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10 April 2024 Leveraging AI in semiconductor process development
Meghali C. Chopra
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Proceedings Volume PC12956, Novel Patterning Technologies 2024; PC1295603 (2024) https://doi.org/10.1117/12.3012440
Event: SPIE Advanced Lithography + Patterning, 2024, San Jose, California, United States
Abstract
Semiconductor process development represents a tremendous opportunity for AI-based approaches which excel in automating routine tasks and recognizing patterns in data. With the right toolset, process engineers can leverage AI models in their day-to-day development. Nevertheless, several key technical challenges must be tackled to successfully implement AI in a semiconductor fabrication environment. For example, model requirements and desired learnings are vastly different when considering the needs of process engineers performing R&D, technology ramp, or high-volume manufacturing. Moreover, preservation of data security remains a pressing issue. Most AI models rely on large sets of data which cannot be shared between manufacturers. In this talk, we will review SandBox’s key innovations in these areas. We will cover critical applications for patterning, etch, and deposition unit process optimization and new opportunities for process co-optimization.
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© (2024) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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Meghali C. Chopra "Leveraging AI in semiconductor process development", Proc. SPIE PC12956, Novel Patterning Technologies 2024, PC1295603 (10 April 2024); https://doi.org/10.1117/12.3012440
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KEYWORDS
Artificial intelligence
Semiconductors
Data modeling
High volume manufacturing
Process engineering
Excel
Fabrication
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