Minimizing Defects in Radiator Grille Upper Garnish Parts using Six Sigma (DMAIC) at PT. AAS

Authors

  • Yosica Mariana Bina Nusantara University
  • Wandi Andrean PT. TVS Motor Indonesia, Karawang, Jawa Barat, Indonesia
  • Nina Tania Lestari Bina Nusantara University

DOI:

https://doi.org/10.21512/emacsjournal.v5i3.10481

Keywords:

Six Sigma, DMAIC, Quality Analysis

Abstract

To achieve quality improvement, companies must align their production processes with customer needs, control production costs effectively, and maintain product quality. This approach enhances customer satisfaction, increases market share, and boosts profitability. PT. AAS, an automotive company specializing in injection molding and painting, relies on resin as its primary raw material to produce car parts for major clients like Hyundai, Suzuki, and Astra. To dominate the market, PT. AAS must prioritize delivering quality products on time to earn customer trust and secure continuous orders. Initially, the QC data for the injection molding area showed a high defect rate of approximately 17.5% for the Garnish Radiator Grille Upper part, from December 2022 to May 2023. Prior to implementing the Six Sigma method, PT. AAS had a DPMO (Defects Per Million Opportunities) value of 58,177, equivalent to a 3.10 Sigma level. After applying the Six Sigma DMAIC (Define, Measure, Analyze, Improve, Control) process, the DPMO decreased to 17,991, resulting in a 3.60 Sigma level. This suggests that PT. AAS currently operates at a 4 Sigma level, with a strong potential to reach 5 or even 6 Sigma by addressing the root causes of rejection. The fishbone analysis highlights the need for action across all departments, including Management. Key areas to focus on include Material, ensuring the correct resin delivery to the Injection Molding station; Machine, verifying proper machine settings and utilizing the 5S methodology; Environment, optimizing room temperature and ventilation; and Man, providing training to enhance operators' knowledge and sense of responsibility.

Dimensions

Plum Analytics

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Published

2023-10-02

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