A Hybrid Six Sigma Dmaic and Fuzzy-FMEA Framework For Defect Reduction and Quality Enhancement In White Copra Production
DOI:
https://doi.org/10.59976/jurit.v2i2.113Keywords:
Six Sigma, Fuzzy-FMEA, White Copra, Product Quality, AgroindustryAbstract
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This study aims to analyze the factors causing defects in white copra products using the Six Sigma (DMAIC) method integrated with Fuzzy-Failure Mode and Effect Analysis (Fuzzy-FMEA). The research method includes collecting production data, calculating Defects Per Million Opportunities (DPMO), determining the sigma level, and analyzing the root causes through cause-and-effect diagrams and risk assessment using Fuzzy-FMEA. The results show that the average sigma level of the process is at 3.63 with a DPMO value of 16,910, indicating that process performance still needs improvement. The dominant factors causing defects include unstable drying temperature, storage humidity, oven machine damage, and operator skill variation. The highest priority risks identified were drying temperature and humidity control, which directly impact the quality of the final product. The practical implications of this study are the need to implement mechanical drying with automatic temperature control, operator training programs, preventive oven maintenance, and standard operating procedures (SOPs) in quality control. This study contributes to strengthening empirical evidence of the application of DMAIC combined with Fuzzy-FMEA in agroindustry, particularly in coconut processing, and serves as a reference for improving product quality based on a quantitative and fuzzy logic approach.
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