A Clustering Analysis Model For Golden Die Extractions Based On Wafer Acceptance Test At Semiconductor R D Stage
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A Clustering Analysis Model for Golden Die Extractions Based on Wafer Acceptance Test at Semiconductor R&D Stage
During the research and development (R&D) stage of semiconductor fabrication, the R&D engineers make a lot of effort to identify golden dice that meet simulated performance of circuit design. With feedback from wafer acceptance test (WAT) data of the golden dice, the efficiency of process window analysis can be further improved. However, it is difficult for current practices to select golden dice due to limited time and cost concerns. In this research, an analytical model is proposed to analyze WAT data during the R&D stage of semiconductor fabrication to assist R&D engineers in resolving these critical issues. WAT data are collected and utilized to classify dice on a wafer and similar golden dice are then identified based on pre-defined golden dice. Similar golden dice can provide much more important feedback from WAT data, and the efficiency of process window analysis can then be improved. Real WAT data at the R&D stage during semiconductor fabrication were collected from a famous semiconductor manufacturing company and were experimented through the presented methodology. Experimental results show that the presented model can successfully extract representative similar golden dice within clusters. With advice from R&D engineers, the representative similar golden dice extracted from this work are sufficient for subsequent process window analysis.
The Greenhouse Gas Protocol
The GHG Protocol Corporate Accounting and Reporting Standard helps companies and other organizations to identify, calculate, and report GHG emissions. It is designed to set the standard for accurate, complete, consistent, relevant and transparent accounting and reporting of GHG emissions.
Advances in Production Management Systems. Smart Manufacturing for Industry 4.0
The two-volume set IFIP AICT 535 and 536 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2018, held in Seoul, South Korea, in August 2018. The 129 revised full papers presented were carefully reviewed and selected from 149 submissions. They are organized in the following topical sections: lean and green manufacturing; operations management in engineer-to-order manufacturing; product-service systems, customer-driven innovation and value co-creation; collaborative networks; smart production for mass customization; global supply chain management; knowledge based production planning and control; knowledge based engineering; intelligent diagnostics and maintenance solutions for smart manufacturing; service engineering based on smart manufacturing capabilities; smart city interoperability and cross-platform implementation; manufacturing performance management in smart factories; industry 4.0 - digitaltwin; industry 4.0 - smart factory; and industry 4.0 - collaborative cyber-physical production and human systems.