| KEYWORD |
AI for Prognostics: a Survey on Emerging approaches and implementation
keywords ARTIFICIAL INTELLIGENCE, COMPUTATIONAL MODELING, COMPUTATIONAL TOPOLOGY, ALGORITHMS DEVELOPMENT, PHM, PROGNOSTICS
Reference persons MATTEO DAVIDE LORENZO DALLA VEDOVA, PAOLO MAGGIORE
External reference persons Leonardo BALDO
Research Groups 16-ASTRA: Additive manufacturing for Systems and sTRuctures in Aerospace
Thesis type REVIEW, REVIEW OF ARTICLES
Description Prognostics and health management (PHM) technologies aim to alleviate the burden of maintenance tasks associated with products or processes by conducting diagnostic and prognostic activities. These activities generate actionable information that facilitates intelligent decision-making, leading to enhanced performance, safety, reliability, and maintainability. PHM requires platform-oriented and solution-oriented approaches that cannot be generalized due to the particular problem and system the PHM strategy is built upon. However, a systematic review on the most influential AI application for prognostics could provide extremely useful insights on the direction this branch is going towards.
Required skills Knowledge of Artificial Intelligence and related applications/approaches
Deadline 31/10/2024
PROPONI LA TUA CANDIDATURA