Semiconductor manufacturing device, information processing device, and high-frequency vibration data analysis method

Abstract

To provide a technique that can reduce the time required for analyzing high-frequency vibration data.SOLUTION: In a semiconductor manufacturing device including a low-order controller for collecting high-frequency vibration data and a high-order controller for analyzing the high-frequency vibration data, the low-order controller includes collection means for collecting the high-frequency vibration data from a sensor, fast Fourier transform means for performing fast Fourier transform processing on the high-frequency vibration data according to a resolution setting, fast Fourier transform data transmission means for transmitting, to the high-order controller, the fast Fourier transform data which has been subjected to the fast Fourier transform processing, and high-frequency vibration data transmission means for transmitting, to the high-order controller, high-frequency vibration data in a period of time in which the fast Fourier transform data exceeds a threshold value for abnormality prediction. The high-order controller has analysis means for analyzing the received fast Fourier transform data and the high-frequency vibration data in the period of time.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present disclosure relates to a semiconductor manufacturing apparatus, an information processing apparatus, and a high-frequency vibration data analysis method. [Background technology]

[0002] For example, an anomaly detection system that uses AE (Acoustic Emission) has been conventionally known. As a method for analyzing an AE signal detected by a sensor, there is a method of sampling the output signal of the sensor at high speed and handling a large amount of data due to the high speed sampling (for example, see Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 5363213 Summary of the Invention [Problem to be solved by the invention]

[0004] The present disclosure provides techniques that can reduce the time required to analyze high frequency vibration data. [Means for solving the problem]

[0005] One aspect of the present disclosure is a semiconductor manufacturing apparatus having a lower-level controller that collects high-frequency vibration data and a higher-level controller that analyzes the high-frequency vibration data, wherein the lower-level controller has a collection means for collecting the high-frequency vibration data from a sensor, a fast Fourier transform means for performing fast Fourier transform processing on the high-frequency vibration data in accordance with a resolution setting, a fast Fourier transform data transmission means for transmitting the fast Fourier transform processed fast Fourier transform data to the higher-level controller, and a high-frequency vibration data transmission means for transmitting the high-frequency vibration data for a time period in which the fast Fourier transform data exceeds an abnormality prediction threshold to the higher-level controller, and the higher-level controller has an analysis means for analyzing the received fast Fourier transform data and the high-frequency vibration data for that time period. Effect of the Invention

[0006] According to the present disclosure, the time required to analyze high frequency vibration data can be reduced. [Brief description of the drawings]

[0007] [Figure 1] 1 is a configuration diagram illustrating an example of a semiconductor manufacturing apparatus according to an embodiment of the present invention. [Diagram 2] FIG. 2 is a diagram illustrating a hardware configuration of an example of a computer. [Diagram 3] FIG. 2 is a diagram illustrating an example of a functional configuration of a lower-level controller. [Figure 4] FIG. 2 is a diagram illustrating an example of a functional configuration of a higher-level controller. [Diagram 5] 10 is a flowchart of an example of processing of a lower level controller according to the embodiment; [Figure 6] FIG. 13 is a diagram illustrating an example of setting a threshold value for predicting an abnormality. [Figure 7] FIG. 13 is a diagram illustrating an example of setting a threshold value for predicting an abnormality. [Figure 8] FIG. 13 is a diagram illustrating an example of setting a threshold value for predicting an abnormality. [Figure 9] FIG. 13 is a diagram illustrating an example of setting a threshold value for predicting an abnormality. [Figure 10] FIG. 13 is a diagram illustrating an example of setting a threshold value for predicting an abnormality. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] Hereinafter, non-limiting exemplary embodiments of the present disclosure will be described with reference to the accompanying drawings. In the accompanying drawings, the same or corresponding members or parts are denoted by the same or corresponding reference numerals, and duplicated descriptions will be omitted as appropriate.

[0009] [First embodiment] Fig. 1 is a schematic diagram of an example of a semiconductor manufacturing apparatus according to the present embodiment. The semiconductor manufacturing apparatus 10 in Fig. 1 includes a semiconductor manufacturing section 12, one or more sensors 14 installed in the semiconductor manufacturing section 12, a lower controller 16, and a higher-level controller 18. The lower controller 16 may be provided outside the housing of the semiconductor manufacturing apparatus 10. The higher-level controller 18 may be provided outside the housing of the semiconductor manufacturing apparatus 10. For example, the lower controller 16 and the higher-level controller 18 may be realized by using a computer connected to be able to communicate data via a network, or a cloud service available via a network.

[0010] The semiconductor manufacturing unit 12 includes, for example, a heat treatment furnace, and performs various heat treatments such as oxidation, diffusion, and low-pressure CVD on a wafer W, which is an example of a substrate to be processed. The sensor 14 detects high-frequency vibration data from the semiconductor manufacturing unit 12. The sensor 14 is, for example, an AE (Acoustic Emission) sensor, which is a type of vibration sensor.

[0011] The lower controller 16 is, for example, a controller for controlling the semiconductor manufacturing equipment 10. The lower controller 16 may be a device used to accumulate high-frequency vibration data detected by the sensor 14. The lower controller 16 may be, for example, a data collection device such as a data logger. The lower controller 16 collects high-frequency vibration data from the sensor 14, and performs fast Fourier transform (hereinafter referred to as FFT) processing on the high-frequency vibration data in accordance with a resolution setting described below. The lower controller 16 transmits the FFT-processed FFT data to the upper controller 18.

[0012] Furthermore, the lower controller 16 transmits high-frequency vibration data for a time period in which the FFT-processed FFT data exceeds a threshold value (trigger level) for abnormality prediction, which will be described later, to the upper controller 18. The lower controller 16 may transmit high-frequency vibration data for a time period instructed by the upper controller 18 to the upper controller 18. The lower controller 16 may manually receive a setting of a threshold value for abnormality prediction, which will be described later, from an operator or the like.

[0013] The upper controller 18 is a device that receives the FFT data and high-frequency vibration data from the lower controller 16 as described above and performs analysis. The upper controller 18 may be, for example, an autonomous controller. The autonomous controller is a controller for autonomously controlling the semiconductor manufacturing equipment 10, and performs, for example, optimization of equipment control and prediction and detection of equipment abnormalities. The upper controller 18 may set a resolution setting, which will be described later, in the lower controller 16.

[0014] Furthermore, the upper controller 18 may set a threshold value for abnormality prediction, which will be described later, in the lower controller 16. The upper controller 18 may detect and predict an abnormality in the semiconductor manufacturing equipment 10 by analyzing the FFT data and high-frequency vibration data received from the lower controller 16. The lower controller 16 and the upper controller 18 control the operation of the semiconductor manufacturing equipment 10 so that the semiconductor manufacturing process is performed under various processing conditions indicated in the recipe.

[0015] The lower controller 16 and the upper controller 18 are realized by, for example, a computer having a hardware configuration shown in Fig. 2. Fig. 2 is a diagram showing the hardware configuration of an example of a computer.

[0016] 2 includes an input device 501, an output device 502, an external I / F (interface) 503, a RAM (Random Access Memory) 504, a ROM (Read Only Memory) 505, a CPU (Central Processing Unit) 506, a communication I / F 507, and a HDD (Hard Disk Drive) 508, all of which are connected to each other via a bus B. The input device 501 and the output device 502 may be connected and used when necessary.

[0017] The input device 501 is a keyboard, mouse, touch panel, etc., and is used by an operator to input various operation signals. The output device 502 is a display, etc., and displays the results of processing by the computer 500. The communication I / F 507 is an interface that connects the computer 500 to a network. The HDD 508 is an example of a non-volatile storage device that stores programs and data.

[0018] The external I / F 503 is an interface with an external device. The computer 500 can read and / or write data from and to a recording medium 503a such as a Secure Digital (SD) memory card via the external I / F 503. The ROM 505 is an example of a non-volatile semiconductor memory (storage device) in which programs and data are stored. The RAM 504 is an example of a volatile semiconductor memory (storage device) that temporarily holds programs and data.

[0019] The CPU 506 is a calculation device that reads out programs and data from storage devices such as the ROM 505 and HDD 508 onto the RAM 504 and executes processes, thereby realizing overall control and functions of the computer 500 .

[0020] The lower controller 16 or the upper controller 18 can realize various functions described below by executing processes according to programs using a computer 500 having a hardware configuration as shown in FIG.

[0021] <Functional configuration> An example of the functional configuration of the lower controller 16 and the upper controller 18 will be described with reference to the drawings. Fig. 3 is a diagram showing an example of the functional configuration of the lower controller. Fig. 4 is a diagram showing an example of the functional configuration of the upper controller.

[0022] The lower level controller 16 shown in FIG. 3 has a collection unit 30, a high-frequency vibration data storage unit 32, a high-frequency vibration data transmission unit 34, a resolution setting reception unit 36, an FFT unit 38, an FFT data transmission unit 40, and a threshold reception unit 42.

[0023] The sensor 14 is installed at a position in the semiconductor manufacturing unit 12 where it can detect high-frequency vibration data to be detected (hereinafter, referred to as Raw data). The collection unit 30 collects the Raw data detected by the sensor 14.

[0024] The high-frequency vibration data storage unit 32 stores the raw data collected by the collection unit 30. The high-frequency vibration data storage unit 32 has a sufficient capacity to store the raw data collected by the collection unit 30, and can store, for example, about 500 hours of raw data.

[0025] The resolution setting receiving unit 36 ​​receives a resolution setting from the upper controller 18. The resolution setting sets the number of waveform points in FFT processing. The resolution setting receiving unit 36 ​​may also receive a resolution setting from an operator who operates a monitor of the lower controller 16. The FFT unit 38 performs FFT processing on the raw data in accordance with the resolution setting received by the resolution setting receiving unit 36, and outputs FFT data.

[0026] The FFT data transmitting unit 40 transmits the FFT data output by the FFT unit 38 to the upper controller 18. In addition, the FFT data transmitting unit 40 receives a setting of a threshold value for predicting an abnormality of the FFT data from the threshold value receiving unit 42. In addition, the threshold value receiving unit 42 may receive a setting of a threshold value for predicting an abnormality from an operator who operates the monitor of the lower controller 16.

[0027] The FFT data transmitting unit 40 detects the moment when the FFT data exceeds the abnormality prediction threshold as a trigger point, and notifies the high-frequency vibration data transmitting unit 34 of the time period when the FFT data exceeds the abnormality prediction threshold.

[0028] When the high-frequency vibration data transmission unit 34 is notified by the FFT data transmission unit 40 of the time period in which the FFT data exceeds the abnormality prediction threshold, the high-frequency vibration data transmission unit 34 reads out the raw data of the time period in which the FFT data exceeds the abnormality prediction threshold from the high-frequency vibration data storage unit 32, and transmits it to the upper controller 18. In addition, the high-frequency vibration data transmission unit 34 may transmit the raw data of any time period instructed by the upper controller 18 to the upper controller 18.

[0029] The upper controller 18 in Figure 4 has a high-frequency vibration data receiving unit 50, a high-frequency vibration data memory unit 52, an analysis unit 54, an FFT data receiving unit 56, an FFT data memory unit 58, a resolution setting instruction unit 60, a threshold instruction unit 62, and a high-frequency vibration data transmission instruction unit 64.

[0030] The high frequency vibration data receiving unit 50 receives raw data from the high frequency vibration data transmitting unit 34 of the lower controller 16. The raw data received by the high frequency vibration data receiving unit 50 is raw data from a time period in which the FFT data exceeded the abnormality prediction threshold or raw data from an arbitrary time period instructed by the upper controller 18, so the amount of data is significantly smaller than the raw data collected by the collecting unit 30, and communication overhead can be significantly reduced.

[0031] The high-frequency vibration data storage unit 52 stores the raw data received by the high-frequency vibration data receiving unit 50. The raw data received by the high-frequency vibration data receiving unit 50 is raw data from a time period in which the FFT data exceeds the abnormality prediction threshold or raw data from an arbitrary time period instructed by the upper controller 18, and the amount of data is significantly smaller than that of the raw data collected by the collecting unit 30, so that the storage capacity of the high-frequency vibration data storage unit 52 can be saved.

[0032] The FFT data receiving unit 56 receives FFT data from the FFT data transmitting unit 40 of the lower level controller 16. The FFT data storage unit 58 stores the FFT data received by the FFT data receiving unit 56. The analysis unit 54 may analyze the raw data stored in the high frequency vibration data storage unit 52 and the FFT data stored in the FFT data storage unit 58, and optimize the device control of the semiconductor manufacturing equipment 10 and predict and detect an abnormality in the equipment.

[0033] For example, the analysis unit 54 determines the resolution setting according to a known analysis algorithm. The resolution setting instruction unit 60 instructs the lower controller 16 of the determined resolution setting. The analysis unit 54 also determines a threshold value for abnormality prediction according to a known analysis algorithm. The threshold value instruction unit 62 instructs the lower controller 16 of the determined threshold value for abnormality prediction. The high-frequency vibration data transmission instruction unit 64 instructs the lower controller 16 of an arbitrary time period of the Raw data to be received from the lower controller 16.

[0034] <Processing> An example of a method for analyzing high-frequency vibration data of the semiconductor manufacturing equipment 10 according to this embodiment will be described below. The lower-level controller 16 of the semiconductor manufacturing equipment 10 performs processing according to the procedure shown in Fig. 5, for example. Fig. 5 is a flowchart of an example of processing of the lower-level controller according to this embodiment.

[0035] In step S10, the collection unit 30 of the lower level controller 16 collects the raw data detected by the sensor 14. In step S22, the FFT unit 38 performs FFT processing on the raw data in accordance with the resolution setting accepted by the resolution setting acceptance unit 36, and outputs the FFT data.

[0036] The resolution setting sets the number of waveform points in FFT processing, and is set to, for example, 1024 resolution, 2048 resolution, or 4096 resolution. For example, when 4096 resolution is set, the number of waveform points is approximately 1 / 2. For example, when 2048 resolution is set, the number of waveform points is approximately 1 / 4. For example, when 1024 resolution is set, the number of waveform points is approximately 1 / 8.

[0037] In step S24, the FFT data transmitting unit 40 transmits the FFT data output by the FFT unit 38 to the upper controller 18. In this manner, the semiconductor manufacturing equipment 10 according to this embodiment always transmits FFT data according to the resolution setting required by the upper controller 18 from the lower controller 16 to the upper controller 18.

[0038] For example, the raw data detected by the sensor 14 is high-frequency data, and there was a problem that if all the raw data detected by the sensor 14 were transmitted to the upper controller 18, a lot of raw data from normal times would be transmitted. Furthermore, since abnormalities in high-frequency vibrations often change during a long period of operation, there were cases where the raw data detected by the sensor 14 was transmitted to the upper controller 18 for about 10 minutes per day. When the raw data detected by the sensor 14 was transmitted to the upper controller 18 for about 10 minutes per day, the raw data was for a fixed time period, making it difficult to perform analysis in time synchronization with any operation of the semiconductor manufacturing equipment 10.

[0039] In the semiconductor manufacturing equipment 10 according to this embodiment, the upper controller 18 always receives FFT data according to the resolution setting required by the upper controller 18, so that analysis can be performed in conjunction with explanatory variables of any operation of the time-synchronized semiconductor manufacturing equipment 10.

[0040] In step S26, the FFT data transmitting unit 40 determines whether or not a trigger point has been detected, which is the moment when the abnormality prediction threshold value set and accepted by the threshold accepting unit 42 has been exceeded. If a trigger point has not been detected, the semiconductor manufacturing apparatus 10 according to this embodiment returns to step S10 and continues processing.

[0041] If a trigger point is detected, the FFT data transmission unit 40 proceeds to the process of step S30. In step S30, the FFT data transmission unit 40 notifies the high-frequency vibration data transmission unit 34 of the detection of the trigger point. The FFT data transmission unit 40 may notify the high-frequency vibration data transmission unit 34 of the time period during which the FFT data exceeds the abnormality prediction threshold.

[0042] When the high frequency vibration data transmission unit 34 is notified of the detection of the trigger point by the FFT data transmission unit 40, it reads out the raw data of the time period in which the FFT data exceeds the abnormality prediction threshold from the high frequency vibration data storage unit 32, and transmits it to the upper controller 18. The time period in which the FFT data exceeds the abnormality prediction threshold may be, for example, about 5 to 60 minutes before and after the trigger point. The abnormality prediction threshold may be set using an automatic trigger detection function by data analysis on the upper controller 18 side.

[0043] The high-frequency vibration data transmission unit 34 selects raw data from the time period when the FFT data exceeds the abnormality prediction threshold and transmits it to the upper controller 18, thereby significantly reducing the communication overhead between the lower controller 16 and the upper controller 18 compared to transmitting all raw data.

[0044] Furthermore, by selecting raw data from a time period in which the FFT data exceeds the abnormality prediction threshold and transmitting the raw data to the upper controller 18, the upper controller 18 can perform a more detailed analysis than with the FFT data. After step S30, the semiconductor manufacturing apparatus 10 according to this embodiment returns to step S10 and continues the process.

[0045] The setting of the threshold for anomaly prediction will be described below. Fig. 6 is a diagram for explaining an example of setting the threshold for anomaly prediction. Fig. 6(A) and Fig. 6(B) show an example of the change in waveform intensity over time. The waveform intensity in Fig. 6 is the sum of the intensities for each frequency.

[0046] By setting the anomaly prediction threshold value 1000 in Fig. 6(A), it is possible to detect as a trigger point the moment when the waveform intensity exceeds the threshold value 1000. Also, by setting the anomaly prediction threshold value 1010 in Fig. 6(B), it is possible to detect as a trigger point the moment when the vibration intensity increases and the waveform intensity exceeds the threshold value 1010.

[0047] FIG. 7 is a diagram for explaining an example of setting the anomaly prediction threshold. In FIG. 7(A), an anomaly prediction threshold 1100 is set for the average waveform intensity, so that the moment when the average waveform intensity exceeds the threshold 1100 can be detected as a trigger point. In FIG. 7(B), an anomaly prediction threshold is set for the maximum waveform intensity, so that the moment when the maximum waveform intensity exceeds the threshold can be detected as a trigger point. In addition, in FIG. 7(C), an anomaly prediction threshold is set for the minimum waveform intensity, so that the moment when the minimum waveform intensity exceeds the threshold can be detected as a trigger point.

[0048] Fig. 8 is a diagram for explaining an example of setting a threshold value for anomaly prediction. Fig. 8 shows an example of a change over time in waveform intensity for each frequency. For example, "d1" in Fig. 8 shows an example of waveform intensity for each frequency in the initial state of the semiconductor manufacturing equipment 10.

[0049] "d2" and "d3" in Fig. 8 show an example of waveform intensity for each frequency in the time-varying state of semiconductor manufacturing equipment 10 after a predetermined period has passed since the initial state. The period of time that has passed since the initial state of "d3" in Fig. 8 is longer than "d2" in Fig. 8. In Fig. 8(B), by setting an anomaly prediction threshold value 1200 for the waveform intensity for each frequency after the time-varying state of semiconductor manufacturing equipment 10 from the initial state, the moment when the waveform intensity for each frequency exceeds the threshold value 1200 can be detected as a trigger point.

[0050] Fig. 9 is a diagram for explaining an example of setting a threshold value for anomaly prediction. Fig. 9 shows an example of a change over time in waveform intensity for each frequency. For example, "d1" in Fig. 9 shows an example of waveform intensity for each frequency in the initial state of the semiconductor manufacturing equipment 10.

[0051] "d2" and "d3" in Fig. 9 show an example of waveform intensity for each frequency of the time-dependent change state of the semiconductor manufacturing equipment 10 after a predetermined period has passed from the initial state. The period of time that has passed from the initial state in "d3" in Fig. 9 is longer than that in "d2" in Fig. 9.

[0052] In FIG. 9, by setting an abnormality prediction threshold 1300 for each arbitrary frequency region, the moment when the waveform intensity for each frequency exceeds the threshold 1300 set for each arbitrary frequency can be detected as a trigger point.

[0053] Fig. 10 is a diagram for explaining an example of setting a threshold value for anomaly prediction. Fig. 10 shows an example in which a range of 0 to 8 kHz in a 0 to 10 kHz frequency band is specified, and a waveform of 2048 points, which is about 1 / 4 of 8000 Hz, is output by averaging the frequency bands before and after the waveform.

[0054] In FIG. 10 , by setting at least one of a characteristic abnormality prediction threshold 1400 of 1.5 kHz or less and an abnormality prediction threshold 1402 of 5 to 8 kHz, the moment when the waveform intensity for each frequency of 1.5 kHz or less exceeds the abnormality prediction threshold 1400 or the moment when the waveform intensity for each frequency of 5 to 8 kHz exceeds the abnormality prediction threshold 1402 can be detected as a trigger point.

[0055] If you specify a range of 0 to 8192 Hz and output with a resolution of 1024 and intervals of 8 Hz, the amount of data will be 1 / 8. If you specify a range of 0 to 8192 Hz and output with a resolution of 2048 and intervals of 4 Hz, the amount of data will be 1 / 4. If you specify a range of 0 to 8192 Hz and output with a resolution of 4096 and intervals of 2 Hz, the amount of data will be 1 / 2.

[0056] According to this embodiment, raw data from the time period when the FFT data exceeds the abnormality prediction threshold is transmitted to the upper controller 18, so that the processing load required for analyzing the raw data can be reduced, and the time required for analyzing the raw data can be shortened.

[0057] Furthermore, according to this embodiment, the resolution setting required by the upper controller 18 can be specified from the upper controller 18 side, so that an analysis algorithm can be used to run a PDCA (Plan, Do, Check, and Act) cycle of data collection, accumulation, and analysis, thereby automating the improvement of analysis accuracy.

[0058] The embodiments of the present disclosure should be considered as illustrative and not restrictive in all respects. In addition, the above-mentioned embodiments may be omitted, substituted, or modified in various forms without departing from the scope and spirit of the appended claims. In addition, the semiconductor manufacturing apparatus 10 of the present embodiment includes processing apparatuses such as a heat processing apparatus, a plasma processing apparatus, and a substrate processing apparatus. [Explanation of symbols]

[0059] 10. Semiconductor manufacturing equipment 14 Sensors 16 Lower Controller 18 Upper controller 30 Collection Department 34 High frequency vibration data transmitter 38 FFT section 40 FFT data transmission section

Claims

1. A semiconductor manufacturing apparatus having a lower controller that collects high-frequency vibration data and a higher controller that analyzes the high-frequency vibration data, The lower level controller is a collection means for collecting the high frequency vibration data from a sensor; A fast Fourier transform means for fast Fourier transforming the high-frequency vibration data in accordance with a resolution setting; a fast Fourier transform data transmission means for transmitting the fast Fourier transform data obtained by the fast Fourier transform processing to the upper controller; a high-frequency vibration data transmitting means for transmitting the high-frequency vibration data during a time period in which the fast Fourier transform data exceeds a threshold for predicting an abnormality to the upper controller; having The upper controller is an analysis means for analyzing the received fast Fourier transform data and the high frequency vibration data for the time period; A semiconductor manufacturing apparatus having

2. The resolution setting is set according to an instruction from the upper controller or an instruction from an operator who operates the lower controller.

2. The semiconductor manufacturing apparatus according to claim 1,

3. The resolution setting may be set to have 1024, 2048, or 4096 waveform points.

2. The semiconductor manufacturing apparatus according to claim 1,

4. the abnormality prediction threshold is set according to an instruction from the upper controller; The high-frequency vibration data transmission means transmits the high-frequency vibration data for a set time period before and after the fast Fourier transform data exceeds a threshold for predicting an abnormality to the upper controller.

4. The semiconductor manufacturing apparatus according to claim 1, wherein:

5. The high-frequency vibration data transmission means transmits the high-frequency vibration data for a time period instructed by the upper controller to the upper controller.

5. The semiconductor manufacturing apparatus according to claim 4,

6. The high-frequency vibration data is collected from an Acoustic Emission (AE) sensor.

4. The semiconductor manufacturing apparatus according to claim 1, wherein:

7. An information processing device that transmits high-frequency vibration data to a host controller that analyzes the high-frequency vibration data, a collection means for collecting the high frequency vibration data from a sensor of the semiconductor manufacturing equipment; A fast Fourier transform means for fast Fourier transforming the high-frequency vibration data in accordance with a resolution setting; a fast Fourier transform data transmission means for transmitting the fast Fourier transform data obtained by the fast Fourier transform processing to the upper controller; a high-frequency vibration data transmission means for transmitting the high-frequency vibration data during a time period in which the fast Fourier transform data exceeds a threshold for predicting an abnormality to the upper controller; An information processing device having the above configuration.

8. A method for analyzing high-frequency vibration data of a semiconductor manufacturing apparatus having a lower controller that collects high-frequency vibration data and a higher controller that analyzes the high-frequency vibration data, comprising: The lower level controller is collecting said high frequency vibration data from a sensor; subjecting the high frequency vibration data to a fast Fourier transform in accordance with a resolution setting; transmitting the fast Fourier transform processed fast Fourier transform data to the upper controller; transmitting the high-frequency vibration data during a time period in which the fast Fourier transform data exceeds a threshold for predicting an abnormality to the upper controller; having The upper controller is analyzing the received fast Fourier transform data and the high frequency vibration data for the time period; A high frequency vibration data analysis method comprising:

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