IoT enabled intelligent fleet management. Moving from reactive to predictive maintenance, By Kalman Tiboldi - Chief Business Innovation Officer @ TVH
Internet is no longer just a global network for people to communicate with one another using computers, but it is also a platform for devices to communicate electronically with the world around them. The result is a world that is alive with information as data flows from one device to another and is shared and reused for a multitude of purposes. Harnessing the potential of all of this data for economic and social good is one of the primary challenges and opportunities. IoT enabled data driven predictive maintenance is becoming relevant in all the major industries as it can drive efficiency by providing higher levels of safety and quality at a fraction of the current costs. Thanks to Big Data, Analytics and IoT devices, predicting potential failures is going to be a real capability…but what happens after a failure is predicted, the need for maintenance is detected or a part replacement is required? Even if you can predict failures, dynamic technician scheduling associated with equipment maintenance management requires insight into real-time held inventory, technician location and estimated service completion time. Establishing an ecosystem where customers, equipment producers, service companies and all other digital service providers can collaborate is the right answer.
During the session I will explore these aspects and more, including:
How to improve quality and service by predicting malfunctions before they cause unscheduled downtime and higher costs?
• - Which are the key challenges to implement an IoT enabled predictive maintenance?
• - How to build a layered architecture for Sensing, Communication, Service and Infrastructure?
• - How predictive maintenance requires a two-step data analytics?
• - How IoT help us to implement a transformational business models like performance-based or pay-per use billing?
About Kalman Tiboldi: Kalman Tiboldi is the Chief Business Innovation Officer of TVH, worldwide market leader in replacement parts for material handling and in-plant industrial vehicles and has over 35 year experience in using information technology for business process innovation. Kalman merged IT and Business in a new department called Business Innovation through IT (BI²T) and managed to promote the collaboration between IT and Business as driving force behind innovation. With his team he has successfully implemented a flawless IT infrastructure with flexible applications, based on service-oriented architecture, turning TVH into a real-time, extended enterprise.
Providing the leadership and direction towards the development and implementation of information systems, Kalman is taking advantage from Cloud-based Services, Big Data and Internet of Things and strongly support Open Source solutions. Kalman holds a Civil engineer polytechnician degree from Military Technical Academy of Bucharest and a Master of Mathematics and Computer Science degree from University of Bucharest.
He was named IT Manager of the Year’ – Large Organizations in 2004 and 2011 by Leading European Trade Publication, Data News.
Predictive Analytics, By Prof. Dr. Mannens - Research Manager @ iMinds
Although Predictive Analytics has been around for a while, it is still a field of research. In this talk, Prof. Dr. Mannens will explain the current state-of-the-art as well as the main challanges & pitfalls when it comes down to setting up a predictive analytics project.
About Prof. Dr. Mannens: Erik Mannens is Professor @ MMLab's KNoWS group / Research Manager @ iMinds Media Technologies Dept. / experienced Project Manager @ iMinds - MMLab (formerly known as IBBT) since 2005 where he has successfully managed +30 projects. He received his PhD degree in Computer Science Engineering (2011) at UGent, his Master’s degree in Computer Science (1995) at K.U. Leuven University, and his Master’s degree in Electro-Mechanical Engineering (1992) at KAHO Ghent. Before joining iMinds-Ghent University-MMLab in 2005 as research manager, he was a software engineering consultant and Java architect for over a decade. His major expertise is centered around metadata modeling, semantic web technologies, broadcasting workflows, iDTV and web development in general. He is involved in several projects as senior researcher and just finished up his PhD on Semantic News Production; he was co-chair of the W3C Media Fragments Working Group and actively participating in other W3C’s semantic web standardization activities (Media Annotations, Provenance, Hydra, Linked Data Platform, and eGovernment).
Networking with New Year's drink
Location: co.station, Parvis Sainte-Gudule 5, 1000 Brussel
Date & Time: 8th of February starting at 19h00.
Organized by Internet of Things Belgium VZW & 3IF Industrial Internet Consortium Flanders
Registration is based on personal invitation only!
In case you received a personal invitation for the "Predictive Maintenance Seminar". Please confirm your presence by registrating below.
You can bring one extra collegue to the seminar. This collegue needs register as well.