General Framework for Processing Time Prediction and Machine Availability for all Fab Equipment

The work here has been published during the 2025 version of the annual Advanced Semiconductor Manufacturing Conference (ASMC). You can read the abstract below, to read the full paper please fill in the information in the form on this page.

ABSTRACT

This paper presents a novel approach that significantly improves processing time (PT) and machine availability predictions across all tools in a GlobalFoundries semiconductor fabrication plant. An attention-based deep neural network was developed to enhance prediction accuracy. The model achieved a 50% to 80% reduction in Mean Absolute Error for PT and machine availability predictions, compared to a baseline statistical model. Deployment on three bottleneck tool families led to a 3% to 7% improvement in chamber utilization. The model is being expanded to all GlobalFoundries’ facilities, with expected similar outcomes.