Predictive Surface Defect Detection in Particleboard Manufacturing using Defect Tracking Matrix–Principal Component Analysis Framework toward Zero Defect Manufacturing

Zero Defects Manufacturing (ZDM) is a proactive quality strategy aimed at preventing defects during production.This study proposes a novel integrated method using the Defect Tracking Matrix (DTM) and Principal Component Analysis (PCA) to predict the sources of surface defects in particleboard manufacturing.The authors evaluated twenty technical attributes and sixteen quality defects.Results showed that duct cleaning, setting the blower, screen cleaning, press calibration, and blade sharpening were key contributors to detecting patterns.The DTM-PCA framework improves traceability and helps implement ZDM through structured, data-driven analysis in a previously unexplored context.

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Publication Details

Journal
Evergreen
Published
2025-12-01
DOI
https://doi.org/10.5109/7402647
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Predictive Surface Defect Detection in Particleboard Manufacturing using Defect Tracking Matrix–Principal Component Analysis Framework toward Zero Defect Manufacturing

Yustina Suhandini Tjahjaningsih, Putu Dana Karningsih, Moses Laksono Singgih
Evergreen
Industrial Vision Systems and Defect Detection
article

Predictive Surface Defect Detection in Particleboard Manufacturing using Defect Tracking Matrix–Principal Component Analysis Framework toward Zero Defect Manufacturing

Yustina Suhandini Tjahjaningsih, Putu Dana Karningsih, Moses Laksono Singgih
article en

Abstract

Zero Defects Manufacturing (ZDM) is a proactive quality strategy aimed at preventing defects during production.This study proposes a novel integrated method using the Defect Tracking Matrix (DTM) and Principal Component Analysis (PCA) to predict the sources of surface defects in particleboard manufacturing.The authors evaluated twenty technical attributes and sixteen quality defects.Results showed that duct cleaning, setting the blower, screen cleaning, press calibration, and blade sharpening were key contributors to detecting patterns.The DTM-PCA framework improves traceability and helps implement ZDM through structured, data-driven analysis in a previously unexplored context.

EvergreenVol. 12(4)
Sepuluh Nopember Institute of Technology (ID), Universitas Panca Marga (ID)
Institut Teknologi Sepuluh Nopember, Direktorat Jenderal Pendidikan Tinggi, Direktorat Riset dan Pengabdian Masyarakat
Industry, innovation and infrastructure
Openalex Percentile: Top 28%
Industrial Vision Systems and Defect Detection
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