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In the modern semiconductor industry, defective products occur with unexpected small variables due to process miniaturization. Managing the condition of each part is an effective way of preventing unexpected errors. The industrial internet of things (IIoT) environment, which can monitor and analyze the performance degradation of parts that affect process results, enables advanced process yield management. This paper introduces the IIoT concept-based data monitoring and diagnostic system construction results. The process of pump vibration data acquisition is explained to evaluate the effectiveness of this system. The target process is deposition. The purpose of the system is to detect degradation of pumps due to by-products of the atomic layer deposition (ALD) process. The system consists of three areas: a data acquisition unit using six vibration sensors, a Web access-based monitoring unit that can monitor vibration data, and an Azure platform that searches for outliers in vibration data.

Industrial Internet of Things for Condition Monitoring and Diagnosis of Dry Vacuum Pumps in Atomic Layer Deposition Equipment