A combination of artificial intelligence, statistical methods and thermodynamics analysis are used. ProcDNA’s hybrid architecture makes use of independent methods to analyze data and to detect anomalies in critical assets of any industry. Advance warnings given by ProcDNA help in significant reduction of forced outages.
ProcDNA uses SimTech’s IPSEpro thermodynamic engine to analyze thermal performance at component level, as well as plant level. “First principles/thermodynamic models” are used to perform mass and energy balance across equipment and provide expected value of the performance to quantify and detect reasons behind degraded performance. Such models are built using design information, HMBD, P&IDs, Correction curves, PG test information and steady state operating data.
With ProcDNA, centralized monitoring of health and reliability of critical assets becomes easy and inexpensive. Results of the analysis can be exported to InDB historian and can also be used to trigger notifications (email, SMS, etc.) for any required maintenance actions.
Our software and solutions are designed to store and analyze data for various types of anomalies in all critical equipment in real time. This capability helps reduce forced outages.
Our software suite is for fleet owners with diverse portfolios, as they can be configured to monitor live data on a continuous basis. They can identify equipment anomalies, process anomalies, data and sensor anomalies in all critical assets, in addition to highly accurate component level thermal performance analysis of all major equipment.