Data-Driven Analysis to Minimize Downtime in an Automated Production Line

This study presents a comprehensive, data-driven approach to minimize operational downtime, a crucial determinant of Overall Equipment Effectiveness (OEE), in a fully automated manufacturing line of a medical care production facility. Through an in-depth study of operational systems, employing innovative analytical tools such as mind maps, causal loops, and cause-effect diagrams, we identified and addressed the primary factors causing machine downtime. Our strategy included the implementation of crafted Standard Operating Procedures (SOPs), which encompassed failure modes for each station, a refined data entry process, and targeted mechanical interventions, particularly at the bottleneck station: the bag welding station. Additionally, the integration of human elements through extensive workforce surveys ensured the alignment of solutions with employee dynamics and self-interest, contributing to sustainable changes. The proposed solution has been shown to increase OEE by more than 1.1% in all scenarios, leading to a revenue increase of over a million USD per year.