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      •   IPB Repository
      • Dissertations and Theses
      • Undergraduate Theses
      • UT - Faculty of Agricultural Technology
      • UT - Agroindustrial Technology
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      IDENTIFIKASI DAN EVALUASI PADA MESIN LABELING MENGGUNAKAN METODE FAILURE MODE AND EFFECT ANALYSIS (FMEA)

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      Date
      2025
      Author
      Rizki, Septian Abdillah
      Warsiki, Endang
      Sugiarto
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      Abstract
      Penelitian ini bertujuan untuk mengidentifikasi dan mengevaluasi potensi kegagalan pada mesin labeling tepung terigu menggunakan metode Failure Mode and Effect Analysis (FMEA). Mesin labeling merupakan komponen penting dalam proses pengemasan yang mempengaruhi efisiensi dan kualitas produk akhir. Permasalahan seperti kesalahan penempelan label, overheat, dan downtime sering terjadi dan berdampak pada produktivitas. Melalui pendekatan FMEA, dilakukan penilaian terhadap tingkat keparahan (Severity), frekuensi kejadian (Occurrence), dan kemampuan deteksi (Detection) untuk setiap mode kegagalan, yang kemudian dihitung nilai Risk Priority Number (RPN)-nya. Hasil analisis menunjukkan bahwa komponen seperti kabel power, sistem pelumasan, dan sensor OCR memiliki nilai RPN tertinggi. Setelah dilakukan tindakan mitigasi seperti pemasangan voltage stabilizer, penggantian grease tahan panas, dan penggantian sensor, terjadi penurunan signifikan pada nilai RPN, dengan rata-rata penurunan lebih dari 70%. Penelitian ini menunjukkan bahwa penerapan FMEA secara sistematis dapat meningkatkan keandalan mesin, mengurangi risiko kegagalan, dan mendukung pencapaian target produksi.
       
      This study aims to identify and evaluate potential failures in the wheat flour labeling machine using the Failure Mode and Effect Analysis (FMEA) method. The labeling machine is a critical component in the packaging process that affects both efficiency and product quality. Issues such as label misplacement, overheating, and unexpected downtime frequently occur, impacting productivity. Through the FMEA approach, each failure mode was assessed based on Severity, Occurrence, and Detection, and the Risk Priority Number (RPN) was calculated. The analysis revealed that components such as power cables, lubrication systems, and OCR sensors had the highest RPN values. After implementing mitigation actions such as installing voltage stabilizers, replacing high-temperature-resistant grease, and upgrading sensors, a significant reduction in RPN values was observed, with an average decrease of over 70%. This study demonstrates that systematic application of FMEA can enhance machine reliability, reduce failure risks, and support production target achievement.
       
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      http://repository.ipb.ac.id/handle/123456789/168967
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      • UT - Agroindustrial Technology [4355]

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      Indonesia DSpace Group 
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