Cleaning Tool State Prediction From Substrate Processing Conditions
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Solution Overview
Problem
Existing methods for determining the state of a cleaning tool in a substrate processing apparatus are inadequate as they do not account for the complex interactions between various operating conditions, leading to inaccurate predictions based solely on accumulated use time or number.
Innovation Solution
An information processing apparatus that utilizes machine learning to predict the state of a cleaning tool by inputting operating condition information, including substrate-holder, cleaning-fluid-supply-structure, and cleaning-tool-cleaning-structure states, to a learning model trained on these conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the cleaning tool state is determined by accumulated use time or number of uses, then the management is simple, but the prediction accuracy of cleaning tool state is insufficient
Solution Approach 1:
The patent changes from using a single parameter (accumulated use time or number of uses) to using multiple parameters (substrate holder state, cleaning fluid supply structure state, substrate cleaning structure state, cleaning tool cleaning structure state) to predict the cleaning tool state, thereby improving prediction accuracy while maintaining manageable complexity through systematic data collection
2Measurement precision
If multiple operating conditions are considered for cleaning tool state prediction, then the prediction accuracy is improved, but the analysis complexity increases
Solution Approach 1:
The patent segments the complex system into distinct components (substrate holder, cleaning fluid supply structure, substrate cleaning structure, cleaning tool cleaning structure), each with its own state parameters. This segmentation allows systematic collection and analysis of multiple operating conditions without overwhelming complexity, as each component's state can be independently monitored and then integrated for overall cleaning tool state prediction
Data Source
AI summary
The information processing apparatus (5) includes: an information acquisition section (500) configured to acquire operating condition information as operating conditions under which a substrate processing apparatus operates. The operating condition information includes substrate-holder state information, cleaning-fluid-supply-structure state information, substrate-cleaning-structure state information, and cleaning-tool-cleaning-structure state information. The substrate processing apparatus includes the substrate holder configured to hold a substrate, the cleaning-fluid supply structure configured to supply substrate cleaning fluid onto the substrate, the substrate cleaning structure configured to rotatably support a cleaning tool and bring the cleaning tool into contact with the substrate to clean the substrate, and the cleaning-tool cleaning structure. The information processing apparatus (5) further includes a state prediction section (501) configured to predict cleaning-tool state information for the operating condition information by inputting the operating condition information acquired by the information acquisition section (500) to a learning model that has been generated by machine learning that causes the learning model to learn a correlation between the operating condition information and the cleaning-tool state information.