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

半导体和微电子制造中开放和规模化数据共享的智能制造研讨会；

• 批准号: 2334590
• 负责人: James Davis
• 金额: $ 10万
• 依托单位: University of California-Los Angeles
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-15 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2334590&HistoricalAwards=false
• 关键词: Workshops; Smart; Manufacturing; Open; Scaled

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.

半导体和微电子制造中具有开放和大规模数据共享的智能制造研讨会将召集来自微电子制造以及人工智能（AI）和机器学习（ML）研究和从业者社区的专家，包括来自相关公司、大学、联邦机构的代表、国家实验室和美国制造研究所。该研讨会的动机是解决先进制造中对制造数据的关键需求，这是之前研讨会系列的一个重要发现，该系列研讨会是在国家科学和技术部先进制造小组委员会以及机器学习和人工智能小组委员会的主持下举办的。技术委员会。无法访问情境化、分类和可发现的制造数据被认为是智能制造和人工智能对美国经济的全部潜力的关键障碍。制造业没有许多其他行业发展起来的用于提高生产力的数据使用或交付基础设施。研讨会的目的是制定访问跨公司微电子生产数据的策略，同时保持专有数据的安全。这样的策略有望通过为机器学习研究人员提供充分表征的数据来提高美国微电子制造公司的生产力。这些数据需要创新新的机器学习架构，特别适合对制造过程数据进行分类。该研讨会的独特之处在于它专注于详细的行业数据，对这些数据的分析定义了关键的业务和技术决策。该研讨会的独特之处还在于强调更广泛的数据科学和计算机科学观点，其结构和形式有助于建立跨社区的观点和兴趣。研讨会将从个人社区讨论开始，以分享立场和理解词汇。这些活动将发展成为一系列跨社区虚拟圆桌会议，让制造和 AL/ML 研究人员与微电子行业的利益相关者共同定义具体的业务和技术问题。这些成果将在随后在华盛顿特区举行的现场会议上共同讨论。面对面会议将：(1) 定义并商定利用当前技术和/或定义新方法需求促进大规模协作数据共享和模型构建的机制，(2) 构建行业、学术和政府合作，(3)制定微电子制造行业跨公司数据聚合行动计划草案。虚拟会议和现场会议将包括专业作家，协助组委会做笔记并合理化每次会议的调查结果，以指导其余会议的议程。现场会议之后将举行所有参与者都参与的虚拟一般审查和评论会议。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力优点和更广泛的影响审查标准进行评估，被认为值得支持。