HanPHI,a predictive analytics solution,warns you of potential failures that can develop into catastrophic failures by comparing real-time data with expected data.

Empirical learning models calculate expected values based on past normal plant operation data and correlated equipment data.

HanPHI provides condition-based early warnings to prevent potential failures by analyzing plant sensor abnormalities,equipment issues,and abnormal operating conditions .

With HanPHI,you achieve systematic and condition-based predictive maintenance,reduce operating costs,and improve plant reliability.

1. Displays health index not only for the whole plant but also for each piece of equipment.

2. Shows the residual of the expected versus real-time value on-trend charts

(where you should be versus where you are).

3. Categorizes plant anomalies quickly based on warning levels.

4. Tracks the minimum index signal with the greatest impact on the decreasing equipment index.

5. Builds expected value models that are the basis of the early warning system.

6. Real-time monitoring of plant reliability through online or mobile devices.