IMPACT OF LEAN SIX SIGMA ON MANUFACTURING EFFICIENCY USING A DIGITAL TWIN-BASED PERFORMANCE EVALUATION FRAMEWORK

This systematic review explores the integration of Lean Six Sigma (LSS) methodologies with Digital Twin (DT) technologies to assess their combined impact on manufacturing efficiency and performance valuation. With the growing need for real-time monitoring, predictive analytics, and continuous improvement in industrial environments, the fusion of LSS and DT offers a promising hybrid framework for enhancing productivity, reducing defects, and enabling adaptive control mechanisms. The review followed the PRISMA 2020 guidelines to ensure transparency and rigor, resulting in the inclusion of 72 peer-reviewed articles published between 2010 and 2024 across multiple sectors including aerospace, automotive, pharmaceuticals, electronics, and FMCG. Findings indicate that the integration of LSS-DT systems leads to significant improvements in cycle time reduction, takt time optimization, predictive maintenance, and real-time quality monitoring. A notable trend across the reviewed literature is the emergence of hybrid performance metrics that blend traditional Lean Six Sigma KPIs with digital system-level indicators such as simulation fidelity, data latency, and predictive control accuracy. While sectors like aerospace and automotive demonstrate high maturity in implementing these integrated frameworks, others—particularly small and medium-sized enterprises—face challenges related to cost, digital literacy, and infrastructural readiness. The review also identifies theoretical tensions between the deterministic nature of traditional Lean Six Sigma models and the probabilistic, adaptive capabilities of digital twin systems. Despite these challenges, the synthesis of findings confirms that LSS-DT integration fosters a culture of continuous improvement and operational resilience supported by data-driven decision-making. This study contributes to the evolving discourse on Industry 4.0 by offering an in-depth, cross-sectoral evaluation of LSS-DT convergence and proposing new directions for hybrid performance management in advanced manufacturing systems.