A systematic review of human centric sustainable and resilient Industry 5.0 with a seven layer framework

The transition from Industry 4.0 to Industry 5.0 represents a fundamental paradigm shift in industrial systems, moving from efficiency-driven, technology-centric automation toward human-centric, sustainable, and resilient socio-technical ecosystems. Despite growing scholarly attention, the literature remains fragmented across engineering, artificial intelligence, sustainability science, ethics, and organizational domains, limiting the emergence of a unified conceptual foundation. To address this gap, this study conducts a systematic literature review following PRISMA 2020 guidelines to integrate and critically synthesize multidisciplinary evidence on Industry 5.0. A rigorous screening and eligibility assessment process was applied to ensure methodological robustness, resulting in the inclusion of 177 peer-reviewed studies. The synthesis traces the evolution of industrial paradigms from Industry 1.0 to Industry 5.0, highlighting the underlying technological, economic, and socio-political forces driving transformation. It develops a multidimensional comparative analysis between Industry 4.0 and Industry 5.0 across seven transformation dimensions, emphasizing fundamental shifts in value creation logic, human–machine integration, autonomy, sustainability orientation, and governance architecture. The study further consolidates enabling technologies, including collaborative robotics, explainable artificial intelligence, digital twins, cyber-physical systems, blockchain, augmented and virtual reality, and edge computing, as core enablers of adaptive human–machine symbiosis. In addition, it introduces a seven-layer conceptual framework integrating foundational infrastructure, intelligence, collaboration, sustainability, resilience, governance, and human-centricity, offering a unified architecture for industrial transformation. The review identifies critical implementation barriers, including cybersecurity vulnerabilities, workforce reskilling constraints, ethical and transparency challenges in AI systems, and fragmented regulatory environments. Collectively, this study establishes a rigorous and integrative foundation for advancing theory and guiding industrial and policy transitions toward next-generation human-centered, sustainable, and resilient industrial ecosystems.