The Role of Machine Learning within MIRELAI

Have you ever wondered how long your phone or computer will last before needing repairs? MIRELAI, a European project, is using artificial intelligence (AI) to improve the reliability of electronics and predict their lifespan more accurately. This is where machine learning (ML) comes in!

But what exactly is machine learning, and how does it improve electronics? Think of machine leaning as a super-smart computer programme that learns from data. In MIRELAI’s case, the data comes from sensors embedded in electronic devices and real-world tests. This data helps the ML programme understand how electronics wear down over time, kind of like a super-powered detective!

MIRELAI is using machine learning in two exciting ways:

Understanding how electronics degrade: Imagine detectives examining how electronics wear down over time. Machine learning helps analyse data from sensors and real-world tests to understand the physics behind this degradation. This knowledge is then fed back into the machine learning models, making them even smarter.
Predicting how long electronics will last: Wouldn’t it be great to know exactly when your phone needs replacing? By combining sensor data with the knowledge gained from the first step, MIRELAI is developing machine learning models that can predict the remaining useful life (RUL) of electronic components. This can help manufacturers create more reliable products and users plan for replacements.

MIRELAI focuses on two key areas where ML can make a big difference:

Miniaturized components: As electronics get smaller, predicting their reliability becomes trickier. MIRELAI is using machine learning to understand how tiny changes in these components affect their lifespan.
Whole circuit boards: Circuit boards, packed with many components. MIRELAI is developing a method to assess the criticality of individual parts on the board, helping identify weak points and prevent overall failure.

By using machine learning, MIRELAI aims to create a future with more reliable electronics. This can lead to longer-lasting gadgets, reduced waste, and better planning for both manufacturers and consumers.