Data Indexing for Semiconductor Failure Pattern Correlation
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Solution Overview
Problem
Current semiconductor manufacturing processes face significant challenges in efficiently storing and retrieving large amounts of manufacturing data, particularly failure data, which requires considerable computing resources and time, leading to delays in corrections and resource utilization.
Innovation Solution
The method involves generating an index for storing data by determining failure patterns and correlating them, allowing for efficient organization and retrieval of data through a relational database, where each failure pattern is stored once and subsequent matches are referenced via an index, reducing storage needs and processing time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If large amounts of manufacturing data are stored in databases, then data completeness is improved, but storage requirements and processing time increase
Solution Approach 1:
The patent creates index copies of manufacturing data that capture essential patterns and relationships without duplicating the entire dataset. The index structure stores condensed representations of data patterns, allowing the system to reference original data when needed while maintaining a compact summary for quick access and analysis.
Solution Approach 2:
The patent extracts key patterns, relationships, and metadata from the full manufacturing dataset to create a separate index structure. This extraction process identifies and stores only the most relevant data characteristics, separating the essential indexing information from the complete raw data while maintaining referential integrity.
2Reliability
If large amounts of manufacturing data are stored in databases, then data completeness is improved, but retrieval time increases
Solution Approach 1:
The patent segments the manufacturing data into two distinct components: a compact index structure for rapid access and the complete original dataset for detailed analysis. The index contains segmented, organized references to data patterns, while the full data remains stored separately, allowing quick pattern matching without scanning entire datasets.
Solution Approach 2:
The patent performs preliminary organization and pattern recognition on manufacturing data during the indexing phase, before actual retrieval operations. By pre-processing and structuring data relationships in advance, the system eliminates the need for time-consuming searches during production, as the index is already optimized for rapid querying.
3Productivity
If computing resources are increased to process manufacturing data, then processing speed is improved, but resource utilization efficiency decreases
Solution Approach 1:
The patent introduces an index structure as an intermediary layer between the manufacturing data and processing operations. This intermediary pre-organizes data relationships and patterns, allowing the system to answer queries and perform analysis without directly processing the full dataset, thereby reducing computational resource requirements while maintaining processing speed.
Data Source
AI summary
A method, apparatus, and a system for generating an index for storing data. A pattern associated with a first set of data is determined. The first set of data is stored. A determination is made as to whether the pattern associated with a second set of data corresponds to the pattern associated with the first set of data. An index associated with the first set of data is correlated to the second set of data in response to determining that the pattern associated with the second set of data corresponds to the pattern associated with the first set of data.