Analytical and Machine Learning Models on Live Streaming Data
Maximise asset performance, minimise asset costs
Machine Learning Models in Maintenance
Machine learning models have proven to enhance the operations of a number of industries. Maintenance is not an exception.
In this webinar we will look at how you can deploy machine learning models that recognise asset and process degradations or failures early and how to connect and deploy these machine learning models to streaming data.
In the first 40 minutes, we discuss:
- Role of machine learning models in maintenance
- Exchange of predictive models produced by data mining
- Main machine learning algorithms and tools
- Model deployment and model management
- A step-by-step example
The webinar session is followed by a 20-minute Q&A session.
“Going from collected maintenance data to deploying predictive algorithms in APM Studio is straightforward. Predictive machine learning models support us in maintenance decision making by giving insights that help us continuously monitor the health of our assets. With machine learning models, we created efficient maintenance plans and minimsed the chance of unexpected failures, thereby reducing preventive maintenance activities that are not necessary”.
Maintenance Manager – Chemical company
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.