Methods and mechanisms to perform maintenance event diagnostics using data matching techniques
The system addresses the inefficiencies in semiconductor manufacturing diagnostics by using data matching and predictive maintenance to accurately identify anomalies and forecast maintenance events, improving efficiency and product quality.
TW202630316APending Publication Date: 2026-07-16APPLIED MATERIALS INC
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Patent Information
- Application Number
- TW114139657
- Authority / Receiving Office
- TW · TW
- Patent Type
- Applications
- Current Assignee / Owner
- Priority Date
- 2025-01-09
- Filing Date
- 2025-10-15
- Publication Date
- 2026-07-16
AI Technical Summary
Technical Problem
Current diagnostic procedures in semiconductor manufacturing fail to accurately identify the root cause of anomalies and cannot perform predictive maintenance, leading to inefficiencies and product yield degradation.
Method used
A system that utilizes data matching techniques to compare sensor data from multiple manufacturing operations, generating normalized datasets and trace-match data to identify fault causes, and implements a predictive maintenance model to forecast potential corrective maintenance events.
Benefits of technology
Improves anomaly detection accuracy, reduces downtime, and prevents unscheduled repairs by identifying root causes and predicting maintenance needs, thereby enhancing manufacturing efficiency and product quality.
✦ Generated by Eureka AI based on patent content.
Abstract
A system configured to, in response to an occurrence of a corrective maintenance event, obtain first sensor data pertaining to a first process run and second sensor data pertaining to a second process run. Responsive to determining that a comparison of the first sensor data and the second sensor data fails to satisfy a first threshold criterion, the system generates a first normalized dataset based on the first sensor data and a second normalized dataset based on the second sensor data. The system then generates trace matching data by performing a trace matching operation on the first normalized dataset and the second normalized dataset. Responsive to determining that the trace matching data satisfies a second threshold criterion, the system identifies a set of sensors associated with the first sensor data as the cause of the fault that triggered the corrective maintenance event.
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