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Predictive Maintenance Using Artificial Intelligence in Critical Infrastructure: A Decision-Making Framework

Year: 2024

Type: article

Abstract: 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.

Source: International Journal of Engineering Business and Management

DOI: 10.22161/ijebm.8.4.1

Author: Thomas L. Wiese

Institution: Empire State University

Language: English

Topic: Reliability and Maintenance Optimization

Subfield: Safety, Risk, Reliability and Quality

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: diamond

OpenAlex ID: W4403899182