Dynamic AI Computation Tasks with SECS/GEM in Semiconductor Smart Manufacturing

Abstract

Semiconductor manufacturing has data management systems comprising multiple layers, including the cloud layer, the edge layer, and the equipment or device layer, which perform different functions in the system. The equipment layer performs data monitoring and detection of faults-the cloud layer and the edge layer help perform computational tasks. Performance of the computational tasks at the equipment layer is beneficial because they help achieve real-time response to the production and reduce the delays caused by data transfer from the equipment layer to the edge or cloud layer. In semiconductor manufacturing, the host computer located at the edge layer communicates to the equipment through Secs/Gem communication protocol. According to the results from our experiment, it is more efficient and effective to perform data analysis at the equipment level. This paper proposes a new Secs/Gem protocol for performing dynamic AI tasks on the equipment. The protocol allows the host to dynamically assign tasks of analyzing data to the equipment, and the equipment reports the results back to the host.