Abstract
AbstractProcess condition was changed by preventative maintenance that may lead to the inconsistency of process output. In practice, process engineers have difficulties to discover the inconsistency that the defect wafer may have been produced before the next measurement. This study proposes a virtual metrology (VM) approach for maintenance compensation in semiconductor manufacturing. The tool process parameter streams were collected to predict the product metrology value, and a relation model was built to adjust the equipment settings for product recipe compensation. An empirical study in maintenance compensation of chemical vapor deposition (CVD) was conducted in a Taiwan semiconductor company for validation. The thickness difference caused by maintenance was reduced from 571A to 77A in training data and 564A to 210A in testing data. The results showed practical viability of the proposed approach and an intelligent system embedded with the developed algorithm has been implemented.
Highlights
Efficient management of maintenance and control for semiconductor manufacturing equipment are essential to improve productivity and yield
Maintenance action is identified by process engineer based on different policies such as Run-to-Failure (R2F) maintenance, scheduled maintenance, Condition-Based Maintenance (CBM) and Predictive Maintenance (PdM)[1]
This study aims to propose a virtual metrology (VM) approach for equipment maintenance compensation in semiconductor manufacturing that uses the real time tool process parameter streams to predict the product metrology value, and building the relation model to compensate values of the product recipe to adjust the equipment settings for yield enhancement
Summary
Efficient management of maintenance and control for semiconductor manufacturing equipment are essential to improve productivity and yield. The inconsistent process output may not be discovered in time and defect wafer may have been produced before the measurement This will result in a wafer yield loss. To deal with this problem, virtual metrology (VM) is proposed to predict the post-process metrology variables by using the in-situ measurements and the wafer state information. This study aims to propose a VM approach for equipment maintenance compensation in semiconductor manufacturing that uses the real time tool process parameter streams to predict the product metrology value, and building the relation model to compensate values of the product recipe to adjust the equipment settings for yield enhancement.
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