Smart manufacturing requires quality-control systems capable of detecting defects and responding to process deviations in real time. This study develops an AI-driven predictive quality-control framework that integrates machine vision, sensor-based monitoring, sequential process modelling, and closed-loop multi-objectiv...
Chidera Anastacia Ezeh, Ayomide Oladele, Ahmed Idowu Agbelejoye et al.· Asian Journal of Advanced Re...· 0 citations
Advances in AI, physics-informed modelling, and Digital Twin technologies offer the potential to enhance predictive maintenance, asset-integrity assessment, and energy management within oil and gas processing systems. However, these frameworks are most useful when they are based on a common data source, use a consisten...
Henry Inkum, C. Ezeh, Vanessa Grant et al.· Asian Journal of Advanced Re...· 0 citations
An AI-driven automation and digital twin framework for smart transportation systems that leverages real-time sensor data, historical transportation information, Internet of Things technologies, and advanced machine-learning algorithms for intelligent traffic management and predictive infrastructure maintenance is propo...
Henry Inkum, C. Ezeh, Georgina Fiyinfoluwa Leramo et al.· Asian Journal of Advanced Re...· 0 citations
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