ITEA SMART-PDM project organises session on “Predictive analytics architectures and applications for industrial systems – 2nd edition” during IECON 2022
Organisations are continuously researching new strategies to improve the Overall Equipment Effectiveness (OEE) of their equipment. Particularly, maintenance costs can vary between 15% and 70% of production or ownership costs, making maintenance an important cost to be reduced. This is now possible due to the high levels of automation and, particularly to innovative IoT solutions. The ITEA SMART-PDM project offers a smart predictive maintenance approach based on cyber physical systems, acquiring manufacturing data to provide diagnosis and prognosis information while rendering the underlying technology financially feasible.
On 18-21 October, SMART-PDM will organise the 2nd edition of the “Predictive analytics architectures and applications for industrial systems” session, during the 48th Annual Conference of the IEEE Industrial Electronics Society (IECON 2021, 18-21 October 2022, Brussels, Belgium). This session will address the main problems of designing industrial maintenance systems, from the collection of data from sensors to its analysis supported by advanced algorithms. All kinds of maintenance paradigms will be targeted, from reactive to predictive and prescriptive, or any other kind of advanced maintenance concepts, with a strong focus on architectures and design. Next to providing an excellent opportunity for SMART-PDM partners to present their results emerging from the project’s 12 use cases linked to predictive maintenance, the session is also an ideal meeting point for other projects along in the domain of predictive maintenance and smart manufacturing in ITEA or other international research and innovation programmes.
SMART-PDM welcomes high quality papers to the “Predictive analytics architectures and applications for industrial systems – 2nd edition” session, which is supported by the IEEE-IES Technical Committee on Industrial Informatics (TC-II), from industry and academia. Topics of interest include, but are not limited to:
- Architectures for predictive analytics applications
- Industrial applications and pilots on emerging maintenance techniques
- Sensors and Cyber Physical Systems for maintenance applications
- AI based control systems in advanced production
- Prognostic and Health Management (PHM) / digital twin / condition monitoring
- Machine learning algorithms
- Signal analysis algorithms for maintenance applications
- Diagnosis & Prognosis & Remaining useful life
- Maintenance safety
- New frontiers: Machine as a service, maintenance as a service and reliable manufacturing
The paper submission deadline is on 8 May 2022.
Interested parties can send their contribution to: Luis Lino Ferreira (llf@isep.ipp.pt), Barış Bulut (baris@enforma-tr.com), or Goreti Marreiros (mgt@isep.ipp.pt).
