20.500.12556/DiRROS-19675 A ǂFramework for applying data-driven AI/ML models in reliability In this chapter, we present a framework for applying artificial intelligence (AI)/machine learning (ML) in reliability, in the context of the iRel40 project. Data-driven models are becoming an increasingly fruitful tool for detecting patterns in complex data and identifying the circumstances in which they occur. Using only data, gathered along the value chain, data-driven methods are now being used to detect indications of potential early failures, signs of wear out or degradation, and other unwanted events within the development, fabrication, or service phases of the electronic components and systems. We present general considerations that were found to be important during the iRel40 project, when designing pipelines that combine data processing with the AI/ML models for predicting or detecting reliability issues. This chapter serves as an introduction to the definitions and concepts used within the specific use cases that rely on the AI/ML methodology within the iRel40 project. machine learning artificial intelligence data-driven models true false true Springer Švica Angleški jezik Ni določen © 2024 The Author(s), under exclusive license to Springer Nature Switzerland AG Neznano 2024-07-23 11:42:30 2024-07-23 11:42:30 2024-07-24 03:48:02 0000-00-00 00:00:00 2024 0 0 Nasl. z nasl. zaslona; Opis vira z dne 22. 7. 2024; 1 spletni vir (1 PDF dokument (323–337 str.)) 0000-00-00 PostprintKoncna Objavljeno NiDoloceno 0000-00-00 0000-00-00 2024-04-22 2026-04-22 004.8 10.1007/978-3-031-59361-1_12 202399235 202391555 https://link.springer.com/chapter/10.1007/978-3-031-59361-1_12 1 21c1efb9-48c7-11ef-b487-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=27172 RAZ_Hribar_Rok_2024.pdf RAZ_Hribar_Rok_2024.pdf 1 EDA00360935E968892AF14DE5913FB82 b01d2104c905b4bc33717733b6477d2c2387eb1f2a1290e72b88afa62f330a1f b0e79174-48c7-11ef-b487-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=27173 Institut Jožef Stefan 0 0 0