Online temperature monitoring system for semiconductor automated test equipment using local Gaussian process

Accurate temperature monitoring in automated test equipment (ATE) is crucial for ensuring the reliability and quality of semiconductor testing. However, ATE temperature models often rely on noisy, sparsely-sampled sensor data, and existing methods struggle to update models efficiently as operating conditions evolve. This paper presents Neighbor-Pseudo-GP, a probabilistic online method for modeling the temperature distribution of an ATE board. Our approach uses a Gaussian process (GP) to represen