<![CDATA[The automotive component industry faces significant challenges in improving operational efficiency and production quality, particularly due to reliance on manual processes. A key issue identified is the company's Overall Equipment Effectiveness (OEE) performance, which has not met the established target, with an average achievement of only 72%, indicating considerable process inefficiencies and productivity losses. External pressures such as global market dynamics, economic uncertainty, and increasing Regional Minimum Wage (UMP) rates have further exacerbated the need for digital transformation to enhance operational efficiency and organizational competitiveness. This study aims to design a digitalization system to address operational inefficiencies and low production quality in the automotive component industry, focusing on improving OEE performance, reducing operational costs, and supporting data-driven decision-making. This research proposes an integrated digitalization system developed through the combination of the selective QC 7 Tools and Design Thinking approaches, with the selective QC 7 Tools applied to systematically identify and analyze the root causes of operational inefficiencies. The implementation resulted in significant improvements, including the complete elimination of 195 minutes per shift of non-value-added activities, the reduction of reporting lead time from 2–3 days to near real-time (0.5 days for analysis), and a 10% increase in OEE performance. The system also enabled the reallocation of 13 administrative personnel to more value-added roles, reduced operational costs, and minimized paper waste and CO₂ emissions. This study confirms that the selective QC 7 Tools prove effective in supporting digital transformation, and that data-driven digitalization can significantly improve competitiveness and business sustainability.]]>
