Under the Six Sigma framework, this study implements the DMAIC (Define–Measure–Analyze–Improve–Control) methodology to methodically mitigate defects in a tissue manufacturing process. Process variability, machine limitations, and operational inefficiencies are inherent factors that contribute to quality deviations and elevated production costs in manufacturing systems. The primary goal of this research is to quantitatively assess the performance of the process and to implement engineering-based interventions that will reduce the occurrence of defects and improve operational efficiency. Based on the baseline analysis, the average defect rate per production cycle was 3.0% to 5.0%, which amounts to an estimated monthly loss of ₱94,000 to ₱157,000. Process mapping, Pareto analysis, and statistical tools were implemented to quantify critical performance indicators, including productivity rate, defect frequency, and process stability. The primary contributors to deterioration were identified as machine-related factors and process inconsistencies through root cause analysis. Mechanical modification and process optimization of the rewinding system were employed to implement engineering enhancements. The results of the post-implementation phase indicated a decrease in the defect rate from 4.2% to 1.6%, which amounts to a 61.9% enhancement in quality performance. On the other hand, disposal costs decreased by approximately 38%, while productivity also increased. A statistically significant difference was observed between the pre- and post-implementation results (p < 0.05) according to the t-test used for statistical validation. The enhanced process stability and reduced variability were further confirmed by control charts. The results verify that the integration of DMAIC methodology with engineering analysis and statistical validation establishes an efficient framework for process optimization and defect reduction. The study underscores the importance of mechanical process enhancement and data-driven decision-making in the pursuit of sustainable quality improvement in manufacturing systems. The results provide a scalable model for operational excellence and continuous development in industrial production environments.

Keywords

DMAIC, defect, optimization, control, efficiency.