<![CDATA[The textile industry, particularly sock manufacturing, faces increasing demands for productivity and cost efficiency amid global competition. This study presents a comprehensive case study on optimizing sock production in a South African knitting plant as a cost-effective alternative to Industry 4.0 adoption. The Research aims to identify and address key factors contributing to low productivity by employing a data-driven approach integrating Six Sigma methodologies and simulation analysis. Production data revealed that frequent system failures caused significant stoppages, material waste, and reduced operational efficiency, with approximately 8% of production output lost to defective socks. Detailed analysis using Failure Mode and Effect Analysis (FMEA) and a cause–and–effect diagram identified machine- and material-related issues as the primary contributors to poor performance. A planned maintenance strategy was developed based on the Mean Time to Failure (MTTF) of major equipment, and its impact was simulated using Any Logic software. Simulation results demonstrated that implementing scheduled maintenance, reducing failure rates by 50%, could increase system availability to 91% and substantially decrease fabric waste. The novelty of this study lies in demonstrating an effective optimization strategy that avoids the high cost and implementation barriers of full Industry 4.0 integration while achieving comparable productivity gains. This simulation-based maintenance framework provides a practical, data-supported solution for enhancing efficiency, reliability, and competitiveness in conventional manufacturing systems. The findings suggest that similar textile plants can adopt this approach to achieve sustainable production improvements without undergoing complete digital transformation.]]>
