Vacuum Leak Detection Method Using Index Regression and Correction for Semiconductor Equipment in a Vacuum Chamber
In semiconductor manufacturing, fault detection is an important method for monitoring equipment condition and examining the potential causes of a fault. Vacuum leakage is considered one of the major faults that can occur in semiconductor processing. An unnecessary O<sub>2</sub> and N<...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-12-01
|
| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/11/24/11762 |
| _version_ | 1827674332474638336 |
|---|---|
| author | Taekyung Ha Hyunjung Shin |
| author_facet | Taekyung Ha Hyunjung Shin |
| author_sort | Taekyung Ha |
| collection | DOAJ |
| description | In semiconductor manufacturing, fault detection is an important method for monitoring equipment condition and examining the potential causes of a fault. Vacuum leakage is considered one of the major faults that can occur in semiconductor processing. An unnecessary O<sub>2</sub> and N<sub>2</sub> mixture, a major component of the atmosphere, creates unexpected process results and hence drops in yield. Vacuum leak detection systems that are currently available in the vacuum industry are based on helium mass spectrometers. They are used for detecting the vacuum leakage at the sole isolation condition where the chamber is fully pumped but cannot be used for in situ detection while the process is ongoing in the chamber. In this article, a chamber vacuum leak detection method named Index Regression and Correction (IRC) is presented, utilizing common data which were gathered during normal chamber operation. This method was developed by analyzing a simple list of data, such as pressure, the temperature of the chamber body, and the position of the auto pressure control (APC), to detect any leakages in the vacuum chamber. The proposed method was experimentally verified and the results showed a high accuracy of up to 97% when a vacuum leak was initiated in the chamber. The proposed method is expected to improve the process yield of the chamber by detecting even small vacuum leakages at very early stages of the process. |
| first_indexed | 2024-03-10T04:38:01Z |
| format | Article |
| id | doaj.art-d36cba4388594000b1802807779f0035 |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-10T04:38:01Z |
| publishDate | 2021-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-d36cba4388594000b1802807779f00352023-11-23T03:37:56ZengMDPI AGApplied Sciences2076-34172021-12-0111241176210.3390/app112411762Vacuum Leak Detection Method Using Index Regression and Correction for Semiconductor Equipment in a Vacuum ChamberTaekyung Ha0Hyunjung Shin1Department of Industrial Engineering, Ajou University, 206, World cup-ro, Yeongtong-gu, Suwon-si 16499, Gyeonggi-do, KoreaDepartment of Industrial Engineering, Ajou University, 206, World cup-ro, Yeongtong-gu, Suwon-si 16499, Gyeonggi-do, KoreaIn semiconductor manufacturing, fault detection is an important method for monitoring equipment condition and examining the potential causes of a fault. Vacuum leakage is considered one of the major faults that can occur in semiconductor processing. An unnecessary O<sub>2</sub> and N<sub>2</sub> mixture, a major component of the atmosphere, creates unexpected process results and hence drops in yield. Vacuum leak detection systems that are currently available in the vacuum industry are based on helium mass spectrometers. They are used for detecting the vacuum leakage at the sole isolation condition where the chamber is fully pumped but cannot be used for in situ detection while the process is ongoing in the chamber. In this article, a chamber vacuum leak detection method named Index Regression and Correction (IRC) is presented, utilizing common data which were gathered during normal chamber operation. This method was developed by analyzing a simple list of data, such as pressure, the temperature of the chamber body, and the position of the auto pressure control (APC), to detect any leakages in the vacuum chamber. The proposed method was experimentally verified and the results showed a high accuracy of up to 97% when a vacuum leak was initiated in the chamber. The proposed method is expected to improve the process yield of the chamber by detecting even small vacuum leakages at very early stages of the process.https://www.mdpi.com/2076-3417/11/24/11762vacuum leak detectionindex regressionvacuum chambersemiconductor equipment |
| spellingShingle | Taekyung Ha Hyunjung Shin Vacuum Leak Detection Method Using Index Regression and Correction for Semiconductor Equipment in a Vacuum Chamber Applied Sciences vacuum leak detection index regression vacuum chamber semiconductor equipment |
| title | Vacuum Leak Detection Method Using Index Regression and Correction for Semiconductor Equipment in a Vacuum Chamber |
| title_full | Vacuum Leak Detection Method Using Index Regression and Correction for Semiconductor Equipment in a Vacuum Chamber |
| title_fullStr | Vacuum Leak Detection Method Using Index Regression and Correction for Semiconductor Equipment in a Vacuum Chamber |
| title_full_unstemmed | Vacuum Leak Detection Method Using Index Regression and Correction for Semiconductor Equipment in a Vacuum Chamber |
| title_short | Vacuum Leak Detection Method Using Index Regression and Correction for Semiconductor Equipment in a Vacuum Chamber |
| title_sort | vacuum leak detection method using index regression and correction for semiconductor equipment in a vacuum chamber |
| topic | vacuum leak detection index regression vacuum chamber semiconductor equipment |
| url | https://www.mdpi.com/2076-3417/11/24/11762 |
| work_keys_str_mv | AT taekyungha vacuumleakdetectionmethodusingindexregressionandcorrectionforsemiconductorequipmentinavacuumchamber AT hyunjungshin vacuumleakdetectionmethodusingindexregressionandcorrectionforsemiconductorequipmentinavacuumchamber |