@article{Wiese_2024, title={Predictive Maintenance Using Artificial Intelligence in Critical Infrastructure: A Decision-Making Framework}, volume={8}, url={http://dx.doi.org/10.22161/ijebm.8.4.1}, DOI={10.22161/ijebm.8.4.1}, abstractNote={<jats:p>Critical infrastructure supports essential services across energy, transportation, water management, and telecommunications sectors. The degradation or failure of assets in these sectors can have serious economic and safety consequences. Predictive maintenance (PdM), driven by artificial intelligence (AI), has emerged as a transformative approach to optimize maintenance activities and prevent failures. This paper reviews current AI-based PdM applications in critical infrastructure and presents a decision-making framework for evaluating when AI should be used. By addressing technical capabilities, economic impacts, and regulatory concerns, the framework helps guide decision-makers in adopting AI for PdM.

</jats:p>}, number={4}, journal={International Journal of Engineering, Business and Management}, publisher={AI Publications}, author={Wiese, Thomas L.}, year={2024}, pages={01–04} }