Abstract Manufacturers today face dual demands: improving operational efficiency and achieving environmental sustainability. Lean Six Sigma (LSS) is effective for reducing waste and variability, while Sustainable Manufacturing (SM) emphasizes resource conservation and environmental performance. However, existing models rarely integrate both goals into a unified system. This paper proposes a novel framework that embeds sustainability metrics—such as energy use, waste generation, and carbon emissions—into the DMAIC (Define, Measure, Analyze, Improve, Control) structure of LSS. We validate the framework using real-world industrial data supported by statistical tools including regression, SPC, and time-series forecasting. Results show measurable improvements in energy efficiency, waste reduction, and process stability. The framework enables manufacturers to meet quality, cost, and environmental targets simultaneously. This study contributes a scalable, data-driven model for achieving sustainable operational excellence.
Alanezi et al. (Fri,) studied this question.