Preventing Asset Outage with Historical Data
Maximise asset performance, minimise asset costs
Creating predictive models to prevent asset outage
“Using historical data to create predictive models to prevent asset outage and identify dysfunctions early on.”
Your assets have a plethora of data collected and stored, ready for you to use to its best potential. Historical data from your assets can be of great value to identify dysfunctions and upsets early. But how do you use this data to optimise current processes and detect issues early so that you can improve asset integrity and availability?
In this webinar, we show you how you can use historical data and apply it to creating effective predictive models for your assets.
In the first 30 minutes we discuss:
- How historical data, stored in your process historians, can be turned into value
- What data you need to build real-time condition monitoring and predictive solutions
- What process you should follow to achieve results
- How you can deploy your findings on real-time (streaming) data
The webinar session is followed by a 20-minute Q&A session.
Jules Oudmans is one of the co-founders of UReason, a provider of technology products and services enabling companies to quickly create intelligent applications that automate complex reasoning on large quantities of real-time data and events. Jules is a seasoned professional active in the field of operational intelligence and real-time analytics.
He has set vision and supported early adaptors and co-visionaries in Oil & Gas, Petro(chemical), Utilities, Pulp & Paper, Defense and Telecom industries at companies such as Halliburton, BP, Motorola, Siemens, Shell, Cargill, Lyondell and BG/Transco.
Jules has a broad range of experience in consultancy, project development and project management roles for customers and prospective customers, throughout Europe, the Middle-East and North America.