A theoretical framework for human-centric cyber-physical production systems in industry 5.0: Enabling resilient, autonomous, and adaptive manufacturing - Kadam, Akash Abaji; Kosna, Srinivas Reddy; Kadam, Supriya Akash (Review of Computer Engineering Research, 2025)
This paper intends to put forward a conceptual framework for the development of Cyber-Physical Production Systems (CPPS), which integrates AI, ML, and IoT technologies with human-centric design principles. Industry 5.0 is focused on a human-centric, resilient, and adaptive manufacturing system where harmony in human-machine collaboration exists. The proposed framework addresses some of the challenges facing currently trending ecologies of manufacturing. In other words, it lets CPPS automatically adjust to changes in the environment and keep learning from real-time data and interactions between people in production settings, making the whole setting more resilient and effective. At the core of this framework is the inclusion of self-learning algorithms and adaptive system architectures that accommodate intuitive human-machine interfaces that support collaborative decision-making and operational flexibility. The paper also includes conceptual implementation scenarios in order to show precisely how this envisioned CPPS framework dynamically copes with these operational challenges and sustains itself at optimal performance to support human roles in complex manufacturing processes. The proposed framework further has the ambition to lay foundation for future empirical research and enable the development of Industry 5.0-aligned smart manufacturing systems in a manner that pays due attention to technological innovation and human well-being. The outcome of our findings underlines the human-centered CPPS for the revolutionary effects it could bring to sustainable and agile manufacturing solutions for the next industrial revolution. Critical challenges such as sustainability, operational disruptions, and collaborative decision-making are addressed, and actionable insights are given for further empirical research and industrial applications.