Initially slower to catch up with the data-driven transformation, the heavy-asset industry has certainly accelerated the adoption of predictive analytics systems that provide multiple maintenance advantages such as fewer outages and breakdowns, extended lifecycle of the assets and equipment, better plant safety, and enhance the overall quality of operations and supply chain processes.
This week, we had the pleasure of hosting the 3rd edition of the Maintenance Analytics Summit, the first time in a virtual setting. Traditionally PdMA Summit brings together maintenance professionals, experts, practitioners, and enthusiasts who are eager to learn from the latest and most innovative methodologies, tools and case studies in data-driven maintenance and advanced data analytics.
On Tuesday, we are opening up the 3rd edition of the Maintenance Analytics Summit where attendees will have a chance to follow online presentations by some of the esteemed experts in predictive maintenance, condition-based monitoring, IIoT, asset lifecycle management and Advanced Data Analytics.
In the previous article, we introduced some of the topics and presentation that were discussed at the very inception of the Maintenance Analytics Summit.
We are just a few days away from the third edition of the Maintenance Analytics Summit. The inaugural Maintenance Analytics Summit took place in 2018 as a response to the need for a platform where experts can present and discuss innovative case studies on data-driven maintenance in the heavy asset and manufacturing industries.
We are honoured to welcome Renato Magliacani and Federico Puccetti from Baker Hughes as presenters at the virtual edition of the Maintenance Analytics Summit.
The digital twin bridge the gap in complex assets between OT systems and the IT environment by capturing data to monitor performance, deterioration and failure, location and safety compliance and remote monitoring systems for scheduling and asset utilisation.
Boris Volavicius in his interview talked to us about the benefits of IIoT, some challenges that are still to be tackled and his prediction for the industry.
Diego Galar, Professor of Condition Monitoring in the Division of Operation and Maintenance Engineering at LTU, Luleå University of Technology, is bringing in the most advanced views from the academic and research field when it comes to Industry 4.0 and industrial AI.
One industry that abundantly reaps the fruits of AI innovation is without doubt manufacturing. AI has proven to be a real game-changer for the heavy asset and manufacturing industry.
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