Prognostic Health Management (PHM) utilizes data mining and analytics to detect early machine abnormalities from data inputs, be it vibration, temperature, partial discharge (PD), etc., so that you will have a clear picture of what is wrong with your equipment, find associations, patterns and determine the root causes long before it fails. Using various algorithms like clustering, neural networks, statistics to develop models for equipment health analysis so that early warning can be triggered and appropriate action taken expeditiously.

BENEFITS

• Early warning based on various parameters affecting equipment condition instead of current practise.
• Finding association and patterns which are not so clear
• Web-Based System
• Low cost, high returns based on subscription ( 1yr onwards)
• Historical data crunching from as long as 10 years ago.
• Decision making based on impact assessment
• Aging based on benchmarking; local and industry wide
• Data input is managed and controlled by you