AI for Predictive Maintenance and Anomaly Detection at VINCI and Schneider Electric скачать в хорошем качестве

AI for Predictive Maintenance and Anomaly Detection at VINCI and Schneider Electric

💡 Visions of Business: "AI for Predictive Maintenance and Anomaly Detection" – Episode #5 From connected assets to offshore infrastructure, AI is redefining how maintenance is planned and performed in the energy and construction sectors. 🔍 At Schneider Electric, Claude Le Pape explains how EcoStruxure Asset Advisor uses AI to detect anomalies and predict equipment failures—helping extend asset lifespan, avoid breakdowns, and reduce environmental impact. By analyzing data from real-world usage and conditions, AI enables smarter, more targeted maintenance interventions. 🔧 Meanwhile, VINCI is leveraging machine learning to optimize railway maintenance on long-term infrastructure like the Paris–Bordeaux high-speed line. Weekly track scans feed models that simulate degradation over time, enabling the company to prioritize actions and combine operations, reducing both costs and carbon impact. 🌊 Offshore wind farms also benefit from AI-powered planning: anticipating breakdowns weeks in advance means maintenance vessels can be reserved early, safety is increased, and green energy output is maximized. 🤝 With Hi! PARIS research teams, companies like VINCI and Schneider Electric are exploring unsupervised learning and graph-based anomaly detection, bringing cutting-edge science into operational excellence. 🔗 Read the full white book: https://www.hi-paris.fr/visions-of-bu... #AI #PredictiveMaintenance #Energy #Sustainability #SchneiderElectric #VINCI #ArtificialIntelligence #SmartInfrastructure #HiPARIS