Process Chamber Error Analysis Using Recipe Data Matching
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Solution Overview
Problem
Current methods for analyzing errors in substrate processing apparatuses are inefficient, requiring significant time and data to identify the cause of issues, and can produce varying results depending on the analyst's skill, often leading to omitted important data and prolonged downtime.
Innovation Solution
A substrate processing apparatus with a data matching control part that compares apparatus data from recipes executed before and during an error, using a selection unit to choose similar conditions, an acquisition unit to gather data, and a calculation unit to match and calculate differences, thereby shortening analysis time and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional error analysis methods are used, then the analysis can be performed with simple procedures, but the analysis time is long and efficiency is low
Solution Approach 1:
The system pre-stores apparatus data from multiple recipes executed under different conditions in a storage unit before errors occur. When an error happens, the data matching control part can immediately retrieve and compare this pre-prepared data without needing to collect it during the error analysis process, thus reducing analysis time significantly
Solution Approach 2:
The system creates copies of apparatus data from previously executed recipes and stores them in the storage unit. These data copies can be rapidly retrieved and compared when errors occur, eliminating the need to re-collect original data and enabling fast error analysis through data comparison
2Measurement precision
If conventional error analysis methods are used, then the analysis can be performed with simple procedures, but the accuracy varies depending on analyst skill and important data may be omitted
Solution Approach 1:
The data matching control part automatically compares apparatus data from the error-containing recipe with data from other recipes, and provides feedback by identifying differences and potential error causes. This automated feedback mechanism eliminates dependence on analyst skill and ensures consistent, accurate error identification
Solution Approach 2:
The system performs self-diagnosis by automatically comparing its own stored apparatus data to identify errors. The data matching control part autonomously retrieves relevant data, performs comparisons, and identifies error causes without requiring external analyst intervention, thus improving accuracy while managing complexity through automation
3Measurement precision
If all apparatus data is compared to ensure thorough analysis, then accuracy is improved, but the data processing load and time consumption increase significantly
Solution Approach 1:
The data matching control part extracts only the specific apparatus data relevant to the error condition from the storage unit, rather than comparing all stored data. By selectively retrieving and comparing only necessary data points, the system maintains high analysis accuracy while significantly reducing data processing time and computational load
Data Source
AI summary
A substrate processing apparatus includes an operating unit for transmitting apparatus data to a memory, the apparatus data being required while a recipe for processing a substrate is executed; and a data matching unit for comparing the apparatus data stored in the memory. When an error occurs in the substrate processing apparatus, the operating unit transmits data representing the error to the data matching unit. The data matching unit includes: a selection unit for selecting first apparatus data which was acquired when the recipe was executed without an occurrence of the error, and stored in the memory; an acquisition unit for acquiring first and second apparatus data from the memory, the first apparatus data being acquired when an error did not occur and the second apparatus data being acquired when an error occurred; and a calculation unit for comparing the first and second apparatus data and calculating a difference therebetween.