An integrated six sigma-fuzzy AHP-DOE framework for optimizing porosity defect in low pressure die casting

Abstract

This study proposes an integrated framework combining Six Sigma, Fuzzy Analytic Hierarchy Process (Fuzzy AHP), and Design of Experiments (DoE) to improve process quality in cylinder head manufacturing. Unlike previous studies that have applied Six Sigma with either DoE or AHP in isolation, this research develops a hybrid approach in which Fuzzy AHP prioritizes Critical-to-Quality (CTQ) factors under uncertainty, and DoE optimizes process parameters within the Six Sigma DMAIC cycle. The method was applied to the Low Pressure Die Casting (LPDC) process, where porosity defects significantly affect product quality. A full factorial Design of Experiments (DoE) was conducted on three parameters: aluminum temperature, pressure, and press-up time, each tested at three levels. The results showed that the optimal combination of 700 °C aluminum temperature, 18,000 Pa pressure, and 8 s press-up time reduced porosity defects to 0.64%, achieving a six-sigma level of 2.49. The findings confirm that the proposed six-sigma, Fuzzy AHP and DoE framework provides a structured and effective approach for minimizing porosity defects while offering practical contributions to quality improvement in the automotive industry.