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
收藏
页码：783 / 785
页数：3
相关论文
共 50 条
  • [1] A new paradigm for accident investigation and analysis in the era of big data
    Huang, Lang
    Wu, Chao
    Wang, Bing
    Ouyang, Qiumei
    PROCESS SAFETY PROGRESS, 2018, 37 (01) : 42 - 48
  • [2] A new paradigm of software service engineering in big data and big service era
    Xu, Xiaofei
    Motta, Gianmario
    Tu, Zhiying
    Xu, Hanchuan
    Wang, Zhongjie
    Wang, Xianzhi
    COMPUTING, 2018, 100 (04) : 353 - 368
  • [3] A new paradigm of software service engineering in big data and big service era
    Xiaofei Xu
    Gianmario Motta
    Zhiying Tu
    Hanchuan Xu
    Zhongjie Wang
    Xianzhi Wang
    Computing, 2018, 100 : 353 - 368
  • [4] Education management and technology reform in big data era - a new paradigm
    Mo, Xuejian
    Proceedings of the 2016 3rd International Conference on Mechatronics and Information Technology (ICMIT), 2016, 49 : 865 - 868
  • [5] A Comprehensive "Big-Data-Based" Monitoring System for Yield Enhancement in Semiconductor Manufacturing
    Nakata, Kouta
    Orihara, Ryohei
    Mizuoka, Yoshiaki
    Takagi, Kentaro
    INTERNATIONAL SYMPOSIUM ON SEMICONDUCTOR MANUFACTURING (ISSM) 2016 PROCEEDINGS OF TECHNICAL PAPERS, 2016,
  • [6] Analysing semiconductor manufacturing big data for root cause detection of excursion for yield enhancement
    Chien, Chen-Fu
    Liu, Chiao-Wen
    Chuang, Shih-Chung
    INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH, 2017, 55 (17) : 5095 - 5107
  • [7] A Comprehensive Big-Data-Based Monitoring System for Yield Enhancement in Semiconductor Manufacturing
    Nakata, Kouta
    Orihara, Ryohei
    Mizuoka, Yoshiaki
    Takagi, Kentaro
    IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING, 2017, 30 (04) : 339 - 344
  • [8] Advanced Semiconductor Manufacturing Using Big Data
    Tsuda, Tomio
    Inoue, Shinji
    Kayahara, Akihiro
    Imai, Shin-ichi
    Tanaka, Tomoya
    Sato, Naoaki
    Yasuda, Satoshi
    IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING, 2015, 28 (03) : 229 - 235
  • [9] Advantages of Using Big Data in Semiconductor Manufacturing
    Villareal, Gabe
    Na, James
    Lee, Joe
    Ho, Tom
    2018 29TH ANNUAL SEMI ADVANCED SEMICONDUCTOR MANUFACTURING CONFERENCE (ASMC), 2018, : 139 - 142
  • [10] AUC Maximization in the Era of Big Data and AI: A Survey
    Yang, Tianbao
    Ying, Yiming
    ACM COMPUTING SURVEYS, 2023, 55 (08)
12345