Emerging Paradigms in VLSI and Semiconductor Manufacturing Leveraging AI-Driven Process Control and Defect Detection Techniques
Keywords:
Artificial Intelligence, VLSI, Semiconductor Manufacturing, Process Control, Defect Detection, Machine Learning, Reinforcement LearningAbstract
The advent of artificial intelligence (AI) has catalyzed transformative shifts across various sectors, including very-large-scale integration (VLSI) and semiconductor manufacturing. This paper explores the emerging paradigms driven by AI in process control and defect detection, which are pivotal to sustaining advancements in semiconductor technology. AI-driven methodologies have enabled enhanced yield, reduced downtime, and superior defect mitigation, ushering in unprecedented precision and scalability. This research paper reviews state-of-the-art literature, highlights emerging trends, and discusses the methodologies and challenges associated with AI integration in semiconductor manufacturing. Furthermore, it presents a comparative analysis of traditional and AI-driven approaches while identifying future research trajectories that promise to redefine semiconductor production.
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Copyright (c) 2025 Juan M. Larrosa (Author)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
