Faculty, Arizona State University
Optimizing semiconductor production with AI-driven maintenance predictions will boost reliability, cut downtime and supercharge production.
Program: FURI
Building a model to output the estimated probability of satisfying build criteria is essential for medium area additive manufacturing development.
Analyzing semiconductor testing data allows for awareness regarding the quality of production, leading to opportunities for improvements.