Enhancing supply chain resilience in retail operations: a novel DFSS and fuzzy logic model for optimizing order fulfillment process

Abstract

By employing Design for Six Sigma (DFSS) methodologies and incorporating fuzzy logic, we propose a novel order fulfillment processes (OFP) model that identifies and integrates critical performance metrics and key process variables essential for supply chain management (SCM). The proposed model effectively optimizes internal processes and synchronizes supply chain (SCs) partners, emphasizing mutual review, enhanced monitoring, and strategic parameter adjustments during forecast evaluations. This model significantly improves performance measurement systems by targeting customer demands, process surveillance, and regulation. Its flexibility and integration of fuzzy logic allow it to manage variability and adapt to unique scenarios, providing targeted analysis and valuable insights for practitioners seeking to enhance their supply chains incrementally. Our research advances the theoretical understanding of SCM while offering practical insights to improve OFP and overall SCM performance.