This thesis embarks on a comprehensive exploration of modern industrial workplaces, delving into the intricate interplay between humans, machines, and software. Motivated by the imperative to bridge existing gaps in industrial automation, the research aims to contribute practical solutions to address the evolving nature of industrial systems. The objectives encompass unraveling the characteristics of so-called Industry 4.0 and Industry 5.0, understanding the contributions of Manufacturing Execution Systems (MES), Cyber-Physical Systems (CPS), and Artificial Intelligence (AI), and enhancing human-machine collaboration in manufacturing environments.

The thesis unfolds through a literature review, introducing an Intelligent Manufacturing Execution System (IMES) framework and presenting real-world applications of AI. Two compelling use cases demonstrate AI's transformative potential in manufacturing control and monitoring applications, addressing challenges hindering widespread adoption. The study further introduces a novel human-centered Cyber-Physical System framework (HC-CPS), leveraging Extended Reality (XR) interfaces and offering design principles for intuitive and collaborative environments. A tangible implementation of this framework serves as a proof of concept, showcasing feasibility and effectiveness in real-world settings.

The contributions of this work extend beyond conceptual frameworks, with practical insights provided through use cases and implementations. The proposed IMES framework and HC-CPS advance understanding and set the stage for the evolution of intelligent and user-friendly manufacturing systems. The thesis concludes with a prototype Cyber-Physical System featuring a 3D digital twin and demonstrating the integration of extended reality technologies to create immersive and human-centered systems. Overall, this research makes significant strides in advancing manufacturing systems toward next-generation solutions.