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Completed STANDARD GRANT National Science Foundation (US)

Workshops on Smart Manufacturing with Open and Scaled Data Sharing in Semiconductor and Microelectronics Manufacturing; Virtual and In-Person; Washington, DC; October/November 2023

$1M USD

Funder National Science Foundation (US)
Recipient Organization University of California-Los Angeles
Country United States
Start Date Aug 15, 2023
End Date Jun 30, 2025
Duration 685 days
Number of Grantees 2
Roles Principal Investigator; Co-Principal Investigator
Data Source National Science Foundation (US)
Grant ID 2334590
Grant Description

The Workshops on Smart Manufacturing with Open and Scaled Data Sharing in Semiconductor and Microelectronics Manufacturing will convene experts from the microelectronics manufacturing and artificial intelligence (AI) and machine learning (ML) research and practitioner communities, including representatives from relevant companies, universities, federal agencies, national laboratories, and the Manufacturing USA Institutes. The workshop is motivated by and addresses the critical need for manufacturing data in advanced manufacturing, a key finding of the previous workshop series, held under the auspices of the Subcommittee on Advanced Manufacturing and the Subcommittee on Machine Learning and Artificial Intelligence of the National Science and Technology Council.

The inability to access manufacturing data that are contextualized, categorized, and discoverable was identified as a critical industry-wide impediment to smart manufacturing and the full potential of AI to the US economy. Manufacturing does not have the data use or delivery infrastructure for enhancing productivity that has evolved in many other industries.

The aim of the workshops is to formulate a strategy for accessing cross-company microelectronics production data while keeping proprietary data secure. Such a strategy promises to improve the productivity of US microelectronics manufacturing companies by providing machine learning researchers with access to the well-characterized data. These data are needed to innovate new machine learning architectures specifically suited to categorizing manufacturing process data.

The workshop is unique in its focus on detailed industry data the analysis of which defines critical business and technology decisions. The workshop is also unique in emphasizing the broader data science and computer science perspectives with a structure and format that facilitates building cross-community views and interests. The workshop will start with individual community discussions to share positions and understand vocabularies.

These will grow into a series of several cross community virtual roundtables to engage manufacturing and AL/ML researchers with stakeholders from the microelectronics industry in defining specific business and technical questions. These outcomes will be addressed together in a subsequent in-person session in the Washington, DC area. The in-person session will: (1) define and agree on mechanisms for facilitating collaborative data sharing and model building at scale with current technologies and/or by defining needs for new methods, (2) frame an industry, academic, and government collaboration, and (3) create a draft action plan for cross-company data aggregation in the microelectronics manufacturing industry.

The virtual and in-person sessions will include professional writers to assist the organizing committee in taking notes and rationalizing the findings from each session to guide the agenda for the remaining sessions. The in-person session will be followed by a virtual general review and comment session that involves all participants.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

All Grantees

University of California-Los Angeles

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