Condition Monitoring Scheduled Oil Sample on Crane Machine Using the Fuzzy Logic Methode
DOI:
https://doi.org/10.55927/fjsr.v2i7.5289Keywords:
Fuzzy Logic, Scheduled Oil Sample, Crane, MachineAbstract
Maintenance of crane engines in the mining world is very much needed to maintain the engine in good condition and function when used. In crane engine maintenance management, a scheduled oil sample is a form of predictive engine maintenance by taking regular oil samples from the engine to analyze its content and quality in the laboratory. The Fuzzy Logic method used in this study aims to monitor the results obtained from the laboratory so that it can be recognized that the condition of the engine is still in excellent condition (eval A), the state of the engine is still good, and no action has been recommended (eval B), it is recommended action on the engine (eval C) and recommends stopping the engine (eval X)
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Bhardwaj, S., Bhardwaj, N., & Kumar, V. (2019). The study of reliability of diesel locomotive engine using weibull distribution. International Journal of Agricultural and Statistical Sciences, 15(2).
Imtihan, M., & Yusup Somantri. (2022). Perawatan Komponen Mesin Forming Untuk Meningkatkan Produksi Cup Minuman. JENIUS : Jurnal Terapan Teknik Industri, 3(1). https://doi.org/10.37373/jenius.v3i1.230
Kosasih, W., Sriwana, I. K., & Purnama, W. J. (2019). Perancangan Sistem Informasi Perawatan Mesin Menggunakan Pendekatan Analisis Berorentasi Objek. Jurnal Ilmiah Teknik Industri, 6(3). https://doi.org/10.24912/jitiuntar.v6i3.4246
McLinn, J. A. (1990). Constant failure rate — A paradigm in transition? Quality and Reliability Engineering International, 6(4). https://doi.org/10.1002/qre.4680060405
Nadjafi, M., Farsi, M. A., Zio, E., & Mousavi, A. K. (2018). Fault trees analysis using expert opinion based on fuzzy-bathtub failure rates. Quality and Reliability Engineering International, 34(6). https://doi.org/10.1002/qre.2313
Pislaru, M., Herghiligiu, I. V., & Robu, I. B. (2019). Corporate sustainable performance assessment based on fuzzy logic. Journal of Cleaner Production. https://doi.org/10.1016/j.jclepro.2019.03.130
Raposo, H., Farinha, J. T., Fonseca, I., & Galar, D. (2019). Predicting condition based on oil analysis – A case study. Tribology International. https://doi.org/10.1016/j.triboint.2019.01.041
Ren, Y. (2021). Optimizing Predictive Maintenance with Machine Learning for Reliability Improvement. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 7(3). https://doi.org/10.1115/1.4049525
Samsinar, R., Almanda, D., & Priatna, E. (2019). Sistem Pengingat Ganti Oli Berdasarkan Running Hours Mesin, Lama Waktu Pemakaian dan Kekentalan Oli pada Mesin Wire Drawing Berbasis Raspberry Pi 1. RESISTOR (ElektRonika KEndali TelekomunikaSI Tenaga LiSTrik KOmputeR), 2(2). https://doi.org/10.24853/resistor.2.2.121-130
Serrano-Guerrero, J., Romero, F. P., & Olivas, J. A. (2021). Fuzzy logic applied to opinion mining: A review. Knowledge-Based Systems, 222. https://doi.org/10.1016/j.knosys.2021.107018
Shetty, R. B. (2018). Predictive Maintenance in the IoT Era. In Prognostics and Health Management of Electronics. https://doi.org/10.1002/9781119515326.ch21
Thawkar, A., Tambe, P., & Deshpande, V. (2018). A reliability centred maintenance approach for assessing the impact of maintenance for availability improvement of carding machine. International Journal of Process Management and Benchmarking, 8(3). https://doi.org/10.1504/IJPMB.2018.092891
Ulugbek, F., Buyun, S., Zheng, X., & Ismael, T. (2018). A reliability-based preventive maintenance methodology for the projection spot welding machine. Management Science Letters, 8(6). https://doi.org/10.5267/j.msl.2018.5.005
Utomo, A. I., & Santoso, D. T. (2022). Implementasi FMEA (Failur Mode And Effect Analysis) Pada Mesin Bubut Konvensional Di PT. Raja Ampat Indotim. Jurnal Teknik Mesin Dan Pembelajaran, 5(1). https://doi.org/10.17977/um054v5i1p17-24
Wicaksono, P. A., Saptadi, S., Nurkertamanda, D., & Rozaq, R. (2021). Production Machine Maintenance System Design Using Reliability Centered Maintenance. IOP Conference Series: Materials Science and Engineering, 1096(1). https://doi.org/10.1088/1757-899x/1096/1/012018
Widyaningrum, M. R., & Winati, F. D. (2022). Penjadwalan Perawatan Mesin di CV Wijaya Workshop dengan Pendekatan Reliability Centered Maintenance (RCM). Jurnal TRINISTIK: Jurnal Teknik Industri, Bisnis Digital, Dan Teknik Logistik, 1(1). https://doi.org/10.20895/trinistik.v1i1.455
Wulansari, N., & Ardyanto W., D. (2019). Hubungan Faktor Individu Dan Ketersediaan Prosedur Perawatan Mesin Dengan Tindakan Tidak Aman Oleh Mekanik. The Indonesian Journal of Occupational Safety and Health, 8(1). https://doi.org/10.20473/ijosh.v8i1.2019.84-93
Zadeh, L. A. (2008). Is there a need for fuzzy logic? Information Sciences, 178(13). https://doi.org/10.1016/j.ins.2008.02.012
Zhu, J., Yoon, J. M., He, D., Qu, Y., & Bechhoefer, E. (2013). Lubrication oil condition monitoring and remaining useful life prediction with particle filtering. International Journal of Prognostics and Health Management.
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