Easily identify data items highly related to abnormal signs using AI technology. Achieve automation of advanced failure prediction and abnormal sign detection utilizing equipment operation data.
Case study of the introduction of an equipment diagnosis system utilizing AI technology from Company A in the chemical manufacturing industry. The company had previously conducted equipment diagnosis through numerical management and remote operation, but faced challenges due to the speed of human judgment and the increased burden from the growing number of monitoring targets. Therefore, they implemented MainGATE/MSPC equipped with Fujielectric's AI technology, achieving automation of abnormal signal detection. This enabled rapid detection of abnormal signals and advanced failure prediction.
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basic information
Related products: MainGATE/MSPC With over 550 implementations primarily in the manufacturing industry, it is used for improving processing accuracy through diagnosis and analysis of manufacturing processes, enhancing quality yield through diagnosis and analysis of manufacturing processes, ensuring process quality through application in medical device quality judgment, stabilizing production volume, and detecting abnormal signs through monitoring of refrigeration systems.
Applications/Examples of results
[Challenges Before Implementation] - While numerical management and remote operation were possible, decisions were made by people based on the data, which necessitated data monitoring to prevent delays in judgment. - As the number of monitoring targets increased to check the values of various locations and equipment, the processing load on personnel also increased. [Effects of Implementation] - The diagnosis of abnormal signs in equipment can now be performed quickly on a per-device basis. - It has become possible to narrow down data items that are highly relevant to abnormal signs, thereby reducing the processing load. - A system was implemented to trigger alarms when abnormal signs occur, achieving advanced failure prediction.
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Case Study: Detection of Abnormal Signs Using Equipment Diagnosis System
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Company information
Providing solutions for various plants and factories such as food, chemicals, oil and gas pipelines, paper and pulp, and cleaning facilities. Our measurement and control systems have over 40 years of history since the launch of the first distributed control system in 1975. Based on our track record, we propose systems and solutions to support the latest technologies, IoT utilization, and the development of smart factories. - Steam generation heat pumps / waste heat utilization / visualization of thermal energy - Clamp-on steam flow meters / flow meters / flow sensors / thermal balance analysis - Industrial furnaces / electric furnaces / high-frequency induction furnaces / IGBT power supplies - Gas analyzers / gas measurement devices / gas analysis sensors - Predictive maintenance / anomaly detection maintenance / preventive maintenance / maintenance and prevention systems / smart security - Smart factory - MES / DCS / SCADA / edge controllers - EMS / energy management systems / visualization of energy - Smart glasses / remote work support systems - Multivariate analysis / MSPC - Engineering tools
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