Application of Statistical Quality-Analysis Tools in the 8D Methodology for Manufacturing Quality Improvement

This study investigates and resolves a pin warping defect in an aluminum component supplied to the automotive industry, applying the eight-discipline (8D) structured problem-solving methodology, supported by established statistical and quality-analysis tools within a statistical quality-control framework. A cross-functional team conducted root cause analysis using a cause-and-effect diagram and Minitab statistical software, complemented by process capability studies and non-parametric hypothesis tests on pin angle measurements from two injection moulding machines. Results demonstrated that manual handling of hot sprues—arising from an automation failure and compounded by the absence of standardized work instructions and operator training—was the primary cause of excessive pin warping. Statistical analysis confirmed significant variability in the manually operated process (Mann–Whitney U-test p = 0.005; Cpk < 0), in contrast to the automated process (Cp = 2.36). Corrective actions encompassing process standardization, operator training, and re-automation were implemented and validated, substantially reducing defect occurrence and restoring the automated process operation. The P-FMEA was updated to prevent recurrence. This work demonstrates the practical value of combining structured problem-solving with statistical analysis as an applied framework for diagnosing and resolving manufacturing defects, with particular relevance to environments where automation failures introduce process variability.