Substrate Processing Data Calibration Across Different Processing Spaces
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Solution Overview
Problem
Current substrate processing apparatuses face challenges in collecting detailed data from inside the processing space, making it difficult to predict optimal processing conditions and ensuring consistency between experimental and mass-produced apparatuses, leading to inefficiencies in achieving target substrate shapes.
Innovation Solution
A data collection system comprising multiple substrate processing apparatuses and a data collection apparatus that compares and corrects observed data across different processing spaces, using calibration and correction amounts to eliminate machine differences and disturbance influences, and generates virtual measurement and shape simulation models for predicting processing outcomes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple substrate processing apparatuses with different processing spaces are used to collect data, then the efficiency of finding optimal processing conditions is improved, but machine differences and disturbance influences cause measurement inconsistency
Solution Approach 1:
The patent introduces a data collection apparatus as an intermediary that mediates between multiple substrate processing apparatuses and the data analysis system. This intermediary standardizes data collection from different apparatuses, applies correction amounts to eliminate machine differences, and ensures consistent data formatting, thereby resolving the measurement inconsistency problem while maintaining the productivity benefits of using multiple apparatuses
Solution Approach 2:
The patent applies parameter changes by calculating and applying correction amounts to transform observed data from different processing spaces into a standardized reference frame. By changing the data parameters through mathematical correction based on calibration data, the system eliminates the effects of machine differences and disturbance influences, enabling consistent comparison across apparatuses
2Manufacturing precision
If experimental apparatuses are used to search for optimal processing conditions, then processing parameter optimization is improved, but differences between experimental and mass-produced apparatuses lead to inconsistent results
Solution Approach 1:
The patent creates a virtual reference processing space that copies and standardizes the characteristics of a reference substrate processing apparatus. By using this virtual copy as a baseline for correction, the system can translate optimal processing conditions found in experimental apparatuses to mass-produced apparatuses, ensuring reliability and consistency across different apparatus types while maintaining the manufacturing precision benefits of experimental optimization
3Loss of information
If detailed data collection from inside processing space is implemented, then processing condition optimization is improved, but difficulty in obtaining accurate internal data increases
Solution Approach 1:
The patent replaces the need for physical sensors inside processing spaces with a virtual measurement system. Instead of mechanically installing measurement devices that would interfere with processing, the system uses computational methods to reconstruct and infer internal processing conditions from external measurements and calibration data, thereby obtaining detailed information while avoiding the difficulties of direct internal measurement
Data Source
AI summary
A data collection system includes: a first substrate processing apparatus having a first processing space, a second substrate processing apparatus having a second processing space, and a data collection apparatus connected to the first substrate processing apparatus and the second substrate processing apparatus. The data collection apparatus is configured to compare observed data observed when substrates having the same or similar shapes are processed under the same processing conditions in the first processing space and the second processing space, respectively, and calculate a correction amount for correcting the observed data observed when being processed in the second processing space, and correct the observed data observed when being processed in the second processing space based on the correction amount, and collect corrected observed data, when searching for a processing condition by processing substrates while changing the processing condition in the second processing space.


