FAULT DETECTION AND VIRTUAL SENSOR METHODS FOR TOOL FAULT MONITORING

Patent №

US 6,895,293

Granted

2005-05-17

Filed 2001

Owner

APPLIED MATERIALS, INC. A CORPORATION OF THE STATE OF DELAWARE

Lab

AI components

4

ml · kr · planning · hardware

Assignment

Recorded

Dataset

AIPD

2023_r1 edition

Application

09833516

Fault detection of a semiconductor processing tool employs several techniques to improve accuracy. One technique is sensor grouping, wherein a fault detection index is calculated from a group of tool operational parameters that correlate with one another. Another technique is sensor ranking, wherein sensors are accorded different weights in calculating the fault detection index. Improved accuracy in fault detection may be accomplished by employing a variety of sensor types to predict behavior of the semiconductor processing tool. Examples of such sensor types include active sensors, cluster sensors, passive/inclusive sensors, and synthetic sensors.

Machine learningKnowledge representationPlanningAI hardwareG05B 19/41865G05B 2219/31357G05B 2219/31443Y02P 90/02

AI classification

Planning1.00
AI hardware1.00
Machine learning0.71
Knowledge representation0.65
Vision0.01
Natural language0.00
Evolutionary computation0.00
Speech0.00

Ownership

APPLIED MATERIALS, INC. A CORPORATION OF THE STATE OF DELAWARE

assignment · 117300895

Assignors

REISS, TERRY, LYMBEROPOULOS, DIMITRIS P.

On an employer assignment, the assignors are typically the inventors.

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