A Smart Predictive Maintenance Approach based on Cyber Physical Systems (SMART-PDM)

ITEA3 Project 17041.

Manufacturing accounts for 15.96% of EU GDP (World Bank), is undergoing immense yet gradual Industry 4.0 transformation with the help of advancements including predictive maintenance, whose market size is estimated to be worth USD 4.9b by 2021 (Markets and Markets).

SMART-PDM’s objective is to acquire manufacturing data to provide diagnosis and prognosis information while rendering the underlying technology financially feasible.

In order to achieve this goal, we created a very complementary and conducive consortium with 12 use case demonstrators ambitious to see the trial results, 9 integration & tools providers and 9 technology and knowledge providers all waiting to test out and further improve their technologies, all with a balanced breakdown of 11 SMEs, 10 Large Enterprises and 4 RTOs which are spread across 5 countries.

The participation of ISEP is led by members of the SoftCPS laboratory, being leader of WP3 (Model Analysis (Dynamic and static)) and working in the propagation of trace information into models, enabling model-based analysis of non-functional properties.

SMART-PDM is an ITEA3 Project, funded by national agencies in Turkey, Finland, Spain and Portugal.

The participation of ISEP is led by members of the SoftCPS laboratory, working in publish-subscribe middleware for connecting physical data with the cyber-world.

Website: https://smart-pdm.eu/

Budget: 7.5 M€ (Total), 244 K€ (ISEP)

Period: December 2018 to December 2021

SoftCPS Responsible: Luis Lino Ferreira

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