Integrating human-centric automation and sustainability through the NAToRM framework: A neuromorphic computing approach for resilient industry 5.0 supply chains

• Advanced technologies enhance efficiency in Industry 5.0 supply chains. • Neuromorphic computing for fast, real-time supply chain data processing. • Persistent homology aids in analyzing complex, high-dimensional datasets. • Spatiotemporal matrices offer in-depth risk assessment across areas and times. • Reinforcement learning improves adaptive AI decision-making in supply chains. Industry 5.0 supply chains face critical challenges in effectively managing the rapidly growing volume, variety, velocity, and veracity of big data while simultaneously ensuring sustainability, privacy, and ethical practices. The complex and interconnected nature of modern supply networks and the swift adoption of advanced technologies have created an urgent need for innovative frameworks to navigate these multifaceted challenges. Existing approaches often fail to adequately address the unique demands of Industry 5.0, lacking the ability to process data in real time, uncover deep insights, and enable dynamic, risk-informed decision-making. Moreover, there is a pressing need for frameworks that emphasize interdisciplinary collaboration and proactively address the potential negative impacts of emerging technologies. This paper introduces a novel, multidisciplinary framework that integrates cutting-edge techniques to tackle these challenges head-on, paving the way for more resilient, intelligent, and adaptable supply chains in the Industry 5.0 era.