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All Journal Industrika : Jurnal Ilmiah Teknik Industri
Irvan Irvan
Universitas Singaperbangsa Karawang
Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Industrial & Manufacturing Engineering

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Penerapan Metode Statistical Process Control dalam Analisis Pengendalian Kualitas Produk Join Brake Rod KTMY di Perusahaan Manufaktur Otomotif Irvan Irvan; Sutrisno Sutrisno
Industrika : Jurnal Ilmiah Teknik Industri Vol. 10 No. 4 (2026): Industrika: Jurnal Ilmiah Teknik Industri
Publisher : Fakultas Teknik Universitas Tulang Bawang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37090/7ekw2a36

Abstract

Product quality in the automotive manufacturing industry greatly affects customer trust and production efficiency. This research was conducted at an automotive manufacturing company with the aim of analyzing the quality control of the Join Brake Rod KTMY part using the Statistical Process Control (SPC) method. The three types of defects analyzed were Non-Central Hole, Blank Minus, and Scratched Material. Data collection involved direct observation, production documentation, and interviews with relevant personnel. The data was analyzed using the Seven Tools of quality, including check sheets, Pareto diagrams, control charts (P-charts), and fishbone diagrams. The results showed that the Non-Central Hole defect was the most dominant, accounting for 56% of total defects from January to December 2024. Control charts indicated several data points outside the control limits, suggesting that the production process was not fully stable. The main causes of defects were found to be related to human, machine, method, material, and environmental factors. Improvement proposals focused on operator training, jig and die adjustment, and raw material inspection. In conclusion, the SPC method is effective in statistically monitoring and controlling product quality in automotive manufacturing. Keywords: Product Defect, Quality Control, Statistical Process Control (SPC), Types of Defect
Co-Authors Sutrisno