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All Journal Tadris: Jurnal keguruan dan Ilmu Tarbiyah Jurnal Ilmiah Manajemen dan Bisnis (JIMB) Jurnal Taman Vokasi Jurnal Analisis Bisnis Ekonomi SEIKO : Journal of Management & Business JURNAL REFORMASI ADMINISTRASI Jurnal Ilmiah untuk Mewujudkan Masyarakat Madani Transparansi Jurnal Ilmiah Ilmu Administrasi Jurnal Pendidikan Vokasi Otomotif Abiwara : Jurnal Vokasi Administrasi Bisnis Pattimura International Journal of Mathematics (PIJMath) JMT (Jurnal Matematika dan Terapan) Jurnal Ilmu Administrasi Publik Jurnal Pendidikan Teknik Mesin Journal of Automotive and Mechanical Applied Technology Jurnal Analisis Bisnis Ekonomi
Sudarwanto, Sudarwanto
Universitas Negeri Yogyakarta
Humanities Automotive Engineering Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Industrial & Manufacturing Engineering Materials Science & Nanotechnology Mathematics Mechanical Engineering Social Sciences Transportation Other

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Journal : Journal of Automotive and Mechanical Applied Technology

 1 
Periodic Maintenance Analysis Of Locomotive Series CC201 And CC203 Using Markov Chain Method at UPT.Balaiyasa Yogyakarta Zufar, Muhammad Nafidz; Nugraha, Beni Setya; Sudarwanto
Journal of Automotive and Mechanical Applied Technology Vol. 1 No. 1 (2024): December
Publisher : Universitas Negeri Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21831/jamat.v1i1.816

Abstract

The objectives of this study are: (1) To get and provide the right periodic maintenance implementation time on CC201 locomotive maintenance. (2) To get and provide the right periodic maintenance implementation time on CC203 locomotive maintenance. The method used in this research is Markov Chain, using the type of applied research. This research uses a quantitative approach. The data collection techniques used are (1) Primary Data Collection; and (2) Secondary Data Collection. Meanwhile, the research instruments used (1) Observation Sheet; and (2) Documentation. The data analysis used is (1) Determination of Condition or State; (2) Creating a Transition Matrix; and (3) Steady State Analysis to get the probability of locomotive conditions in good condition, lightly damaged, moderately damaged or severely damaged. The results of this study show that: (1) The right periodic maintenance implementation time on CC201 locomotive maintenance is proposal II at interval P2 with the highest probability of good condition of 0.609 and the lowest probability of heavy condition of 0.021. With this, a maintenance scheduling policy is obtained for every 1 month to perform periodic maintenance on day 7,128. (2) The right periodic maintenance implementation time for CC203 locomotive maintenance is proposal II at interval P2 with the highest probability in good condition of 0.619 and the lowest probability in severe condition of 0.142. With this, a maintenance scheduling policy is obtained for every 1 month to perform periodic maintenance on day 24,516.
Co-Authors Ade Firmansyah Ade Imas Rismayati Agustine, Debby Assyodiq, Rizal Beni Setya Nugraha Binoto, Rustham Michael Eric Hermawan Ibnu Hadi Ibnu Hadi Ibnu Siswanto Joko Sriyanto Karnadi Karnadi, Karnadi Khanifah Khanifah Mahatma, Yudi Nur Holisah Nurul Husna Prasetyono, Agus Puji Purwanto Purwanto Rahman, Yoanna Rismayati, Ade Imas Rudiyanto, Atha Fawwaz Sanyoto, Bagus Sayyidi, Sabbihis Sukaswanto Sukaswanto Sundari, Sri Tafakur Tafakur Tambengi, Roike Teguh Santoso Vera Maya Santi Yosep Efendi Zufar, Muhammad Nafidz