KINETIKA embraces Industry 4.0 concepts to create a groundbreaking 4D digital twin framework for cultural heritage (CH) objects with mechanical parts, focusing on movable structures of industrial heritage and cultural heritage masonry. By integrating advanced imaging - photogrammetry, laser scanning and muography - KINETIKA captures both the physical form and internal complexity of objects, reflecting their dynamic nature. Through IoT-based sensor networks, the project continuously monitors structural integrity, environmental conditions, and mechanical performance, feeding data into AI-driven analytics for anomaly detection, predictive maintenance, and conservation strategies. The core principles of the 4D Digital Twin include accurate 3D representation, displacement or strain estimation, functional simulation, predictive failure analysis and time-based evolution modelling. These capabilities are enhanced by advanced computer vision and AI algorithms, enabling new levels of study and engagement with CH assets. KINETIKA also emphasises interactive and cross-media engagement, combining 3D models, images, sensor data and simulations to create immersive experiences for researchers, educators and the public. Collaboration between the cultural and industrial sectors is central, with KINETIKA's platform being seamlessly aligned with the ECCCH framework to ensure data interoperability. Third-party CH service providers will offer and consume specialised services through a secure interface, enhancing the ECCCH data while tailoring solutions for different heritage professionals. The project will validate its innovations through representative case studies, including clock towers, looms and drawbridges, demonstrating the platform's adaptability and guiding further applications across a wide range of cultural artefacts.