Enhancing Quality Control of Packaging Product: A Six Sigma and Data Mining Approach - Resty Ayu Ramadhani; Rina Fitriana; Anik Nur Habyba; Yun-Chia Liang (Jurnal Optimasi Sistem Industri, 2023)
Six Sigma is of paramount importance to organizations as it provides a structured and data-driven approach, fostering continuous improvement, minimizing defects, and optimizing processes to meet and exceed customer expectations. In response to the increasing defects of packaging product in a cosmetics industry in Indonesia, surpassing the speciﬁed 3% tolerance limit, this research conducts a thorough investigation into the root causes, corrective measures, and improvement proposals to elevate product quality. By leveraging the Six Sigma method and data mining techniques, the study systematically addresses the complexities associated with defect reduction in packaging for cosmetics product. The research methodology encompasses deﬁning the problem through SIPOC and Critical to Quality (CTQ) diagrams, measuring via control charts and sigma level calculations, and analyzing using tools like pareto diagrams, Apriori algorithms, ﬁshbone diagrams, and Fault Mode and Eﬀect Analysis (FMEA). Key ﬁndings reveal a notable correlation between spot defects and varying colors, leading to pearl defects as identiﬁed by the Apriori algorithm. FMEA identiﬁes critical failures, including suboptimal printing plate conditions, clumpy ink usage, and insuﬃcient operator attention to ink ﬁlling. The improvement stage proposes practical solutions, such as implementing alarms and buzzers, color-indicator-adjusted ink storage labels, and a structured form for cleaning and monitoring printing plates. These ﬁndings carry signiﬁcant implications, providing a tailored roadmap for enhancing the quality of cosmetic packaging. The anticipated implementation of proposed improvements aims to elevate customer satisfaction by addressing speciﬁc pain points in the production process. Furthermore, the research contributes valuable insights to the broader cosmetics industry, oﬀering eﬀective methodologies for defect reduction and quality enhancement in packaging processes.