Expediting Manufacturing Launch Using Integrated Data With AI/ML Analytic Solutions

Manufacturing yield, test time and quality are important metrics in new product introduction (NPI) to manufacturing safe launch. A powerful yield management system is crucial to achieve the goal metrics. In this paper, recommended yield management system selection criteria, data integration and machine learning (ML) methodologies along with innovative ways of using the selected yield management system to benefit safe manufacturing launch efficiency are introduced. Three examples of using a cloud yield tool including ML capabilities to expedite yield learning, test time reduction (TTR) and quality enhancement are presented.

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Publication Details

Journal
IEEE Journal of the Electron Devices Society
Published
2024-12-25
DOI
https://doi.org/10.1109/jeds.2024.3522126
Citations
1
Primary Topic
Manufacturing Process and Optimization
Type
article
Field-Weighted Citation Impact
0.35
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article

Expediting Manufacturing Launch Using Integrated Data With AI/ML Analytic Solutions

Jeffrey David, Tomonori Honda, R. Burch, Helen Yu et al.
1 citations
IEEE Journal of the Electron Devices Society
Manufacturing Process and Optimization
0.35
article

Expediting Manufacturing Launch Using Integrated Data With AI/ML Analytic Solutions

Jeffrey David, Tomonori Honda, R. Burch, Helen Yu, Scott D. Martin, Laurenz van der Meer, Wanting Xiong, Edward Yang, Sherry Lee, Vaishnavi Reddipalli
article en
1 citations

Abstract

Manufacturing yield, test time and quality are important metrics in new product introduction (NPI) to manufacturing safe launch. A powerful yield management system is crucial to achieve the goal metrics. In this paper, recommended yield management system selection criteria, data integration and machine learning (ML) methodologies along with innovative ways of using the selected yield management system to benefit safe manufacturing launch efficiency are introduced. Three examples of using a cloud yield tool including ML capabilities to expedite yield learning, test time reduction (TTR) and quality enhancement are presented.

IEEE Journal of the Electron Devices SocietyVol. 13
PDF Solutions (United States) (US), Renesas Electronics (United States) (US)
Industry, innovation and infrastructure
Openalex Percentile: Top 32%
Manufacturing Process and Optimization
0.35
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Expediting Manufacturing Launch Using Integrated Data With AI/ML Analytic Solutions — Jeffrey David, Tomonori Honda, et al. · IEEE Journal of the Electron Devices Society (2024) | TGRS Research Map | TGRS