Manutenção inteligente de helicópteros militares: aplicação da indústria 4.0 e inteligência artificial em cenários de conflito

Abstract

This dissertation investigates the optimization of military helicopter maintenance through the application of Industry 4.0 and Artificial Intelligence (AI) in conflict scenarios. In a strategic landscape demanding high operational readiness, this work reaffirms the necessity of transitioning from traditional maintenance paradigms to proactive and predictive approaches. The study establishes a solid theoretical framework, detailing the evolution of maintenance and the pillars of Industry 4.0 that enable real-time monitoring and fault anticipation. AI is explored across its diverse applications in aeronautical maintenance and the military context, demonstrating its transformative potential to ensure greater availability and resilience. A conceptual model for intelligent maintenance of military helicopters is proposed, outlining its architecture based on comprehensive data collection, robust infrastructure, advanced AI-driven analysis, and a Human-in-the-Loop interface. This model aims to enhance diagnosis and prognosis, optimizing repairs and resource allocation. The study of real conflicts illustrates the severe limitations of traditional maintenance, propelling the evolution towards intelligent models. The proposed model's application would have mitigated operational difficulties, increasing availability. This capability reflects the profound transformation of current military maintenance, evolving from a reactive model to proactive, predictive, and prescriptive. In summary, this dissertation offers a theoretical-conceptual roadmap for implementing intelligent maintenance, focusing on military helicopters, highlighting its strategic role in ensuring operational readiness and optimizing resources in battlefield scenarios.