Digital Twins for Yield
Analyzing Manufacturing Sensor and Process Data at Scale

On Demand Webinar

Digital twins are virtual representations of physical systems. The current interest in them is fueled by the convergence of IoT, machine learning and big data technology. As process complexity increases, they are becoming key to efficient operations and high product yields.

There is now a demand for ‘wide-and-big data’ analytic solutions that detect associations between product quality metrics and thousands to millions of process variables. These cutting edge solutions can support root-cause and predictive analyses. Further, the results must be available close to "real-time" to enable useful process interventions — for example to identify subtle equipment changes, process shift or drift, or to predict and remedy substandard yield for a lot in the line.

This webinar focuses on the implementation of a semiconductor manufacturing digital twin for yield that detects associations between product quality metrics and up to millions of predictor process.

What you will see via demos and learn about:

  • How hybrid big-data plus in-memory systems are being utilized to address the various new analytic and IT-architecture problems associated with this challenge
  • How to combine large-scale distributed analytics capabilities with comprehensive server- and in-memory-based advanced analytics
  • How to deliver actionable interactive results through intelligent visualizations.

Speakers:

Mike Alperin, Manufacturing Industry Consultant

Steven Hillion, Sr. Director Data Science

觀看網絡研討會

要處理您的註冊,TIBCO Software Inc.和 TIBCO 附屬公司 (統稱“TIBCO”)需要從您那裡收集以下個人資料。通過註冊此TIBCO資源, 即表示您同意TIBCO處理此個人資料並通過電子郵件,電話和/或社交媒體與 資源-相關的信息與您聯繫。

TIBCO還希望通過電子郵件,電話和/或社交媒體與您聯繫,了解您可能感興趣的產品和服務。請在下面表明您同意我們使用您的個人資料。

TIBCO可就其產品和服務與我聯繫。