Semiconductor Part Tracking via Golden MDA for Coupling Effect Detection
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Solution Overview
Problem
Current semiconductor manufacturing tool part kits often lead to coupling effects due to unknown part provenance and interactions, resulting in tool faults and prolonged troubleshooting, causing resource wastage and downtime.
Innovation Solution
A system and method for part tracking and kit verification using unique data matrix codes encoded with part identification and performance data, where a multi-dimensional array (MDA) of part data is compared to detect potential coupling effects, and a kit unique code is generated to determine if parts will cause a coupling effect based on usage history.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If parts are assembled into a kit based on a parts list without tracking part provenance, then kit assembly is simple and quick, but coupling effects between parts cannot be detected, leading to tool faults and prolonged troubleshooting
Solution Approach 1:
The system performs preliminary actions by encoding part identification data into data matrices before assembly, creating a golden MDA that stores provenance information. This allows the system to detect coupling effects before the kit is installed in the tool, preventing faults rather than addressing them after assembly.
Solution Approach 2:
The system creates a digital copy (golden MDA) of the parts list with embedded provenance information from data matrices. This digital replica allows verification of part compatibility without physically examining each part, maintaining quick assembly while ensuring reliability through data-based verification.
2Reliability
If part provenance and interaction data are tracked using data matrices and golden MDA, then coupling effects can be detected early, but the system complexity increases
Solution Approach 1:
The golden MDA serves multiple functions: it stores part identification data, tracks provenance information, enables coupling effect detection, and provides a verification mechanism. This multi-functional approach consolidates what would otherwise require separate systems into a single unified structure.
Solution Approach 2:
The data matrix acts as an intermediary carrier that bridges physical parts and their digital provenance information. By encoding part identification data into machine-readable data matrices, the system creates a standardized interface that simplifies tracking without requiring complex direct monitoring of each part.
3Ease of repair
If coupling effects are detected after tool installation, then troubleshooting can identify the fault cause, but tool downtime increases and resources are wasted
Solution Approach 1:
The system performs coupling effect detection before the kit is installed in the tool by comparing the golden MDA with the assembled kit composition. This preliminary verification prevents incompatible parts from being installed, eliminating the need for post-installation troubleshooting and avoiding tool downtime entirely.
Solution Approach 2:
The system provides feedback on part compatibility by comparing the assembled kit against the golden MDA standards. This feedback mechanism allows operators to verify kit composition and detect potential coupling effects before installation, preventing faults rather than requiring corrective action after installation.
4Measurement precision
If data matrices are scanned and verified against golden MDA for each kit, then part authenticity and compatibility are ensured, but the verification process time increases
Solution Approach 1:
The system uses digital copies (data matrices and golden MDA) to represent physical parts and their specifications. By comparing digital representations rather than physically examining each part, the system achieves high verification accuracy quickly through automated data comparison rather than manual inspection.
Solution Approach 2:
The system replaces manual part verification with automated optical scanning and digital data comparison. Machine-readable data matrices are scanned and automatically compared against the golden MDA, substituting time-consuming manual verification with rapid automated processing that maintains high precision.
Data Source
AI summary
The present disclosure relates to systems and methods for semiconductor tool part tracking and kit verification. Data relating to part identification and performance are encoded to a unique code that is encoded into machine-readable form, such as a data matrix. A multi-dimensional array (MDA) of the data matrices of a group of parts is a ‘golden MDA’. When assembled into a kit, the parts are scanned and compared to the golden MDA. If there's a match, a kit unique code is used to generate a kit data matrix. The part data matrix codes are provided to a database to determine if a part combination will cause a coupling effect, based on part usage history.