Using Data to Make Maintenance More Predictable
Maximise asset performance, minimise asset costs
The Power of Predictive Analytics
Leading companies are leveraging real-time condition based and predictive maintenance solutions to prevent equipment failures, optimize processes, increase availability and reduce maintenance costs.
In this webinar, we will explain how on the basis of the data available from your assets and processes you can create data driven maintenance solutions that create immediate insights.
In the first 40 minutes, we discuss:
- A working project flow for APM projects
- How to select the critical assets and non-conformities
- What data to collect from which systems
- How to choose the most fitting asset failure models
- How to deploy these data driven maintenance solutions
The webinar session is followed by a 20-minute Q&A session.
“Using APM-Studio we were able to easily set-up asset monitors that continuously monitors if we expose our critical assets (pumps/furnaces) to integrity limits. We not only have a real-time insight into the risk but also the likelihood of unwanted events enabling us to be in better control.”
Maintenance Manager, Refinery.
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.