Category - Maintenance Analytics Summit 2019

Chairman's Opening Remarks - Diego Galar, Luleå University of Technology

Maintenance Analytics Summit 2019

Chairman’s Closing Remarks – Diego Galar, Luleå University of Technology

Closing Remarks by the event chairman of the Maintenance Analytics Summit, Diego Galar, Professor at Luleå University of Technology

Maintenance Analytics Summit 2019

Journey to Production Value from Data & AI in Asset Intensive Industry – Henrik Göthberg, Dairdux

Insights what it takes and what works to become Data and AI Ready (DAIR) – A strategic, middle manager and operational perspective. The presentation will explore: The strategic and tactical challenges to become DAIR for...

Maintenance Analytics Summit 2019

So you have started your AI program, What now! – Ray Hall, Arundo Analytics

Many companies have started their digitalisation/AI program but have yet to see the value they expected. The Arundo presentation shares their view on what companies have been doing and what an alternative approach may...

Maintenance Analytics Summit 2019

Semantic Modelling of Big Industrial Data for Predictive Maintenance – Dimitris Kiritsis, EPFL

The degradation of functional components of engineering assets represents the main need for predictive maintenance. Degradation is also a major sources of product defects. The Industrial Internet of Things and...

Maintenance Analytics Summit 2019

Sustainable Productivity in Final Assembly – Rickard Hansen, Atlas Copco

How can IoT and analytics support the final assembly process? What are the obstacles to overcome and how can you remotely support a process with both operator held and fixture devices. Key Takeaways The entry value to...

Maintenance Analytics Summit 2019

Implementing Industrial IoT Systems in High Risk IT Landscapes – Nikolaj Skov Purup, Ørsted

Industrial IoT (IIoT) systems is a key enabler for disruptive transformations for operators of heavy assets. Assets such as wind turbines or ships have lifespans of 30 years or more and thus, IIoT systems must co-exist...

Maintenance Analytics Summit 2019

Probabilistic Digital Twins: An Innovative Asset Integrity Maintenance – Arvind Keprate, DNV GL

The session will be expounding the role of probabilistic digital twins in asset integrity maintenance with primary focus on application of Bayesian Networks (BNs). An illustrative case study shall be performed...

Maintenance Analytics Summit 2019

Compressor Performance Monitoring: From Yearly to Continuous on a Screen – Marianne Ytterbø, ABB

Presentation of a joint innovation project between ABB and customers resulting in an online performance monitoring system for centrifugal compressors based on thermodynamic calculations and advanced integration of...

Maintenance Analytics Summit 2019

Data-driven Approach to Maintaining Airport Baggage Handling System – Lasse Vilhelmsen, Beumer Group

In this session I will focus on how to best understand, visualize and analyze data from a baggage handling system consisting of thousands of moving parts installed in a conveyor system several kilometers long. I will go...

Maintenance Analytics Summit 2019

Edge Analytics: How to Prepare Machine Data for Your ML Model – Göran Appelquist, Crosser

A common IoT scenario is collecting data from various sensors and devices. Often communicating with different protocols and setups. To be able to use that data, the user must normalize and prepare the data for further...

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Category - Maintenance Analytics Summit 2019

Chairman’s Closing Remarks – Diego Galar, Luleå University of Technology

Journey to Production Value from Data & AI in Asset Intensive Industry – Henrik Göthberg, Dairdux

So you have started your AI program, What now! – Ray Hall, Arundo Analytics

Semantic Modelling of Big Industrial Data for Predictive Maintenance – Dimitris Kiritsis, EPFL

Sustainable Productivity in Final Assembly – Rickard Hansen, Atlas Copco

Implementing Industrial IoT Systems in High Risk IT Landscapes – Nikolaj Skov Purup, Ørsted

Probabilistic Digital Twins: An Innovative Asset Integrity Maintenance – Arvind Keprate, DNV GL

Compressor Performance Monitoring: From Yearly to Continuous on a Screen – Marianne Ytterbø, ABB

Data-driven Approach to Maintaining Airport Baggage Handling System – Lasse Vilhelmsen, Beumer Group

Edge Analytics: How to Prepare Machine Data for Your ML Model – Göran Appelquist, Crosser

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