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  5. Document and Data Management
  6. Numerous hiring achievements towards DX! Real-time data management system.

Numerous hiring achievements towards DX! Real-time data management system.

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last updated:Mar 25, 2025

宇部情報システム
宇部情報システム
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Adopted by many companies worldwide! Accelerating DX using highly reliable operational data!

The "PI System" is a real-time data management system designed to visualize and share operational data (such as production results, quality information, and equipment utilization rates) in real time. It is widely used in industries such as electricity, gas, oil, chemicals, and manufacturing, serving as a platform to collect and utilize time-series data from various equipment and sensors, and has been adopted by many companies worldwide as a global standard. At Ube Information Systems, we support our customers' digital transformation based on our long-standing experience in developing infrastructure for group companies and utilizing collected data related to this system. 【Features】 ■ PI Interface: Supports over 450 types of data sources Capable of collecting time-series data from vendor systems, assets, and sensors ■ PI Data Archive: Compresses and stores data Enables long-term data storage and quick data retrieval ■ PI Asset Framework: Associates data with equipment as a key Provides "information" that anyone can easily use *For more details, please refer to the PDF materials or feel free to contact us.

    Document and Data Management
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Numerous hiring achievements towards DX! Real-time data management system.

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  • Related Link - https://www.uis-inf.co.jp/iot/pi/

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【Other Features】 - The sensor data is compressed using PI's unique method and stored in a database, allowing only necessary data to be saved and IT resources to be conserved. - Utilizes a data archiving system developed by OSIsoft, which has a proven track record of long-term continuous data accumulation over several decades. - Sensor data can be linked around assets (equipment) and stored in the database without the need for special programming. - Assets can be managed hierarchically, allowing for the retrieval of aggregated values at each level, such as by factory or department. - Computational functions (PI Analysis Service) can be used to perform calculations using sensor data. - Calculation results can be registered in the database and treated similarly to data obtained from sensors. - As an Excel add-in, accumulated data from the PI System can be imported into Excel, enabling data processing using Excel functions. - Real-time data, equipment data, and analysis results can be visualized through a web browser. *For more details, please refer to the PDF document or feel free to contact us.

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Real-time data management system "PI System"

Real-time data management system "PI System"

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Abnormal Signal Detection System Construction Service [SAILESS] Service Introduction Materials

Abnormal Signal Detection System Construction Service [SAILESS] Service Introduction Materials

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Case Studies of the Abnormal Signal Detection System Construction Service "SAILESS"

Case Studies of the Abnormal Signal Detection System Construction Service "SAILESS"

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[6/7 Seminar] Early Detection of Equipment Troubles with No Prior Experience - AI-based Anomaly Prediction Without the Need for Abnormal Data - Ube Information Systems

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In building an anomaly detection system using AI, there are various barriers such as "no abnormal data," "lack of accumulated big data," and "uncertainty about the construction process." Additionally, even after construction, issues like "high false positives" and "not being used on-site" tend to arise. The "Anomaly Detection System Construction Service" we are introducing this time provides a comprehensive service from preliminary analysis to utilization support, tailored to fit the needs of various manufacturing sites and customers for building AI systems. It can be constructed even without abnormal data or accumulated big data, and it can detect troubles that have not been experienced in the past. In this seminar, we will cover key points for constructing an AI anomaly detection system, including: - Data preparation and preprocessing - Elimination of the need for skilled maintenance techniques - Algorithm selection - How to trigger alerts This seminar is especially recommended for those who are considering building an anomaly detection system using AI but are unsure about how to implement it concretely. Since it is a web seminar, please feel free to join us.

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宇部情報システム

宇部情報システム

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Our company was established in 1983 to develop the information systems department of UBE Corporation, which operates in a wide range of fields including chemicals, construction materials, industrial machinery, and energy. We have extensive experience not only in managing functions unique to the manufacturing industry, such as research and development, design, production, and quality control, but also in building and operating information systems for procurement, sales, logistics, accounting, and human resources. Some of these are offered as system products (packaged software).

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