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US-2024419867-A1 · Dec 19, 2024 · US
Method for rejecting tuning disturbances to improve lamp failure prediction quality in thermal processes
US10140394B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10140394-B2 |
| Application number | US-201514841365-A |
| Country | US |
| Kind code | B2 |
| Filing date | Aug 31, 2015 |
| Priority date | Sep 25, 2014 |
| Publication date | Nov 27, 2018 |
| Grant date | Nov 27, 2018 |
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Abstract
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Embodiments disclosed herein include methods for reducing or eliminating the impact of tuning disturbances during prediction of lamp failure. In one embodiment, the method comprises monitoring data of a lamp module for a process chamber using one or more physical sensors disposed at different locations within the lamp module, creating virtual sensors based on monitoring data of the lamp module, and providing a prediction model for the lamp module using the virtual sensors as inputs.
First claim
Opening claim text (preview).
What is claimed is: 1. A method for lamp failure prediction, comprising: creating virtual sensors by collecting data comprising current and resistance related to an upper lamp and a lower lamp of a lamp module disposed in a semiconductor process chamber, wherein the virtual sensors are represented as equations selected from one or more of the following: first virtual sensor = log ( abs ( TII k 1 * TIR ) + 1 ) , second virtual sensor = log ( abs ( TOI k 2 * TOR ) + 1 ) , third virtual sensor = log ( abs ( BII k 3 * BIR ) + 1 ) , fourth virtual sensor = log ( abs ( BOI k 4 * BOR ) + 1 ) , and fifth virtual sensor = log ( abs ( TII k 1 * TIR + TOI k
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Classifications
- G06F30/20Primary
Design optimisation, verification or simulation (optimisation, verification or simulation of circuit designs G06F30/30) · CPC title
Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks · CPC title
Virtual sensor · CPC title
Logarithmic or exponential functions · CPC title
Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods · CPC title
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- What does patent US10140394B2 cover?
- Embodiments disclosed herein include methods for reducing or eliminating the impact of tuning disturbances during prediction of lamp failure. In one embodiment, the method comprises monitoring data of a lamp module for a process chamber using one or more physical sensors disposed at different locations within the lamp module, creating virtual sensors based on monitoring data of the lamp module,…
- Who is the assignee on this patent?
- Applied Materials Inc
- What technology area does this patent fall under?
- Primary CPC classification G06F30/20. Mapped technology areas include Physics.
- When was this patent published?
- Publication date Tue Nov 27 2018 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
- What related patents are in patentsdb?
- We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).