Boosting Electronics Manufacturing Efficiency with Automated Data Mining and OEE Process Analytic - Sumargo, Ruly; Santoso, Handri (Universitas Merdeka Malang, 2024)
In the last few decades, the industrial sector has experienced rapid growth, driven by increasing demand and intense competition among manufacturers, especially in the electronics sector. This competition focuses on providing superior products with competitive prices, maintained quality, and optimal delivery times. Optimizing manufacturing processes and effectively utilizing company resources have become key to competitiveness in the manufacturing industry. To ensure comprehensive optimization and smooth manufacturing workflows, it is crucial to engage in systematic evaluation and analytical processes. One of the key performance metrics in assessing manufacturing process efficiency is Overall Equipment Efficiency (OEE), which is used to uncover improvement opportunities and inefficient areas. Accurate OEE measurement requires a data mining systems with automated quantitative data collection methods and real-time calculations. These systems visualize process losses in six (pareto) groups, aiding users in analyzing processes and determining process improvements. The implementation of OEE and alert systems for management can bring an 11.82% increase in overall production efficiency. This achievement can serve as a model for other companies embarking on the initial stages of digital transformation processes.