Plasma Processing Apparatus State Prediction Using Environmental Data Filtering
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Solution Overview
Problem
Current methods for predicting the state of plasma processing apparatuses struggle to accurately remove continuous temporal change components caused by physical environment changes, leading to inaccuracies in maintenance timing and apparatus state prediction.
Innovation Solution
A plasma processing apparatus equipped with a state prediction system that extracts and removes temporal change components from input data using principal component analysis, allowing for precise prediction of apparatus state and maintenance needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional data processing methods are used to predict apparatus state, then the prediction system can operate with basic sensor data, but the prediction accuracy is reduced due to inclusion of irrelevant temporal change components
Solution Approach 1:
The patent extracts and removes temporal change components related to physical environment changes (quartz window fogging, cover roughness, insulating film thickness) from the sensor data before performing state prediction. This separation isolates the relevant degradation signals from irrelevant environmental variations, improving prediction accuracy while maintaining manageable system complexity through targeted data filtering.
Solution Approach 2:
The patent transforms the raw sensor data by removing specific temporal change components, effectively changing the parameter composition of the input data. This parameter transformation allows the prediction model to focus on relevant degradation patterns without being confounded by environmental variations, achieving higher precision without proportionally increasing system complexity.
2Reliability
If comprehensive sensor data is used for state prediction, then more information is available for analysis, but irrelevant temporal change components reduce the reliability of prediction results
Solution Approach 1:
The patent selectively extracts and removes specific temporal change components (quartz window fogging, cover roughness, insulating film thickness) from the comprehensive sensor data. This targeted extraction maintains reliable prediction by eliminating known sources of irrelevant variation while preserving other useful information in the sensor data for accurate state assessment.
Solution Approach 2:
The patent introduces an intermediate data processing step that acts as a mediator between raw sensor data and the prediction model. This intermediary process removes irrelevant temporal components before data reaches the prediction algorithm, improving reliability by filtering out noise while maintaining the integrity of relevant degradation signals.
3Reliability
If maintenance is performed frequently to ensure apparatus reliability, then apparatus failure is reduced, but the operation rate and productivity decrease due to increased maintenance time
Solution Approach 1:
The patent performs preliminary state prediction by continuously analyzing sensor data and removing irrelevant temporal components. This preliminary assessment allows maintenance to be scheduled based on actual apparatus condition rather than fixed intervals, enabling maintenance to be performed just in time before failure occurs, thus maintaining reliability while minimizing unnecessary maintenance interruptions to productivity.
Solution Approach 2:
The patent implements a feedback mechanism where the state prediction results (based on filtered sensor data) continuously inform maintenance scheduling decisions. This feedback loop allows the system to adapt maintenance timing to actual apparatus condition, performing maintenance only when predicted degradation indicates necessity, thereby maintaining reliability without excessive maintenance that would reduce productivity.
Data Source
AI summary
A plasma processing apparatus including a state prediction apparatus that predicts an apparatus state of the plasma processing apparatus configured to include an apparatus data recording unit that records apparatus data output from the plasma processing apparatus during the processing of the sample, a physical environment measurement data recording unit that measures physical environment in the processing chamber and records apparatus physical environment data, data correction unit that extracts a temporal change component of the physical environment from a plurality of the apparatus physical environment data recorded in the physical environment measurement data recording unit and extracts the temporal change component of the physical environment from the apparatus data to remove the temporal change components, and an apparatus state prediction calculation unit that predicts the state of the plasma processing apparatus using the apparatus data from which the temporal change component of the physical environment is removed as input data.