Diagnosing method for service life of semiconductor manufacturing apparatus

A technology for manufacturing devices and diagnostic methods, applied in semiconductor/solid-state device manufacturing, pump control, general control systems, etc., and can solve problems such as reduced operating efficiency, defective products, and increased maintenance frequency

Inactive Publication Date: 2003-03-19
KK TOSHIBA
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0003] In a specific manufacturing process, when the pump is stopped, not only a lot of products in the manufacturing process are defective, but also due to the generation of fine dust inside the manufacturing equipment, sufficient maintenance of the manufacturing equipment is required, so the manufacturing efficiency of semiconductor devices is greatly reduced
In order to prevent the sudden stop in the process, when considering the margin in the maintenance time of the pump, the maintenance frequency of the pump increases, not only the maintenance cost increases, but also the operation efficiency of the semiconductor manufacturing equipment is significantly reduced due to the replacement of the pump, and the semiconductor device is reduced. Manufacturing efficiency is greatly reduced

Method used

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  • Diagnosing method for service life of semiconductor manufacturing apparatus
  • Diagnosing method for service life of semiconductor manufacturing apparatus
  • Diagnosing method for service life of semiconductor manufacturing apparatus

Examples

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no. 1 example

[0030] In the method for diagnosing the lifetime of semiconductor manufacturing equipment according to the first embodiment of the present invention, the time-series data of characteristic quantities such as motor current, motor power, pressure inside the pump, vibration, and gas temperature obtained from the semiconductor manufacturing equipment are analyzed to predict A probabilistic approach to future failures of semiconductor manufacturing equipment. For example, it can be observed that "the motor current of the dry pump increases at a certain moment, and the motor current increases after a specific hysteresis width (data interval) τ", which is helpful for the fault diagnosis of the dry pump.

[0031] First, in order to analyze time-series data of feature quantities acquired from semiconductor manufacturing equipment, it is necessary to assume constancy. Invariance simply means that the time series data at each time is realized by the same probability process, or the stati...

no. 2 example

[0057] The life diagnosis method of semiconductor manufacturing equipment according to the second embodiment of the present invention describes an example of using frequency analysis for failure diagnosis of a dry pump. That is, instead of the motor current self-co-dispersion function C(τ) used in the dry pump failure diagnosis of the first embodiment, the frequency distribution of the casing vibration of the dry pump is analyzed.

[0058] The lifetime diagnosis method of a semiconductor manufacturing device according to the second embodiment of the present invention is based on Figure 7 The procedure shown proceeds:

[0059] (1) First, in step S21, time-series data of a characteristic quantity (vibration) of a dry pump as a semiconductor manufacturing apparatus is measured. Vibration measurement is carried out by measuring the acceleration of the housing with an acceleration sensor every 10 seconds. Each measurement was performed at intervals of 0.5 msec for a total of 1 s...

no. 3 example

[0066] The lifetime diagnosis method of a semiconductor manufacturing apparatus according to the third embodiment of the present invention describes an example of using the Mahalanobis distance MD for failure diagnosis of a dry pump. That is, instead of evaluating the transition of the self-co-dispersion function C(τ) of the motor current used in the fault diagnosis of the dry pump according to the first embodiment, characteristic quantities such as the motor current, the pressure inside the pump, and the vibration of the outer wall of the pump are used to generate The Mahalanobis distance MD.

[0067] A lifetime diagnosis method of a semiconductor manufacturing device according to a third embodiment of the present invention is based on Figure 9 The procedure shown proceeds:

[0068] (1) First, in step S31, the reference time of the corresponding feature quantity is measured under the same processing conditions as the target diagnosis at a predetermined time before the time ...

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Abstract

A method for diagnosing life of manufacturing equipment having a rotary machine, includes: measuring reference time series data for characteristics before deterioration of the manufacturing equipment occurs; finding a reference auto covariance function based on the reference time series data; extracting a reference variation caused by variations of the process condition and power supply from the reference auto covariance function, and calculating a cycle of the reference variation; measuring diagnostic time series data for the characteristics in a sequence to be measured of the manufacturing equipment; finding a diagnostic auto covariance function based on the diagnostic time series data; and determining the life of the manufacturing equipment from the diagnostic auto covariance function using a component with a cycle shorter than a cycle of the reference variation.

Description

technical field [0001] The present invention relates to a diagnostic method for predicting the lifetime of semiconductor manufacturing equipment, and more particularly to a diagnostic method for predicting the lifetime of dry pumps used in CVD devices, dry etching devices, and the like. Background technique [0002] In order to efficiently manufacture semiconductor devices, fault diagnosis of semiconductor manufacturing equipment has become important. In recent years, in system LSIs, there has been an increasing trend toward low-volume, high-variety production, and accordingly, efficient semiconductor device manufacturing methods that can be used in a small area are required. Efficient semiconductor production uses small-scale production lines. However, only by reducing the mass production line, there is a problem of lower investment efficiency due to problems such as a lower operating rate of manufacturing equipment. As a countermeasure, there is a method of performing mu...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): H01L21/302G05B23/02H01L21/02H01L21/3065H01L21/31
CPCG05B23/0283F04D19/04F04D27/001H01L21/02
Inventor 佐俣秀一牛久幸广石井贤中尾隆
Owner KK TOSHIBA
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