Paper Contents
Abstract
For years, data analytics and artificial intelligence (AI) have been a disruptive innovation among today's competitive semiconductor industry players, actively transforming traditional manufacturing processes and design paradigms. Semiconductor companies are also embracing machine learning (ML) and AI software tools with the aim of optimizing production flows, reducing downtime, improving product quality, and providing opportunities for innovation. To that end, these techniques are surveyed for applications in semiconductor companies, and the importance of applying them to improve production performance, yield optimization, and process innovation is elaborated. Semiconductor companies can predict failures, monitor equipment performance in real time, and design next-generation integrated circuits more efficiently and with reduced power. Here, advanced ML models and AI-based decision support systems are used. Further, the study describes leadership methodologies within semiconductor companies. It compares analy
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Copyright © 2025 GOWTHAM V. This is an open access article distributed under the Creative Commons Attribution License.
