Gracia Wiranatalie Damanik
UPN "Veteran" Jawa Timur

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Waste Analysis in the Aluminum Extrusion Process utilizing Lean Six Sigma and Failure Mode and Effect Analysis (FMEA) Gracia Wiranatalie Damanik; Enny Aryanny
ITEJ (Information Technology Engineering Journals) Vol. 11 No. 1 (2026): June
Publisher : Pusat Teknologi Informasi dan Pangkalan Data IAIN Syekh Nurjati Cirebon

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24235/itej.v11i1.293

Abstract

This study aims to identify the dominant types of waste, investigate the underlying causes of quality failures, and formulate improvement recommendations to enhance the efficiency of the production process. The research employs an integrated approach combining Lean Six Sigma and Failure Mode and Effect Analysis (FMEA) to systematically identify inefficiencies and prioritize corrective actions. In contrast to previous studies that primarily focus on a single Critical to Quality (CTQ) characteristic within aluminum extrusion processes, this study examines four dominant CTQs, thereby providing a more comprehensive framework for quality improvement. The findings indicate that defects constitute the most critical form of waste, with the highest weight value of 0.1206, followed by waiting (0.0905) and transportation (0.0854). Further analysis using fishbone diagrams and FMEA reveals that denting defects represent the most significant failure mode, yielding the highest Risk Priority Number (RPN) of 336. Based on the proposed improvement initiatives, the company has the potential to eliminate all non-value-added (NVA) activities and substantially reduce necessary non-value-added (NNVA) activities. The implementation of these recommendations decreases the total production lead time from 2,435.59 minutes to 1,870.41 minutes, while increasing the proportion of value-added (VA) activities from 40.86% to 46.34%. These results demonstrate that the integration of Lean Six Sigma and FMEA provides an effective and systematic approach to improving process efficiency and product quality in aluminum extrusion manufacturing.