Journal of Resource Management and Decision Engineering 5 Serial Number 16 2026 09 01 Providing an Integrated Model of Lean Six Sigma and Supply Chain Resilience and Analyzing Its Effects on Improving Flexibility in Industries Providing an Integrated Model of Lean Six Sigma and Supply Chain Resilience and Analyzing Its Effects on Improving Flexibility in Industries 1 14 EN Journal Article 2025 08 04 <p>The purpose of this study is to design and validate an integrated model of Lean Six Sigma and resilient supply chain management across various industries by evaluating the effects of lean tools on resilience indicators. The research employed an exploratory mixed-methods approach implemented in four stages: content analysis to identify key factors, interpretive structural modeling to develop the conceptual model, a fuzzy inference system to assess the effects, and design of experiments to validate the model. The statistical population consisted of twelve experts, including industrial engineering specialists and managers active in different industries, selected through purposive and snowball sampling. Data collection instruments included semi-structured interviews and NVivo version 11, MATLAB, and Minitab software. Content analysis resulted in the extraction of sixty-six open codes, twenty-four axial categories, and eleven selective categories, which led to identifying eight lean tools—including 5S, Poka-Yoke, QFD, SMED, FMEA, benchmarking, SIPOC, and BSC—and three resilience indicators: flexibility, capacity, and adaptability. Data saturation was achieved after the twelfth interview. Findings from interpretive structural modeling indicated that 5S and QFD serve as driving variables at lower levels and influence intermediate variables and resilience outcomes at higher levels. Results of the design of experiments using fractional factorial designs showed that 5S, with a coefficient of 15.3, had the greatest impact on flexibility and capacity, while QFD had the strongest effect on adaptability. The fuzzy inference system results further confirmed these findings. Periodic review of the supply chain using benchmarking at medium or high levels is recommended.</p> https://journalrmde.com/index.php/jrmde/article/download/218/298