A Taguchi-Based Framework for Continuous Quality Improvement in Crude Palm Oil Production

Purpose – This study aims to analyze and optimize the quality of Crude Palm Oil (CPO) using the Taguchi method. The research focuses on identifying the dominant factors affecting Free Fatty Acid (FFA), moisture, and impurity content, as well as determining the optimal parameter combination to achieve consistent product quality that meets company standards. Design/methodology/approach – The study employed an experimental design based on the Taguchi method using an orthogonal array with seven factors at two levels. Data were collected from laboratory tests on CPO samples during production, focusing on FFA, moisture, and impurities. Statistical analyses included the Signal-to-Noise Ratio (S/N), Analysis of Variance (ANOVA), and confidence interval validation to identify significant factors and optimal operating conditions. Findings – The results show that factors A (fresh fruit bunch maturity) and F (sterilizer process conditions) significantly influence CPO quality, as indicated by the highest F-ratios (4.64 and 4.86) and contribution values exceeding 15%. The optimal parameter combination successfully minimized variability in FFA and impurity levels, though overall results still slightly exceeded company standards, suggesting the need for stricter control of raw material selection and processing parameters. Confidence interval analysis confirmed that the predicted mean values for FFA, moisture, and impurities were close to the specification limits, indicating potential for further refinement. Originality– This study provides empirical evidence of the Taguchi method’s applicability in the palm oil industry, particularly for improving CPO quality under real industrial constraints. The novelty lies in integrating Taguchi analysis with confidence interval verification to assess compliance robustness, offering a structured framework for continuous process improvement in CPO manufacturing.