Smart Supply Chain Management Integrating Lean Six Sigma and Industry 4.0–5.0: Framework, Applications, and Challenges for Sustainability and Resilience
Abstract
Despite rapid digital transformation, modern supply chains remain vulnerable, facing demand volatility, supply disruptions, operational inefficiencies, fragmented digital adoption, limited human–AI collaboration, and growing sustainability pressures. Conventional strategies focused on cost reduction and process standardization are no longer sufficient to ensure resilience, adaptability, and long-term value creation. This study presents a Smart Supply Chain Management (SSCM) framework that integrates Lean Six Sigma (LSS) with Industry 4.0 (I4.0) digital technologies and Industry 5.0 (I5.0) human-centric innovations. Implemented through the DMAIC (Define–Measure–Analyze–Improve–Control) methodology, the framework enables predictive, data-driven decision-making, operational excellence, ESG-aligned performance, and enhanced human–AI collaboration. It leverages I4.0 technologies—including AI, IoT, big data analytics, digital twins, and robotics—for real-time visibility, automation, and predictive insights, while embedding I5.0 innovations—such as collaborative robots, AR/VR, human digital twins, and emotional AI—to enhance workforce engagement, creativity, ethical decision-making, and ergonomic safety. Sustainability and social responsibility are integrated across operations, fostering resilient, adaptable, and socially responsible supply chains. By addressing critical digital, human, and operational bottlenecks, this framework delivers novel theoretical insights, actionable guidance for practitioners, and a foundation for future empirical research, offering organizations a roadmap to achieve long-term competitiveness while aligning technology adoption with human-centric and sustainable practices.
Fields of Study & Subjects
Supply Chain Resilience and Risk Management
Digital Transformation in Industry
Quality and Supply Management
Publication details
- Journal / source
- Intelligent and sustainable manufacturing
- Publisher
- SCIE Publishing Limited
- Volume
- 3
- Issue
- 1
- Pages
- 10007–10007
- Publication date
- 1 January 2026
- Language
- EN