<![CDATA[Quality control plays a vital role in maintaining product consistency and customer satisfaction in the manufacturing industry. This study was conducted at PT Manufaktur Cakung, a manufacturer of truck engine components, aiming to identify dominant defect types, determine their root causes, and provide data-driven improvement recommendations. The methods applied include Statistical Quality Control (SQC) and Root Cause Analysis (RCA). SQC utilized tools such as the histogram, Pareto chart, scatter diagram, and control chart to analyze four months of production data totaling 7,417 units. The results showed an average defect rate of 0.14%, with four dominant defects: clogged fuel nozzle (20%), leaking exhaust manifold (30%), leaking water pump (30%), and improper flywheel balancing rework (20%). Although the process was statistically under control, variations still occurred due to inconsistent SOP implementation, poor instrument calibration, and suboptimal work environment conditions. Using RCA with the 5 Why’s and Ishikawa diagram, the main causes were identified as human error and measurement inaccuracy. The proposed improvements are projected to reduce defects below 0.1%, demonstrating the effectiveness of SQC–RCA integration in achieving continuous quality improvement. Keywords: Defect, Manufacturing Process, Quality, RCA, SQC]]>
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