Enhancing Overall Equipment Effectiveness (OEE) in a Specific Food Manufacturing Process

This thesis explores the challenges and strategies involved in optimizing production line efficiency within a food manufacturing process, with a focus on improving Overall Equipment Effectiveness (OEE). By utilizing lean management techniques, the research specifically addresses the issue of downtime and its impact on operational performance. Lean tools such as gemba, process mapping, key performance indicators (KPIs), and bottleneck analysis were applied, in combination with Industry 4.0 principles, to leverage data and advanced technologies aimed at enhancing manufacturing efficiency. A key contribution of this thesis is the development of the Stop Reason Application, designed to capture precise downtime data and provide actionable insights into micro-stoppages often overlooked by traditional methods. Collaboration with production managers, engineers, and operators ensured the application’s scalability and effectiveness. The findings highlight specific equipment, such as the capper and the all-in-one machine, as major contributors to production stoppages. Additionally, product-specific issues, such as labeler performance and setup times, were identified. This research underscores the importance of precise downtime tracking in optimizing production line performance, offering valuable insights into improving operational efficiency through technology and collaboration. The Stop Reason Application proved to be a valuable tool for decision-making, contributing to continuous improvement in the manufacturing process.