© SelSus Consortium
various environmental impacts, and fluctuating production volume. Additionally, the cost
pressure increased significantly, due to increasing suppliers. Along with this, to enable
availability of production equipment and by that establish a high level of ability to deliver
within supply-chain considering low level of inventory and buffer stock, just ensuring
relative high level of reliability and availability at production level is not sufficient.
The European Union significantly supports industry, suppliers, research institutes and
universities in facing this challenge to manage the switch to digitalization of the
production, comprising component, equipment, and entire line and considering the entire
life-cycle starting from planning phase, down to ramp-up, production, and re-use.
With new and advanced machines, fixtures and tools, comprising extended sensor
capabilities, smart materials and ICT self-diagnosis and self-awareness will be enabled
within SelSus project and will also prove self-healing capabilities
Additionally, distributed diagnostic and predictive and renovation models will be an
integrated part of smart devices, enabling prognosis failure modes, component
degradations, and by that predict future downtimes of devices.
These goals are reflected in the work packages and milestones, focusing on conversing
vision into real working machines and production lines. As one of the key objectives within
SelSus, data will be gathered, transformed into information and knowledge, and by that
may offer an added value to supplier and end-to-end-user using self-diagnosing and self-
Sensor networks, built up of a variety of sensor nodes, will add the capability for
distributed analysis, interoperable and delay-tolerant communication.
Integrated models and methodologies for predictive maintenance will enable constant
life-long assessment, by forecasting degradation and deterioration trends of single
components and equipment. Additionally, machine learning and data mining techniques,
combined with discrete material flow simulation models will enable decision models, on
how to anticipate unforeseen future malfunctions and downtimes.
These methodologies will be proofed and demonstrated on three different levels, which
are device level, equipment level, and factory, respective line level.
As scheduled, one integrated task will be, to disseminate publishable results. Additionally,
to website, Linked-In account, flyers, etc., the consortium organized a Smart Factory
Workshop to directly communicate goals and results to industry and universities.
+49 711 970 1864
Main contact person:
Roland Wertz (until 31
The University of Nottingham
Main contact person: Milena Radenkovic
+44 115 84 67670
The Manufacturing Technology Centre
Main contact person: Lina Huertas
+44 24 7670 1678
Main contact person: Dr. Michael Peschl
Electrolux Italia S.p.A.
Main contact person: Alessandro Mazzon
+39 0434 396044
Main contact person: Dr. Philipp Dreiss
+49 711 699 20000
IEF Werner GmbH
Main contact person: Ulrich Werner
+49 7723 925 154
Advanced data processing GmbH
Main contact person: Knut Voigtländer
+49 351 2044990
GAMAX Számitástechnikai Kft
Main contact person: Gabor Horvath
Hugin Experts AS
Main contact person: Anders Madsen
+45 2012 5568
Main contact person: João Reis
Ford Motor Company Ltd.
Main contact person: Peter McIntyre
+44 1268 402223
Main contact person: Axel Bindel
Main contact person: Barry Auty
+44 7871 325100
Main contact person: Niels Lohse
+44 1509 227625