Uncovering the Influence of Operational Factors on Manufacturing Efficiency with Real Time Data

In modern manufacturing, OEE is a crucial metric, for assessing production efficiency. However, traditional OEE such as TOEE often missed out the key operational parameters-those that have the greatest influence on overall factory performance. This research provides comparative analysis using Traditional Overall Equipment Effectiveness (TOEE) and Modified Overall Equipment Effectiveness (MOEE). The research considers additional operational variables, which are ideal cycle time, downtime, roller performance and customer demand. This study seeks to provide a more dynamic and comprehensive view of manufacturing efficiency. The manufacturing production system is incorporating data in real time. The study looks into how machine performance data, shift schedules, the planned as well as unplanned downtime uncover hidden inefficiency. These findings align with MOEE's ability to be more representative of how efficiently a company operates due to its accounting for more variables. This approach allows manufactures to put a finger on the pulse to recognize improvements area in real-time, to refine production processes and improve OEE. Leveraging true sustainability data: this paper shows activity recommendations when moving to a model that includes real time information with a view to refined performance metrics, such as the path to decision making in manufacturing operations. The findings highlight that MOEE provides a more comprehensive and accurate reflection of manufacturing efficiency compared to TOEE by incorporating real-time operational factors.