<![CDATA[In the manufacturing industry, quality control is a crucial factor in ensuring high-quality products that meet established standards. This study aims to develop a Six Sigma (SS) methodology with an Internet of Things (IoT) approach to enhance quality control effectiveness in the acrylic manufacturing industry. The method used in this study follows the DMAIC (Define, Measure, Analyze, Improve, Control) approach, combined with IoT technology to detect, analyze, and optimize the production process in real-time. This study employs a quantitative and qualitative (mixed-method) approach, collecting data through IoT sensor installations, production data analysis, and quality inspection. The collected data is analyzed using statistical methods and Six Sigma techniques to identify the main factors causing defects in acrylic production. Subsequently, an IoT system is implemented to improve automatic quality monitoring, reduce process variation, and optimize production efficiency. The research findings indicate that the integration of Six Sigma and IoT can significantly reduce product defect rates compared to conventional methods. Furthermore, the application of an IoT-based monitoring system enhances the speed of anomaly detection in the production process, allowing corrective actions to be taken more quickly and accurately. In conclusion, implementing this methodology can be an effective solution for the manufacturing industry to improve operational efficiency, reduce waste, and ensure consistent product quality.]]>
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