A data-driven and cognitive analytics framework for sustainable supply chain transformation in industry 6.0

The transition from data-driven to cognitively adaptive supply chains represent a critical step toward Industry 6.0, where learning, coordination, and sustainability must be addressed jointly. Existing supply chain analytics approaches remain limited in capturing adaptive and systemic behaviors under uncertainty, particularly in resource- and energy-intensive industrial contexts. This study proposes a Cognitive and Data-Driven Framework for Supply Chains based on federated learning and synthetic data simulations grounded in aggregated industrial benchmarks. The framework introduces the Adaptivity Coefficient (A c ), a composite metric integrating learning velocity, anticipatory responsiveness, and technological exposure to quantify cognitive readiness at the network level. Results from simulation experiments show that cognitively adaptive supply chains achieve significant performance improvements compared to conventional predictive approaches. Specifically, cognitive coordination reduces cumulative disruption costs by 18–25%, lowers emissions intensity by up to 15%, and shortens recovery time by approximately 27%. The analysis further demonstrates that adaptive learning expands the Pareto-efficient frontier, enabling simultaneous gains in cost efficiency, resilience, and environmental performance under varying levels of uncertainty. These findings suggest that cognitive adaptivity functions as a strategic capability rather than a purely technical feature. The study concludes by highlighting the managerial and policy implications of embedding cognitive learning into supply chain governance and by outlining pathways for future empirical validation in hard-to-abate manufacturing sectors. • A Cognitive and Data-Driven Framework is proposed to model Industry 6.0 supply chains. • Synthetic data and federated learning are used to simulate adaptive and sustainable behaviors. • The Adaptivity Coefficient (Ac) quantifies network readiness and cognitive performance. • Cognitive adaptivity simultaneously improves cost efficiency, resilience, and environmental outcomes. • The study outlines governance and validation pathways for systemic change in hard-to-abate industries.