Industrial data technology of iEM System intelligent platform, applies to the continuous online evaluation on health condition of utility equipment, and timely detection of impact equipment health and performance change point, so as to provide guidance for the efficient and stable operation of equipment.

Equipment Online Health Assessment

iEM System intelligent platform mines equipment mass historical data and creates models to achieve real-time quantitative assessment of online health status of equipment. iEM System intelligent platform for using the industrial data modeling technology, changes the binding mode of upper and lower limit alarm view device status through a single parameter, creatively uses a healthy similarity curve that integrates equipment association parameters and the rules of historical operation and real-time evaluates the changes of equipment between the current state and history state of the security and optimization.

Early Warning & Diagnosis

iEM System intelligent platform equipment online health technology assessment, early warning and diagnosis equipment for a potential failure, early detection of potential accidents so as to prevent in the bud. From the relatively passive post fault management mode, it is changed into a more proactive fault prediction and prevention model in advance. iEM System intelligent platform, which uses the industrial big data modeling technology, can provide the accurate early warning of the potential gradient fault from 14 days to more than 120 days.

Energy Consumption Analysis, Prediction & Optimization

Build analysis prediction optimization model of high energy consumption equipment by using iEM System intelligent platform to achieve real-time monitoring of energy consumption changes and early warning. By modeling the industrial data of the production process and set off for the online prediction of energy consumption survey, and under the premise of safety, realize the maximization of energy utilization.


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Tel:010-82737780 81717788


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No.8 Xueqing Road, Haidian District, Beijing, China

P. O. Box:100192




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