Lean, AI, and Data-Driven Transformation for Sustainable, Resilient, and Human-Centric Industry 5.0

Dear Colleagues,

The manufacturing sector is undergoing a profound technological, organizational and societal transformation. Over the past decade, Industry 4.0 (I4.0) has reshaped industrial production systems through the adoption of cyber–physical systems, the Industrial Internet of Things (IIoT), cloud and edge computing, advanced automation and data-driven decision-making technologies. These innovations have unlocked unprecedented levels of connectivity, visibility and process intelligence across manufacturing systems and industrial value chains.

More recently, the rapid emergence of artificial intelligence (AI) technologies, including machine learning, generative AI, large language models and autonomous agentic systems, has opened a new frontier for industrial transformation. These technologies are increasingly capable of supporting decision-making, adapting dynamically to changing production conditions and collaborating with human operators, thereby redefining the role of digital systems within manufacturing environments.

At the same time, growing research and policy attention have highlighted a critical challenge: technological advancement and automation alone are insufficient to ensure sustainable industrial development. Unbalanced digitalization may increase energy consumption, exacerbate organizational inequalities, reduce workforce inclusiveness and create new vulnerabilities in industrial systems. In response, the Industry 5.0 (I5.0) paradigm, promoted by the European Commission and increasingly adopted within the international scientific community, proposes a broader vision of industrial transformation grounded in three interconnected dimensions: human-centricity, environmental sustainability and systemic resilience. I5.0 therefore represents not only a technological evolution but also a managerial, organizational and socio-technical transformation. From this perspective, manufacturing organizations can be understood as complex socio-technical systems in which social dimensions, such as people, organizational relationships, skills and culture, continuously interact with technical elements including digital technologies, AI systems, processes and operational infrastructures. I5.0 thus calls for new governance models, responsible innovation approaches, workforce strategies and decision-making frameworks capable of aligning technological progress with human wellbeing, sustainability goals and long-term industrial resilience.

This Special Issue is specifically positioned at the intersection of technological innovation and managerial paradigms in I5.0. On the one hand, advanced AI technologies and data-driven systems are reshaping manufacturing operations, maintenance, logistics and industrial decision-making. On the other hand, established approaches, such as lean manufacturing, total productive maintenance (TPM), continuous improvement, sustainable operation management and organizational resilience continue to provide essential foundations for efficiency, adaptability, waste reduction and value creation. In the context of I5.0, these paradigms must be reinterpreted and expanded to integrate emerging AI capabilities and human-centered principles.

A central focus of this Special Issue concerns the role of data, intelligence and decision-making in industrial transformation. The growing diffusion of connected assets, digital platforms and AI-generated outputs is producing large and heterogeneous streams of industrial data. Converting this data into actionable and trustworthy knowledge through transparent, explainable and human-centered analytical approaches represents a critical challenge for the future of sustainable manufacturing and industrial management. The ways organizations govern, integrate and operationalize these technologies will increasingly influence operational performance, workforce inclusion, environmental and economic sustainability, strategic resilience and long-term competitiveness.

This Special Issue welcomes interdisciplinary contributions from engineering, operations and production management, management engineering, computer science, sustainability science, industrial management and related disciplines. We encourage original research articles, systematic and narrative reviews, methodological contributions and industrial case studies addressing both the technical and socio-technical dimensions of I4.0-to-5.0 transition. Particular attention will be devoted to interdisciplinary contributions addressing the integration of lean principles, AI-driven technologies, sustainability, resilience, governance and human-centered approaches within I5.0 transformation.

Topics of Interest

This Special Issue welcomes original research articles, reviews and case studies addressing (but not limited to) the following topics:

Lean, AI and data-driven manufacturing for Industry 5.0

• Integration of lean manufacturing principles with Industry 4.0 and Industry 5.0 enabling technologies.
• AI-enabled continuous improvement, waste reduction, intelligent decision-support and operational process optimization.
• Data-driven production systems, predictive analytics and smart maintenance strategies.
• Organizational, managerial and economic implications of AI-driven manufacturing transformation.

Sustainable and Resilient Systems

• AI-driven approaches for energy efficiency, resource optimization, carbon footprint reduction, and sustainable industrial performance.
• Lean–green manufacturing, circular economy strategies and environmentally responsible digitalization.
• Resilient operational systems, adaptive process management and disruption response strategies.
• Risk management, strategic resilience and economic assessment in Industry 4.0 to 5.0 transitions.

Human-Centric AI and the Future of Industrial Work

• Human–AI collaboration and human-centered operational systems aligned with Industry 5.0 principles.
• Explainable, trustworthy and responsible AI for industrial and organizational decision-making, including fairness, accountability, transparency and governance issues.
• Worker wellbeing, ergonomics, cognitive support and human augmentation in digitally enabled workplaces.
• Organizational transformation, workforce capabilities and socio-technical approaches to AI adoption.

Industry 5.0 Governance, Transition Frameworks and Industrial Applications

• Transition models, maturity frameworks and technology management approaches for Industry 4.0 to Industry 5.0 evolution.
• Governance, policy and regulatory mechanisms supporting sustainable and human-centric industrial systems.
• Performance measurement, data-driven decision-making and empirical evaluation of Industry 5.0 practices and outcomes.
• Industrial case studies and real-world applications integrating lean, AI, sustainability, resilience and governance principles.

Dr. Sara Antomarioni
Dr. Laura Lucantoni
Guest Editors

Manuscript Submission Information

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• sustainability
• Industry 5.0
• lean manufacturing
• artificial intelligence
• data-driven decision-making
• sustainable manufacturing
• human-centric systems
• predictive maintenance
• operational resilience
• continuous improvement
• socio-technical transformation