Enhancing Quality Control of Packaging Product: A Six Sigma and Data Mining Approach

Abstract

This study explores the application of Six Sigma and data mining methodologies to address the high defect rate in the packaging of Wardah Lightening Powder Foundation. Faced with quality control challenges, the research aims to systematically identify the root causes of packaging defects and develop strategic measures to enhance product quality. Employing a comprehensive Six Sigma approach, the study incorporates various analytical tools, including SIPOC diagrams, Critical-to-Quality (CTQ) characteristics, control charts, Pareto diagrams, and Failure Modes and Effects Analysis (FMEA). These tools facilitate a detailed investigation of the packaging process, highlighting significant failure types and inefficiencies. The research methodology involves an extensive data collection and analysis phase, utilizing data mining techniques to delve into historical defect data. This analysis uncovers underlying patterns and correlations that contribute to packaging failures. Based on these findings, the study proposes targeted interventions to mitigate defect levels. These interventions include the implementation of alarm systems and buzzers on production lines to promptly address issues, and the redesign of ink storage labels for clearer communication and error reduction. The outcomes of this study demonstrate a substantial improvement in packaging quality, evidenced by a marked reduction in defect rates. This enhancement not only contributes to operational efficiency but also plays a crucial role in elevating customer satisfaction levels. The research underscores the effectiveness of integrating Six Sigma with data mining in identifying, analyzing, and resolving quality issues in manufacturing processes. It provides valuable insights for organizations in the packaging industry seeking to optimize their quality control mechanisms and achieve higher standards of product excellence.