New paradigm of Yield analysis in Big Data and AI Era in Semiconductor Manufacturing

被引：0

作者：

David, Jeffrey ^{[1
]}

Gupta, Ashutosh ^{[1
]}

Bamb, Rishi ^{[1
]}

Akar, Said ^{[1
]}

Holt, Jonathan ^{[1
]}

Strojwas, Andrzej ^{[1
]}

Brozek, Tomasz ^{[1
]}

机构：

[1] PDF Solut Inc, Santa Clara, CA 95050 USA

来源：

8TH IEEE ELECTRON DEVICES TECHNOLOGY & MANUFACTURING CONFERENCE, EDTM 2024 | 2024年

关键词：

yield analysis; AI/ML predictive yield models;

D O I：

10.1109/EDTM58488.2024.10512106

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The paper describes how the semiconductor product yield analysis evolved from simple one-way correlation analysis limited by siloed data into powerful cloud based and AI/ML enhanced analytics tool. We discuss the tasks and efforts needed to align all data types, create the Big Data accessible repositories, and deploy end-to-end analytics, updating the AI/ML models using incoming new yield data stream.

引用

页码：783 / 785

页数：3

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