Session 1: Tuesday 17 November 2020, 13.30-15.30
Chair: Yves Keraron
Scheduling predictive maintenance with production tasks: A steel industry case study, Nikolaos Nikolakis Lms - University of PATRAS, Xanthi Bampoula, Kosmas Alexopoulos
How Data Models Can Contribute to Linking Real-Life Assets with their Digital Twin – A Case Study in Predictive Maintenance. Moritz von Stietencron, BIBA, Karl Hribernik, Biba, Klaus-Dieter Thoben, Biba
Ontologies combining design semantics and semantics used in operation and maintenance: Feedback from EDF power plants case studies, Dourgnon Anne - EDF, Antoine Alain - Université de Lorraine, Samba Mansor - ATOS Sénégal
Maintenance terminology standards: some issues and the need of a shared framework for interoperability, Yves Keraron - ISADEUS, Antoine Despujols - AFIM/EFMS
Session 2: Tuesday 17 November 2020, 16.00-17.30
Chair: Yves Keraron
Panel Discussion.
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The papers to be presented are as follows:
Scheduling predictive maintenance with production tasks: A steel industry case study - Nikolaos NIKOLAKIS corresponding author LMS - University of PATRAS, (nikolakis@lms.mech.upatras.gr), Xanthi BAMPOULA, and Kosmas ALEXOPOULOS
Abstract: Production scheduling is essential for a production system, prescribing when and where each operation necessary to manufacture a product will be fulfilled. Interruptions in the production process, both planned and unplanned, may result in reduced productivity. Predictive analytics however estimating the failure probability of a certain production asset can create insight and consist another factor for production scheduling. This study investigates an approach for combining predictive analytics with a scheduling system. The proposed framework, a result of the SERENA project, is evaluated in a use case coming from the steel industry.
How Data Models Can Contribute to Linking Real-Life Assets with their Digital Twin – A Case Study in Predictive Maintenance - Moritz von Stietencron, BIBA - Bremer Institut für Produktion und Logistik GmbH, Hochschulring 20, 28359 Bremen, Germany (sti@biba.uni-bremen.de), Karl Hribernik, BIBA, (hri@biba.uni-bremen.de), Klaus-Dieter Thoben, BIBA, (tho@biba.uni-bremen.de)
Abstract: The basic concept of a digital twin as widely used mandates the existence of an original counterpart – most commonly dubbed as “real” – which is represented by the digital instance. Subsequently, this co-existence of the real and digital twins poses a continuous interoperability issue between the physical and digital world. While in theory, the mapping of e.g. physical to digital properties is trivial, in practice, it usually is not. This paper presents a case study on how this interoperability problem can be addressed by the use of a unified data model for predictive maintenance applications, which has been developed in the EU-funded innovation action UPTIME.
Ontologies combining design semantics and semantics used in operation and maintenance : Feedback from EDF power plants case studies - Dourgnon Anne - EDF, quai Watier, 78400 Chatou (anne.dourgnon@edf.fr), Antoine Alain - Université de Lorraine (alain.antoine@univ-lorraine.fr), Samba Mansor - ATOS Sénégal, Sacré Coeur 3 Pyrotechnie, Dakar (mansorsamba@gmail.com )
Abstract: Usual langage pratices of industrial maintenance are rather different from whose used during power plants design. Maintenance is part of O&M (Operation & Maintenance) whose concepts are more “operational” than the ones of design phases. We propose here to question these practices for a better understandabilty between these semantic fields. As coresearchers, we investigated, questionned and rephrased. This inquiry offers food for thought, theoretical but also pratical. The role of ontologies is also questionned. The case studies are from EDF power plants.
Maintenance terminology standards: some issues and the need of a shared framework for interoperability - Yves Keraron - ISADEUS, 21 rue Rollin, 75005 Paris, (yves.keraron@isadeus.fr) and Antoine Despujols - AFIM/EFMS (antoine.despujols@free.fr)
Abstract: Terminology is the first critical point cited by practitioners when they are questioned on the need for standards. This paper gives a first analysis of maintenance terminology standards and highlights some discrepancies between the definitions and the meanings of the same terms. To homogenize the meanings of the terms and to achieve the highest benefit of digital technologies in industry, a shared framework is needed. This paper questions the possibility of such a framework and the conditions of its benefit for industry.
Panel discussion
The presentations will be followed by a panel which will highlight the value of new technologies used in predictive maintenance platforms for the management of industrial assets.
After the panel we will have a session of collective intelligence to get input for a structured roadmap of the Foresee Cluster, a grouping 6 H2020 projects of predictive maintenance if the factory of the future.