Method for predicting life span of rotary machine used in manufacturing apparatus and life predicting system

• US 20030153997A1
• Filed: 08/28/2002
• Published: 08/14/2003
• Est. Priority Date: 08/31/2001
• Status: Active Grant

• Current Assignee: Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Original Assignee: Kabushiki Kaisha Toshiba (Toshiba Corporation)
• Inventors: Ishii, Ken, Nakao, Takashi, Samata, Shuichi, Furuhata, Takeo, Ushiku, Yukihiro
• Granted Patent: US 6,885,972 B2
• Time in Patent Office: Days
• US Class Current: 700/108
• CPC Class Codes: G05B 19/4065 Monitoring tool breakage, life or condition
• CPC Class Codes: G05B 2219/37252 Life of tool, service life, decay, wear estimation
• CPC Class Codes: Y02P 90/80 Management or planning

Abstract

A method for predicting life span of a rotary machine used in a manufacturing apparatus, includes: measuring rotary machine acceleration evaluation time series data with a sampling interval being less than a half the cycle of an analysis target frequency, a number of samplings being at least four times the analysis target frequency; generating evaluation diagnosis data based on variations in characteristics corresponding to the analysis target frequency by subjecting the evaluation time series data to frequency analysis; and determining the life span of the rotary machine using the evaluation diagnosis data.

Claims

1. A method for predicting life span of a rotary machine used in a manufacturing apparatus, comprising:

measuring rotary machine acceleration evaluation time series data with a sampling interval being less than a half the cycle of an analysis target frequency, a number of samplings being at least four times the analysis target frequency;

generating evaluation diagnosis data based on variations in characteristics corresponding to the analysis target frequency by subjecting the evaluation time series data to frequency analysis; and

determining the life span of the rotary machine using the evaluation diagnosis data.

2. The method of claim 1, wherein the rotary machine is a dry pump used in a semiconductor manufacturing apparatus.

3. The method of claim 2, wherein the analysis target frequency is fixed at an integral multiple of a reference frequency unique to the rotary machine.

4. The method of claim 2, wherein the characteristics represents a peak acceleration value.

5. The method of claim 4, wherein the evaluation diagnosis data is generated by a decrease rate of the peak acceleration value and determines a time point where the decrease rate exceeds a threshold value just before shutdown.

6. The method of claim 4, wherein the evaluation time series data is sampled and measured under conditions where a load defined by process conditions for the rotary machine is constant, the evaluation diagnosis data being generated therefrom and the life span is determined by transient changes of increase and decrease of the peak value determined by the evaluation diagnosis data.

7. The method of claim 2, wherein the characteristics represents a frequency at a peak acceleration.

8. The method of claim 7, wherein the evaluation diagnosis data is generated by a decrease rate for the frequency at the peak acceleration and determines a time point where the decrease rate exceeds a threshold value just before shutdown.

9. A method for predicting life span of a rotary machine used in manufacturing apparatus, comprising:

measuring reference time series data of an acceleration of the rotary machine and evaluation time series data of the acceleration respectively, with a sampling interval being less than a half the cycle of an analysis target frequency, a number of samplings being at least four times the analysis target frequency or more;

generating reference diagnosis data based on variations in characteristics corresponding to the analysis target frequency by subjecting the reference time series data to a frequency analysis;

generating evaluation diagnosis data based on variations in a peak value by subjecting the evaluation time series data to the frequency analysis; and

determining the life span of the rotary machine using the reference diagnosis data and the evaluation diagnosis data.

10. The method of claim 9, wherein the rotary machine is a dry pump used in semiconductor manufacturing apparatus.

11. The method of claim 10, wherein the analysis target frequency is fixed at an integral multiple of a reference frequency unique to the rotary machine.

12. The method of claim 10, wherein the characteristics represents a peak acceleration value.

13. The method of claim 12, wherein the evaluation diagnosis data is generated using the decrease rate of the peak acceleration value and determines a time point where the decrease rate exceeds a threshold value just before shutdown.

14. The method of claim 12, wherein the reference diagnosis data is obtained as a first peak acceleration from the reference time series data before a film deposition sequence using the dry pump, the evaluation diagnosis data is obtained from the evaluation time series data after the film deposition sequence as a second peak acceleration, and a time where an acceleration ratio of the second peak acceleration to the first peak acceleration becomes smaller than a threshold value is determined as being the end of the life span.

15. The method of claim 12, wherein the evaluation time series data is measured under conditions where a load defined by process conditions for the dry pump is constant, the evaluation diagnosis data is generated therefrom, and life span is determined with transient changes of increase and decrease of the peak value shown through the evaluation diagnosis data.

16. The method of claim 12, wherein a Mahalanobis space is formed with the reference diagnosis data obtained from the reference time series data measured at a time that is earlier than the time where the evaluation time series data is measured by a predetermined length of time determined through an empirical rule under the same process conditions as the evaluation time series data, calculating a Mahalanobis distance of the evaluation diagnosis data based on the Mahalanobis space, and determining a time point where the Mahalanobis distance exceeds a threshold value as just before the end of the life span.

17. The method of claim 10, wherein the characteristics represents a frequency at the peak acceleration.

18. The method of claim 17, wherein the evaluation diagnosis data is generated using the decrease rate of the frequency at the peak acceleration and determines a time point where the decrease rate exceeds a threshold value as just before life span.

19. The method of claim 17, wherein the reference diagnosis data is obtained as the first peak acceleration from the reference time series data before a film deposition sequence using the dry pump, the evaluation diagnosis data is obtained from the evaluation time series data after the film deposition sequence as the second peak acceleration, and a time where a frequency ratio of the frequency at the peak of the acceleration of the second peak acceleration to the first peak acceleration becomes smaller than a threshold value is determined as being the end of the life span.

20. The method of claim 17, wherein a Mahalanobis space is formed with the reference diagnosis data obtained from the reference time series data measured at a time that is earlier than the time where the evaluation time series data is measured by a length of time determined through an empirical rule under the same process conditions as the evaluation time series data, calculating a Mahalanobis distance of the evaluation diagnosis data based on that Mahalanobis space, and determining a time point where that Mahalanobis distance exceeds a threshold value as just before the end of the life span.

21. A life predicting system, comprising:

a rotary machine;

an accelerometer for sampling and measuring evaluation time series data for an acceleration of the rotary machine with a sampling interval being less than half a cycle of an analysis target frequency, a number of samplings being at least four times the analysis target frequency or more;

a frequency analysis device for performing a frequency analysis on an output from the accelerometer;

a peak acceleration transition recording module for generating evaluation diagnosis data based on variations in characteristics corresponding to the analysis target frequency from the evaluation time series data using results of the frequency analysis, and recording the evaluation diagnosis data; and

a life span determination unit for determining life span of the rotary machine using the evaluation diagnosis data.

22. The system of claim 21, wherein the rotary machine is a dry pump used in a semiconductor manufacturing apparatus.

23. The system of claim 22, wherein the analysis target frequency is fixed at an integral multiple of a reference frequency unique to the rotary machine.

24. The system of claim 22, wherein the characteristic represents a peak acceleration value.

25. The system of claim 22, wherein the characteristic represents a frequency at the peak acceleration.

26. The system of claim 22, wherein the accelerometer is placed one of on a top surface of a gear box of the rotary machine, on a side surface of the gear box, on a bottom surface of the gear box, on a top surface of a casing within 20 cm from the gear box, on a side surface of the casing, and on a bottom surface of the casing.

27. A life predicting system, comprising:

a rotary machine;

an accelerometer for sampling and measuring reference time series data for an acceleration of the rotary machine and evaluation time series data of the acceleration respectively, with a sampling interval being less than half a cycle of an analysis target frequency, a number of samplings being at least four times the analysis target frequency or more;

a frequency analysis device for performing a frequency analysis on an output from the accelerometer;

a peak acceleration transition recording module for generating reference diagnosis data based on variations in a peak value of acceleration corresponding to the analysis target frequency from the reference time series data, generating evaluation diagnosis data based on variations in a peak value from the evaluation time series data, with results of the frequency analysis, and recording the reference diagnosis data and the evaluation diagnosis data; and

a life span determination unit for determining life span of the rotary machine using the reference diagnosis data and the evaluation diagnosis data.

28. The system of claim 27, wherein the rotary machine is a dry pump used in semiconductor manufacturing apparatus.

29. The system of claim 28, wherein the analysis target frequency is fixed at an integral multiple of a reference frequency unique to the dry pump.

30. The system of claim 28, wherein the characteristic represents a peak acceleration value.

31. The system of claim 28, wherein the characteristic represents a frequency at the peak acceleration.

32. The system of claim 28, wherein the accelerometer is placed one of on a top surface of a gear box of the dry pump, on a side surface of the gear box, on a bottom surface of the gear box, on a top surface of a casing within 20 cm from the gear box, on a side surface of the casing, and on a bottom surface of the casing.