PhD in AI-Driven Digital Twin for Predictive Maintenance in Smart Manufacturing

This PhD project at Technological University Dublin focuses on advancing AI-driven Digital Twin technologies for predictive maintenance and energy optimization in smart manufacturing. The research will integrate Industrial IoT sensors, real-time data analytics, and machine learning to create scalable frameworks that monitor equipment health, predict failures, and recommend maintenance actions. The project also explores AI-driven energy efficiency strategies while maintaining productivity and reliability. Successful candidates will contribute to sustainable, resilient manufacturing systems and collaborate with industrial partners. The project aligns with European Industry 5.0 priorities and offers opportunities for high-impact publications and international networking.

• Design and implement a scalable Digital Twin architecture for predictive maintenance and energy optimization in industrial environments.
• Develop and integrate real-time data acquisition systems from Industrial IoT sensors.
• Create predictive models using machine learning algorithms to monitor equipment health and predict failures.
• Conduct validation through simulation and experimental case studies to ensure framework reliability.
• Support real-time decision-making for maintenance and energy optimization in manufacturing systems.
• Collaborate with industrial partners and international research networks to apply and refine the framework.
• Generate high-quality journal and conference publications based on research findings.