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All Journal Journal of Advanced in Information and Industrial Technology (JAIIT)
Dina Maharani
St. John's University Taiwan, Taiwan
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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Integrating Statistical Process Control and Failure Mode and Effects Analysis to Reduce Product Defects in Oil Filter Manufacturing (Case Study: CV XYZ) Vitho Azeryan; Anindya Rachma Dwicahyani; Dina Maharani
Journal of Advances in Information and Industrial Technology Vol. 8 No. 1 (2026): May
Publisher : LPPM Telkom University Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52435/jaiit.v8i1.710

Abstract

CV XYZ is a small-to-medium-sized manufacturing company struggling with a high rate of product defects. This study integrates Statistical Process Control (SPC) and Failure Modes and Effects Analysis (FMEA) to analyze and improve the quality performance of the oil filter production process at CV XYZ. Several SPC tools were applied, including a check sheet, Pareto analysis, P-control chart, and root cause analysis using a fishbone diagram. The findings revealed that deformation was the most frequent defect type, accounting for 152 units (23%) out of 675 total defects recorded over five months. Root cause analysis identified multiple contributors to deformation defects, which were then evaluated using FMEA based on three parameters: severity, occurrence, and detection. The Risk Priority Number (RPN) calculations determined that excessive product stacking was the primary cause, followed by non-compliance with standard operating procedures (SOPs), a poorly organized workstation, and inadequate lighting and visibility. Based on these findings, several corrective actions were recommended, including improving SOPs for the pressing process, scheduling regular SOP training, and implementing standardized stacking procedures aligned with production output. These measures are projected to reduce total nonconformities by approximately 6.9%. The key contribution of this study is providing a practical quality improvement framework for SME manufacturers with limited quality management resources and analytical capabilities. The integrated SPC-FMEA approach enables data-driven decision-making without requiring extensive expertise. Nevertheless, real-world implementation remains necessary to validate the projected outcomes.
Co-Authors Anindya Rachma Dwicahyani Vitho Azeryan