Quality Control Analysis of a Digital Printing Company Based on Production Reject Data Using the C-Chart & Pareto Chart Methods

Angela Michelle; Aurelia Giza; Selvia Selvia; Uriel Christabella Valencia; Tony Michelle; Aurora Natasha; Hendriani Concetta Tiara Regina; Nurhayati Nurhayati

doi:10.71456/sur.v4i2.1713

Authors

Angela Michelle* Department of Business, Prasetiya Mulya University
Aurelia Giza Department of Business, Prasetiya Mulya University
Selvia Selvia Department of Business, Prasetiya Mulya University
Uriel Christabella Valencia Department of Business, Prasetiya Mulya University
Tony Michelle Department of Business, Prasetiya Mulya University
Aurora Natasha Department of Business, Prasetiya Mulya University
Hendriani Concetta Tiara Regina Department of Business, Prasetiya Mulya University
Nurhayati Nurhayati Food Business Technology, Prasetiya Mulya University

DOI:

https://doi.org/10.71456/sur.v4i2.1713

Keywords:

C-chart, Digital Printing, Pareto Analysis, Production Defects, Statistical Process Control

Abstract

Digital printing industries face persistent quality challenges due to production defects that increase operational costs and reduce customer satisfaction. This study analyzed reject rates at PT. X, a mid-sized digital printing company in Tangerang, Indonesia, from August 2025 to January 2026 using quantitative descriptive-analytical methods through a case study approach. Total sampling captured 180 daily observations of production defects categorized into machine-related issues, packaging defects, lamination failures, base-support problems, blurry printing, and others. Statistical Process Control techniques employed c-charts to establish control limits (CL=1,500, UCL=1,616, LCL=1,384) and Pareto charts to prioritize dominant defect causes. Results revealed process stability for four months, with significant deviations in November 2025 (1,767 defects exceeding UCL) and August 2025 (1,327 defects below LCL), indicating special cause variations. Machine-related defects consistently contributed 40-50% of total rejects across all months. Findings confirm average reject rates of 2-3% per batch and recommend prioritizing machine maintenance and process monitoring. This research provides an adaptive SPC model for seasonal defect management in tropical manufacturing contexts and practical improvement strategies for digital printing SMEs.

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