Failure sign detection based on running data

    Detects differences between current operational data and past nominal operation data to detect system failure signs in advance. As a result, system availability is improved and losses of opportunity reduced. 
    • Energy
    Toshiba Energy Systems & Solutions Corporation
    October 27, 2020
    English, Japanese


    Problem Identification

    Emergency shutdowns due to failures have a tremendous effect on the operations of a power plant, not only losing power generation, but also require emergency repair. Power plant operators following the development and adoption of IoT technologies on a global scale have become increasingly interested in leveraging these technologies to reduce down time in their operating. However, if they usually manage to digitalized and gather a variety of data, its exploitation in order to improve efficiency of power plant operation is still a challenge.

    About the Service

    By building a model from the correlations between past data collected during nominal operations and comparing it with present data in real time, we have achieved that detecting differences with past behavior and predicting failures before they happen.

    This service is part of our Electric Power Business Platform. It can be freely combined with the other services on the platform.


    Customer Benefit

    Accurate prediction of when failures will happen allows planning for equipment down time and inspection, improving availability rates and reducing loss of opportunity.

    Why Toshiba

    1. Our experience as a plant manufacture allows us to build accurate models with the appropriate assets
    2. Real time visualization of the actual data and the values predicted by the model
    3. If necessary, clients can update the model on their own


    Screen Samples

    Comparison of actual measures with predicted values

    Screen of comparison of actual measures with predicted values


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