Assistant Professor University of Cincinnati Cincinnati, OH, United States
The proposed presentation will summarize the emerging challenges (at the process level, operation level, and enterprise level) in high-mix semiconductor manufacturing, see Figure 1, that were determined during the October 2022 Advanced Process Control Council meeting as part of a consensus building effort. Next, a list of needed technologies and infrastructures that might address these challenges is provided, focusing on technologies that might be enabled or enhanced by artificial intelligence / machine learning (AI/ML) capabilities. These technologiesare organized as Data Technology (DT), Analytical Technology (AT), Operation Technology (OT), and Platform Technology (PT). This process is important because understanding the technical challenges and needs is a prerequisite to manufacturers, equipment/materials vendors, and solution providers collaborating and developing solutions. Ultimately, the findings from this work will enable a technology development roadmap that advances high-mix semiconductor manufacturing and facilitates new standards, technology prototypes, and research consortiums in the U.S.A.
This effort is supported by the National Institute for Standards and Technology (NIST) through a project that aims to establish a U.S.A. roadmap for high-mix semiconductor manufacturing. A key component of the approach towards achieving this goal is to consult with experts in the semiconductor industry to determine the technical challenges in the semiconductor manufacturing ecosystem and specifically challenges faced by U.S.A. interests, and collect ideas on how artificial intelligence and machine learning (AI/ML) can play a role in providing potential solutions to address these challenges.