Abnormality prediction of production equipment

We will assist in building a system that analyzes time series data obtained from sensors on production equipment to predict abnormalities and failures.

The era of "IoT" is upon us, where various sensors are connected to devices and equipment, and the data obtained there is analyzed by AI and utilized in management. With the technology for predicting abnormalities in production equipment, the manufacturing industry can now collect and analyze sensor data installed in factory production equipment using IoT technology, allowing for the early detection and response to equipment troubles, thereby avoiding risks and increased costs due to equipment downtime. 【Expected Issues】 - Equipment on the critical path must not break down, so inspections and parts replacements are frequently conducted, but this may be excessive. - It takes time to determine the causes when a failure occurs. 【Expected Effects】 - Reducing excessive maintenance through maintenance based on the degree of abnormality of the equipment. - By estimating abnormal causes with the anomaly detection model, time can be saved in the procurement and preparation of repair parts.

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