Intelligent Reliability 4.0 (iRel4.0)

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Reliability, electronic components and systems, harsh environments, prognostic and health monitoring.

Description of the project

The reliability of electronic components and systems (ECS) is a major industrial challenge: unexpected failures cause financial loss, loss of reputation, and can even lead to life-threatening situations. New types of sensors and new possibilities of communication make it now possible to use digital solutions to enhance the reliability of ECS.

In the iRel4.0 project, the goal is to improve the reliability of electronic components and systems along the entire value chain ranging from chip, packaging and at board and system level. The project follows a vertical, supply chain-oriented approach to execute research across the entire value chain. Electronic components and systems should become reliable more quickly, which means that the development processes can be transferred faster to production and also lead to an improved quality level through fundamental understanding of physical failure mechanisms and the use of Artificial Intelligence methods. The reliability must also be guaranteed when using the systems in new, safety critical and harsh environments, whereby new materials need to be used.

In this project, the research for AI and data science techniques and methodologies plays an important role, to allow extracting knowledge for prognostics and health monitoring purposes from data collected from electronic components such as boards, packages and chips. This data is used to understand, characterise and forecast the behaviour of the single components and their interactions.

The results will be validated in different application domains, such as automotive, energy and digital industry. In Belgium, the use case will be focusing on automotive and more particularly on researching a hybrid methodology for monitoring the health of fuel tanks in hybrid vehicles.


 Project partners (BE) 


Project details

May 2020 - April 2023

With the support of 

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This project has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 876659. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Germany, Austria, Slovakia, Sweden, Finland, Belgium, Italy, Spain, Netherlands, Slovenia, Portugal, Greece, France, Turkey”.

Met de steun van


Projet subsidié par la Region de Bruxelles-Capital - Innoviris/project gesubsidieerd door het Brussels Hoofdstedelijk (Project subsidised by the Brussels Capital Region - Innoviris):

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