Abstract The manufacturing industry plays a vital role in the economic foundation of many countries. To meet increasing demands, operational efficiency and product quality must be closely monitored. These are commonly measured using Key Performance Indicators, including Overall Equipment Effectiveness, which is based on availability, performance, and quality. Manual OEE measurement often leads to delays, inaccuracies, and limited real-time monitoring. To address these challenges, this research proposes an automated, real-time OEE Calculation System (OEE-CS) for Metal Inert Gas welding machines using Industry 4.0 technologies such as the Internet of Things and Cyber-Physical Systems. Data from sensors is transmitted wirelessly, analyzed, and displayed through a user-friendly interface accessible via smartphone or PC. Experimental results show that the OEE-CS accurately calculates OEE components with an average deviation of 4.5% compared to manual methods. The system also correctly identifies non-operational periods, yielding an OEE value of 0% when no production is scheduled. These findings demonstrate the system’s reliability and its potential to support data-driven decision-making in real time.
Raharno et al. (Mon,) studied this question.
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