Plasma Tool Data Management via Unified Substrate File
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Solution Overview
Problem
Current methods for collecting and managing substrate processing data from cluster tools are inefficient, as data is not readily accessible, stored across multiple tables, and requires time-consuming analysis to reconstruct processing conditions, leading to accuracy and quality issues.
Innovation Solution
A computer-implemented method that collects and stores substrate processing data in a single file, including meta-data and process data streams from transducers, using periodic and event-based methodologies, and indexes the data for easy retrieval and analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If substrate processing data is stored across multiple tables organized by data owner, then data can be collected systematically from different sources, but data access becomes complex and time-consuming when reconstructing processing conditions
Solution Approach 1:
The patent combines data from multiple data owners and tables into a single unified data structure that preserves all process parameters while enabling direct access. Instead of querying multiple tables separately, the unified structure allows retrieval of complete processing conditions in one operation, eliminating the time-consuming process of cross-referencing multiple data sources.
2Device complexity
If data is stored in separate tables for each data owner, then data organization follows a modular structure, but data analysis complexity increases when troubleshooting specific substrates
Solution Approach 1:
The patent segments data by substrate identifier, creating independent data containers for each substrate that include all relevant process parameters. This segmentation allows analysts to isolate and examine individual substrate processing conditions without navigating through complex inter-table relationships, significantly simplifying troubleshooting while maintaining organized data storage.
3Reliability
If absolute timestamps are used across multiple tables, then data synchronization between different data owners is achieved, but perfect matching of timestamps across tables is not guaranteed due to different data collection triggers
Solution Approach 1:
The patent introduces a substrate-specific data structure that acts as an intermediary, collecting and correlating all process parameters based on substrate processing events rather than relying on absolute timestamp synchronization across multiple independent tables. This intermediary structure ensures accurate pairing of process data with the correct substrate and processing conditions, eliminating timestamp matching errors.
4Quantity of substance
If large bandwidth pipeline is used to transmit data to database, then all collected data can be transmitted, but infrastructure complexity and cost increase
Solution Approach 1:
The patent extracts and processes data locally at the source, creating compact substrate-specific data structures that contain only relevant information for each substrate. This extraction approach reduces the overall data volume that needs to be transmitted through the pipeline, as redundant and unnecessary data is filtered out before transmission, thereby reducing infrastructure requirements while maintaining data completeness for analysis.
Data Source
AI summary
A computer-implemented method for managing substrate processing data. Substrate process data is acquired while a substrate is processed in a plasma-processing chamber of a cluster tool. The method includes receiving meta-data that identifies at least one of an identification of the substrate and a process. The method further includes receiving from transducers process data streams, each of the process data streams pertaining to a process parameter being monitored. Individual data items in each of the process data streams are being collected in accordance to one of a first methodology and a second methodology. The first methodology represents data collection that is periodic in time. The second methodology represents data collection that happens when predefined events occur. The method also includes storing individual data items associated with process data streams in a single file. The single file stores only data pertaining to a single recipe used to process the substrate.