Application of the Lean Six Sigma Methodology Enhanced by Fuzzy Logic Optimizing Mold Changeover Times in the Automotive Injection Industry

Minimizing mold changeover time is a critical challenge in the plastic injection molding industry, as it directly impacts productivity, operational efficiency, and competitiveness. This study introduces an integrated approach that combines Lean Manufacturing tools, the DMAIC methodology (Define, Measure, Analyze, Improve,Control), and Single Minute Exchange of Dies (SMED) techniques, enhanced by fuzzy logic and artificial intelligence (AI). The methodology focuses on improving mold changeover processes for the NEGRI BOSSI 650 machine by identifying bottlenecks, transforming internal tasks into external ones, and optimizing workflows to reduce downtime and improve overall efficiency. Key phases of the study included identifying the root causes of inefficiencies through data collection and analysis, streamlining task sequences using real-time process data, and balancing the production line by redistributing workloads and reducing bottlenecks. Fuzzy logic and AI technologies were employed to support decision-making and enhance optimization, ensuring a robust and adaptable framework for continuous improvement. The results obtained were of high impact a 65% reduction in mold changeover time and a 46.8% improvement in Process Cycle Efficiency (PCE) with significant improvements in terms of the global line balancing. These findings validate the effectiveness of combining Lean principles with advanced technologies such as fuzzy logic in solving Industry challenges, improving resource utilization, and ensuring long-term operational performance. This study just goes to prove that a structured Lean Manufacturing approach combined with innovative tools and automation can drive significant improvement in the plastic injection molding industry, establishing a scalable and competitive strategy for operational excellence.