Enhancing inventory accuracy in dairy industries
integrating DMAIC and action research for optimizing logistics performance
DOI:
https://doi.org/10.14488/BJOPM.2439.2025Keywords:
DMAIC, Quality tools, Inventory management, OTIF (On Time In Full)Abstract
Goal: The goal is to analyze the application of Lean Six Sigma and DMAIC in the inventory management of a dairy industry, aiming to optimize inventory accuracy, reduce picking errors, and enhance OTIF performance, thereby improving overall operational efficiency.
Design / Methodology / Approach: This applied and descriptive research adopts an action research strategy, with researchers actively participating in the project's execution. Lean Six Sigma principles and the DMAIC framework were systematically applied to inventory, picking, and supply processes. Statistical validation was conducted using the Z-test for two proportions to confirm the effectiveness of the improvements implemented.
Limitations of the investigation: The study focuses on a case analysis in a dairy processing environment; however, the structured methodology adopted allows replication in industries characterized by operational complexity, perishability, or high inventory turnover.
Practical implications: The study offers valuable insights for logistics, procurement, and operations professionals. The implemented methodologies led to a 36.63% reduction in inventory discrepancies, resulting in cost savings of R$124,540.56. Additionally, significant improvements were achieved in controlling picking errors and enhancing OTIF performance, underscoring the critical role of structured continuous improvement methodologies in inventory management.
Originality / Value: This research addresses a gap in applied studies on inventory management in the dairy sector, demonstrating the successful application of Lean Six Sigma and DMAIC to achieve substantial operational improvements. The study presents a replicable model for other industries seeking to optimize inventory control, minimize operational errors, and elevate supply chain performance.
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Copyright (c) 2025 Francisco Tiago Araújo Barbosa, Rogerio Santana Peruchi, Maria Silene Alexandre Leite, Mauro Sergio Mascarenhas
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