes image data is provided, and the data analysis unit analyzes the Cutting Tools Binarize multiple image data, Multiple binary image data From inside , on one blade The data with the maximum wear area was extracted, and the maximum area was then used to Cutting Tools This method is characterized by analyzing the amount of wear. Effect of the Invention

[0009] According to the present invention, the state of the cutting edge of the tool after cutting is photographed from different angles and the acquired image data is analyzed by image processing, so that wear on the side surface of the tool and the like can be appropriately measured.

[0010] Problems, configurations and effects other than those described above will become apparent from the following description of the embodiments. [Brief description of the drawings]

[0011] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a tool wear monitoring system according to a first embodiment. [Diagram 2] FIG. 13 is a diagram illustrating an example of the configuration of a computer that realizes the tool wear monitoring device. [Diagram 3] FIG. 2 is a diagram illustrating an example of a cutting tool. [Figure 4] FIG. 1 is a diagram showing an example of wear of a cutting tool. [Diagram 5] FIG. 2 is a diagram showing an example of a data analysis unit and related parts of the tool wear monitoring device of the first embodiment. [Figure 6] FIG. 4 is a diagram showing an operation flow of the tool wear monitoring system. [Figure 7] FIG. 2 is a diagram showing a configuration for capturing an image using a microscope camera. [Figure 8] FIG. 13 is a diagram showing an image of tool wear when photographed. [Figure 9] FIG. 11 is a diagram illustrating image processing of acquired image data. [Figure 10] FIG. 11 is a diagram showing a flow of outputting the amount of wear from image capture in the first embodiment. [Figure 11] FIG. 11 is a diagram showing an example of the configuration of a tool wear monitoring system using a plurality of microscope cameras according to a second embodiment. [Figure 12] FIG. 13 is a diagram showing an example of a GUI of the tool wear monitoring system of the third embodiment. [Figure 13] FIG. 13 is a diagram showing an example of a network of a tool wear monitoring system according to a fourth embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0012] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. However, the present invention should not be interpreted as being limited to the description of the embodiment shown below. It will be easily understood by those skilled in the art that the specific configuration can be changed without departing from the concept or gist of the present invention. In addition, in the configurations of the invention described below, the same reference numerals are used in different drawings for the same parts or parts having similar functions, and duplicated explanations may be omitted. EXAMPLES

[0013] In this embodiment, an embodiment of a tool wear monitoring system will be described.

[0014] FIG. 1 is a diagram for explaining an example of a configuration diagram of a tool wear monitoring system. The tool wear monitoring system 100 is composed of a machine tool 1 and a tool wear monitoring device 2. The tool wear monitoring system 100 is used in a cutting process. In cutting, a workpiece is formed into a desired shape by high-speed rotation of a spindle 4 to which a cutting tool 3 such as an end mill is fixed. The machine tool 1 is composed of the cutting tool 3, the spindle 4, a spindle motor 5 for rotating the spindle 4, a servo amplifier 6 for inputting a control current and voltage for driving the spindle motor 5, and a numerical control device (NC device) 7 for moving according to command values.

[0015] In the tool wear monitoring system of the present invention, a microscope camera 8 is installed in a machine tool. This microscope camera 8 may be installed in the same machine where the workpiece is fixed, or in a tool magazine where unused tools are kept waiting. The camera may be connected by wire, or wirelessly using a method such as WiFi (registered trademark) or Bluetooth (registered trademark). A current / voltage sensor 18 for measuring the current and voltage values ​​of the spindle motor 5 is also installed.

[0016] The image data of the camera 8 and the current and voltage values ​​of the current and voltage sensor 18 are input to the receiving unit 9 of the monitoring device 2. When the receiving unit 9 receives the data, it is input to the signal processing unit 11 through the data recording unit 10. If the recorded data is in the raw data state, it may contain a lot of noise. For example, the current and voltage sensor 18 may receive electrical noise depending on the condition of the factory or the condition of the control panel of the processing machine. In addition, the contrast of the image data may vary depending on the brightness of the room due to the weather. For this reason, it is important to remove noise by signal processing and extract only the current and voltage values ​​used in processing, and this is also a necessary element for high-precision monitoring. Since some signal processing is required depending on the process, process data 14 to associate with the signal processing is input here.

[0017] The data from which noise has been removed is input to the data analysis unit 12. Here, the image data is subjected to image processing to analyze the amount of wear. The current and voltage signals are either used as is or converted into power and then converted into parameters equivalent to the load during processing. The learning data 15 stores data accumulated in the past. The learning data 15 may be used as teacher data for the analysis by the data analysis unit 12. The analysis results of the data analysis unit 12 are input to the transmission unit 13. From here, they are sent to the network 16.

[0018] Network 16 is for sharing among multiple parties involved and may be a cloud or an in-house server. For example, when image processing results are input via network 16 and a decision is made to stop machining, the results are sent to conversion unit 17, which converts them into signals to control an NC device and feeds them back to machine tool 1. At this time, control may be performed via NC device 7, or a signal may be sent directly to servo amplifier 6. Tool wear monitoring device 2 also includes a GUI (Graphical User Interface) 19 for displaying analysis results and the like and for inputting commands.

[0019] 2 is a diagram showing an example of the configuration of a computer that realizes the tool wear monitoring device 2. The tool wear monitoring device 2 is composed of a general computer 50 such as a personal computer that includes a processor 51 such as a CPU (Central Processing Unit), a memory 52 such as a DRAM (Dynamic Random Access Memory), a storage 57 such as a HDD (Hard Disk Drive) or SSD (Solid State Drive), an input device 55 such as a keyboard, a mouse, a touch panel, an output device 56 such as a display, a communication module 54 such as a NIC (Network Interface Card), and an interface 53 that connects these. The computer may be configured on a cloud.

[0020] Figure 3 shows an example of an end mill. When machining is performed with a cutting tool 3, which is an end mill, wear progresses at the cutting edge 20, which is the cutting edge portion. An enlarged view of this state is shown in Figure 4. At the cutting edge 20, wear 21 is observed, for example, on the flank face. At this time, it is difficult to estimate the exact amount of wear visually, so the exact amount of wear is generally measured using a microscope.

[0021] Figure 5 shows an example of the data analysis unit and related parts of the tool wear monitoring device 2. The signal processing unit 11 receives tool data 39 and process data 40 from, for example, the process data 14. This is because appropriate signal processing differs depending on the tool and process. For example, in the case of a process where a specific frequency band such as chatter vibration is a problem, signal processing linked to that process by the signal processing unit 11, such as FFT processing, is effective. In addition, in the case of a tool or process where the load is small and the change is correspondingly small, the influence of outliers and the influence of high frequencies are large, so signal processing such as a filter that eliminates outliers and a low-pass filter that eliminates high frequencies becomes important.

[0022] The data from which only the parts necessary for judgment are extracted by signal processing is input to the data analysis unit 12. In the data analysis unit 12, for example, the current and voltage values ​​are converted to power values ​​in the power calculation 30. Then, in the analysis 31, the change in the load during machining is read from the change in power. Next, the analysis result is output in the power judgment result 32. Since the change in power is almost correlated with the change in load, for example, if the power increases suddenly and then drops immediately afterwards, it is assumed that the tool has broken. This judgment result is fed back to the processing machine via the transmission unit 13 to replace the tool due to tool breakage, to send a processing stop signal to the processing machine, to notify the process designer to review the processing conditions, and to suggest to the product designer to review the tolerance conditions of this part. The change in the load during machining may be estimated from the change in current or voltage.

[0023] In the case of images taken by a microscope camera 8, the amount of tool wear is analyzed by image processing 33 and wear area calculation 34. The analysis results are judged by wear judgment result 35. Similarly, when tool wear exceeds a threshold, this can be used to request the process designer to modify the processing conditions, or to send information about the deterioration of the finish surface accuracy due to an increase in surface roughness to the assembly staff, and provide advice to the assembly worker. Furthermore, when the threshold is frequently exceeded, it can be used to notify the product designer to review the tolerance setting. To carry out these operations, learning data 15 is required, and examples include the current and power data 36 and image data 37 accumulated up to now, and judgment result data 38 showing the judgment results at that time.

[0024] FIG. 6 illustrates an example of the operation flow of the tool wear monitoring system. First, the process starts in monitoring start S100. Next, in parts number determination S101, it is determined how many parts there are. At this time, if the number (for example, the Nth part) is equal to or greater than a threshold, monitoring ends S108. If the number is equal to or less than the threshold, in part Nth tool determination S102, it is determined which tool to use in order to determine the process. Next, the process to be processed with the selected tool is started in target process processing start S103. Next, processing with the tool is completed in target process processing end S104. The tool that has been used up is replaced by an ATC (Automatic Tool Changer) in tool magazine evacuation S105 and is evacuated to the tool magazine. The tool evacuated to the tool magazine is measured for tool wear in evacuated tool wear measurement S109. The measured data is transmitted to the receiving unit 9 in measurement data transmission S110. After the first tool is removed from the machine in Tool Magazine Evacuation S105, the next tool is brought in. The tool and process are identified in Next Tool Identification S106. Machining then begins after going through Nth Part Tool Identification S102. When all tools have been completed, the process leaves this loop and proceeds to Next Part Determination S107. If there is a next part, the process returns to Part Count Identification S101 and processing resumes. If there is no next part and processing is to end, the process proceeds to Monitoring End S108 and the system ends.

[0025] FIG. 7 illustrates an example of a configuration diagram when capturing images with a microscope camera. In this example, the cutting tool 3 is fixed to the spindle inside the machine, not in a tool magazine. When machining by the target cutting tool is completed, the cutting tool 3 moves to the location where the microscope camera 8 is fixed. The microscope camera 8 is fixed so as not to move by a jig 61. When the tool cutting edge approaches the microscope camera 8 and stops, it rotates once on the spot. During that one rotation, multiple images are captured. Note that the cutting tool 3 may be fixed and the microscope camera 8 may be rotated around the cutting tool 3 to capture multiple images.

[0026] The photographing method is shown in Figure 8. The appearance of the cutting edge differs depending on the angle of rotation, and the appearance of tool wear changes accordingly. For this reason, for example, if multiple images are taken of a rotating tool, images can be obtained in which the cutting edge is slightly shifted. By performing this for one rotation, wear images 62, 63, and 64 can be obtained for all blades, the number of images taken. The wear area of ​​all these captured images is calculated, and the image with the maximum wear area for one blade is selected. For a tool with four blades, four images are taken that show the maximum area for each blade.

[0027] In the unprocessed image data of FIG. 8, the background and other parts other than the worn parts are mixed in, making it difficult to determine only the worn parts. An example of image processing is explained in FIG. 9. In the worn parts, the coating of the tool at that part peels off, exposing the internal metal and often shining white. For this reason, if the white parts are processed and the rest are separated by binarization or the like, it becomes possible to select only the worn parts. After processing, as shown in wear extraction units 70, 71, and 72, only the worn areas at each rotation angle can be extracted. This makes it possible to select the image with the largest worn area.

[0028] FIG. 10 describes a series of flows from taking images of the cutting edge 20 of the cutting tool to outputting the wear amount. First, the flow starts with image taking start S200. Next, the required number of images is set in setting the number of images taken N S201. In the case of FIG. 7, multiple images of the cutting edge are taken during one rotation of the tool, but if the spindle is rotated one degree at a time, for example, N=360 is input. In the case of FIG. 11 described later in the second embodiment, for example, if four cameras are installed, N=4 is input since four images are taken. Next, in taking the i-th image S202, images are taken with the camera. In the next step N=i? S203, the current number of images taken is confirmed. If the number of images has reached N, binarization processing is performed, for example, on all the captured image files, in binarization of the N pieces of captured data S204. If the number of images has not yet reached N, the process proceeds to step S205 of i=i+1. Here, in the case of FIG. 7, the tool rotates by the specified angle. In the case of FIG. 11, the process proceeds to preparation for taking images with the adjacent camera. The process proceeds to step S202, where the next image is captured. When the binarization process for all image files is complete, the data file with the largest area is extracted from them in step S206. Then, wear amount analysis is performed from the extracted file in step S207, and finally, wear amount data is output in wear amount output S208.

[0029] According to this embodiment, the amount of wear on the side of the cutting tool can be appropriately calculated by taking multiple images of the cutting edge of the cutting tool from different angles using a microscope camera, binarizing the images, extracting the data file with the largest area from among them, and analyzing the amount of wear. Also, the current and voltage values ​​of the spindle motor are measured using a current and voltage sensor, power is calculated, and the load during machining can be estimated from the changes in current, voltage, or power, making it possible to detect breakage of the cutting tool. EXAMPLES

[0030] 11 shows a tool wear monitoring system according to embodiment 2. In embodiment 2, a plurality of microscope cameras are used to measure the wear of a cutting tool 3 retracted in a tool magazine 77.

[0031] The tools in the tool magazine cannot rotate by themselves. For this reason, if multiple microscope cameras 8, 73, 74, 75 are arranged circumferentially around the cutting tool 3, images showing tool wear measured from appropriate angles can be obtained. Since the tool magazine 77 has spatial limitations, it is believed that the measurement accuracy will improve if as many small microscope cameras as possible are used.

[0032] According to this embodiment, the amount of wear on the side surface, etc., of a cutting tool retracted into a tool magazine can be appropriately obtained. EXAMPLES

[0033] 12 shows the GUI of the tool wear monitoring system of Example 3. Example 3 shows the results of evaluation and analysis of tool wear on the screen of GUI 19.

[0034] As shown in the figure, tool numbers 81 for distinguishing tools, threshold values ​​82 set for necessary control, and tool cutting edge photos 84, 85, 86, and 87 showing images of acquired tool wear are displayed. Then, plots 88 of the amount of tool wear (area) for each number of cut pieces, and a graph 83 of a tool wear curve showing the relationship between the number of cut pieces and the amount of tool wear (area) are displayed. The plot on the far right exceeds the threshold value, so replacement of the cutting tool is required.

[0035] According to this embodiment, a plot of the tool wear amount (area) for each number of pieces machined is displayed on the GUI screen, so that it is possible to recognize the need to replace the cutting tool when the threshold value is exceeded. Also, by displaying a graph of the tool wear curve, it is possible to predict the time to replace the tool. EXAMPLES

[0036] 13 shows an example of a tool wear monitoring system according to the embodiment 4. In the embodiment 3, the tool wear monitoring system is networked.

[0037] In order to develop a solution using the tool wear monitoring system, it is important to know how to utilize it through a network. The data including the analysis results sent from the transmitter 13 is sent to the network 16. Various data is stored in the network 16. For example, there are wear amount data 90 photographed by the microscope camera 8, dimensional accuracy data 91 linked by the wear amount, process data 92, power data 94 measured by a current / voltage sensor, and assembly accuracy data 93. This network 16 can be the cloud or an in-house server. It is fine as long as it can be shared by multiple parties involved.

[0038] For example, here, a product designer 95, a tool maintenance person 96, a machine tool operator 97, a process designer 98, and an assembly person 99 are taken as examples. Each person has a terminal, to which instructions and advice are sent from the network. If the tool wear progresses quickly and it is difficult to obtain the desired surface roughness, the product designer 95 sends a notice to that effect from the network 16, and the product designer 95 sends a drawing correction instruction and a tolerance correction value to the network 16. When the tool reaches the threshold wear amount, the tool maintenance person 96 receives the timing of tool replacement from the network 16 and prepares a new tool. When the tool wear approaches the threshold or a sudden increase in power data occurs, the machine tool operator 97 receives the notice from the network 16 and responds by adjusting the override of the machine tool, etc. locally. In addition, the machine tool operator 97 issues a request to correct the machining conditions to the process designer 98. The assembly person 99 receives information on the deterioration of the finishing surface accuracy due to the deterioration of the machining surface accuracy caused by the tool wear and the increase in power, and sends and receives advice.

[0039] According to this embodiment, tool wear information measured by the tool wear monitoring device can be shared among a plurality of people involved through a network, enabling a rapid response to tool wear.

[0040] The present invention is not limited to the above-mentioned embodiment, but includes various modified examples. For example, the above-mentioned embodiment has been described in detail to easily explain the present invention, and is not necessarily limited to those including all of the configurations described. Also, it is possible to replace a part of the configuration of one embodiment with the configuration of another embodiment, and it is also possible to add the configuration of another embodiment to the configuration of one embodiment. Also, it is possible to add, delete, or replace a part of the configuration of each embodiment with another configuration. [Explanation of symbols]

[0041] 1…Machine tool 2. Monitoring equipment 3…Cutting tools 4…Spindle 5...Main shaft motor 6...Servo amplifier 7...NC unit (numerical control device) 8…Microscope camera 9…Receiver 10...Data recording section 11...Signal processing unit 12…Data analysis section 13...Transmitter 14…Process data 15…Learning data 16…Network 17...Conversion section 18...Current / Voltage sensor 19…GUI 20…Cutting edge 21...Wear 30…Power calculation 31…Analysis 32…Power judgment result 33...Image processing 34…Wear area calculation 35...Wear evaluation result 36…Current and power data 37...Image data 38…Judgment result data 39...Tool data 40...Process data 77…Magazine 83...Tool wear curve 100...Tool wear monitoring system

Claims

1. A tool wear monitoring device that inputs a plurality of image data of a cutting tool taken by a microscope camera at different angles in a rotational direction of the cutting tool, and monitors wear of the cutting tool, comprising: A data analysis unit that analyzes image data, The data analysis unit A plurality of image data of the cutting tool photographed at different angles is binarized; Extracting data of the maximum wear area for one blade from the plurality of binarized image data; Analyze the amount of wear on the cutting tool from the extracted maximum area data A tool wear monitoring device comprising:

2. The tool wear monitoring device according to claim 1, further comprising: a receiving unit that receives image data from the microscope camera and measurement data from a current / voltage sensor that measures a current / voltage of a motor that rotates the cutting tool; a data recording unit that records the image data and measurement data received by the receiving unit; a signal processing unit that processes the image data and the measurement data recorded in the data recording unit; a transmission unit for transmitting an analysis result by the data analysis unit to a network; A tool wear monitoring device comprising:

3. 3. The tool wear monitoring device according to claim 2, The data analysis unit further The load during machining is estimated from changes in current, voltage, or power based on measurement data from current and voltage sensors. Outputs the estimated load during machining A tool wear monitoring device comprising:

4. The tool wear monitoring device according to claim 1, further comprising: Equipped with a display that shows the monitoring status, The display unit displays a tool number, a threshold value of the wear amount of the cutting tool, and a tool wear curve showing the relationship between the number of pieces machined and the wear amount. A tool wear monitoring device comprising:

5. A tool wear monitoring system for monitoring wear of a cutting tool, comprising: a microscope camera that captures multiple images of the cutting tool cutting edge at different angles in the direction of the cutting tool rotation; A tool wear monitoring device that analyzes the measurement data; and a network for storing the output of the tool wear monitoring device, The data analysis unit of the tool wear monitoring device includes: Multiple image data of the cutting tool taken at different angles are binarized, Extracting data of the maximum wear area for one blade from the plurality of binarized image data; Analyze the amount of wear on the cutting tool from the extracted maximum area data A tool wear monitoring system comprising:

6. 6. The tool wear monitoring system according to claim 5, Equipped with a sensor that measures the current and voltage of the machine tool motor, The data analysis unit of the tool wear monitoring device further comprises: The load during machining is estimated from changes in current, voltage, or power based on measurement data from current and voltage sensors. Outputs the estimated load during machining A tool wear monitoring system comprising:

7. 6. The tool wear monitoring system according to claim 5, A tool wear monitoring system characterized in that the microscope camera is fixed and captures multiple images of the cutting tool tip at different angles as the cutting tool rotates.

8. 6. The tool wear monitoring system according to claim 5, A tool wear monitoring system characterized in that the cutting tool is fixed and multiple images of the cutting tool cutting edge are taken at different angles by multiple microscope cameras arranged around the cutting tool.

9. 6. The tool wear monitoring system according to claim 5, The tool wear monitoring device further comprises: a receiving unit that receives image data from the microscope camera and measurement data from a current / voltage sensor that measures a current / voltage of a motor that rotates the cutting tool; a data recording unit that records the image data and measurement data received by the receiving unit; a signal processing unit that processes the image data and the measurement data recorded in the data recording unit; a transmission unit for transmitting an analysis result by the data analysis unit to a network; Tool wear monitoring system including:

10. 6. The tool wear monitoring system according to claim 5, Equipped with a display that shows the monitoring status, The display unit displays a tool number, a threshold value of the wear amount of the cutting tool, and a tool wear curve showing the relationship between the number of pieces machined and the wear amount. A tool wear monitoring system comprising:

11. 6. The tool wear monitoring system according to claim 5, A tool wear monitoring system, wherein the network has at least one of wear amount data, dimensional accuracy data, process data, power data, and assembly accuracy data.

12. A program for making a computer function as a tool wear monitoring device that inputs a plurality of image data of a cutting tool taken by a microscope camera at different angles in a rotational direction of the cutting tool and monitors wear of the cutting tool, the program comprising: The program functions as a data analysis unit that analyzes image data by binarizing multiple image data of the cutting tool photographed at different angles, extracting data on the maximum area of ​​the wear area for one blade from the multiple binarized image data, and analyzing the amount of wear of the cutting tool from the extracted data on the maximum area.

13. The program according to claim 12, further comprising: a receiving unit that receives image data from the microscope camera and measurement data from a current / voltage sensor that measures a current / voltage of a motor that rotates the cutting tool; a data recording unit that records the image data and measurement data received by the receiving unit; a signal processing unit that processes the image data and the measurement data recorded in the data recording unit; a transmission unit for transmitting an analysis result by the data analysis unit to a network; A program characterized by causing a computer to function as described above.

14. The program according to claim 12, The data analysis unit further comprises: A program characterized by estimating the load during machining from changes in current, voltage, or power based on measurement data from a current / voltage sensor that measures the current and voltage of a motor that rotates a cutting tool, and outputting the estimated result of the load during machining.

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