Analisis Keandalan Mesin Menggunakan MTTR dan Downtime untuk Menentukan Mesin Kritis pada Lini Produksi PT X.
DOI:
https://doi.org/10.29407/jmn.v8i2.20403Keywords:
downtime, keandalan mesin, mesin kritis, MTTR, preventive maintenanceAbstract
Keandalan mesin sangat penting dalam menjaga kelancaran produksi, terutama pada industri make-to-order seperti PT X. Penelitian ini menganalisis efektivitas pemeliharaan mesin menggunakan Mean Time To Repair (MTTR) dan total downtime berdasarkan data kerusakan selama Februari 2022. Metode penelitian meliputi pengumpulan data kerusakan, perhitungan MTTR, dan identifikasi mesin kritis. Hasil menunjukkan terdapat 22 mesin yang mengalami gangguan, dengan downtime terbesar pada CNC Router 6.5 (1080 menit), Bending (870 menit), dan High Frequency HF1 (180 menit). Temuan ini mengindikasikan bahwa pemeliharaan masih bersifat reaktif dan menyebabkan tingginya kehilangan waktu produksi. Penelitian merekomendasikan penerapan preventive maintenance terjadwal dan peningkatan pencatatan histori kerusakan.
Downloads
References
[1] E. Y. Salawu et al., “Impact of Maintenance on Machine Reliability : A Review,” in E3S Web of Conferences, 2023, vol. 430, pp. 1–12.
[2] S. F. Rahmananto and P. H. Tjahjanti, “Maintaining Printing Machines at a Textile Company Pemeliharaan Mesin Cetak di Perusahaan Tekstil,” in Procedia of Engineering and Life Science, 2024, vol. 7, pp. 132–137.
[3] J. O. Aji, “Improving Facility Operations : A Quantitative Evaluation of MTBF , MTTR , and SLA Targets,” Eur. J. Innov. Stud. Sustain., vol. 1, no. 3, 2025.
[4] A. Breznick, M. Kohutiar, M. Krbat, M. Eckert, and P. Mikuš, “Reliability Analysis during the Life Cycle of a Technical System and the Monitoring of Reliability Properties,” Systems, vol. 11, no. 556, 2023, doi: https://www.mdpi.com/2079-8954/11/12/556.
[5] M. Zieja, N. Grzesik, J. Tomaszewska, and G. Kozłowski, “applied sciences Implementation of the Mean Time to Failure Indicator in the Control of the Logistical Support of the Operation Process,” Appl. Sci., vol. 13, 2023, doi: https://doi.org/10.3390/app13074608.
[6] L. Pinciroli, P. Baraldi, and E. Zio, “Maintenance optimization in industry 4 . 0,” Reliab. Eng. Syst. Saf., vol. 234, 2023, doi: 10.1016/j.ress.2023.109204.
[7] D. Apriatno, “USULAN PENERAPAN TOTAL PRODUCTIVE MAINTENANCE (TPM) GUNA MENINGKATKAN KINERJA MESIN ELEKTROPLATING DI PERUSAHAAN FURNITUR TANGERANG,” J. OE, vol. 7, no. 3, pp. 271–288, 2015.
[8] P. Ka´zmierczak, K. Zywicki, and P. Rewers, “The Impact of Downtime on the Stability of the Production Schedule,” Appl. Sci., vol. 15, 2025.
[9] P. Moemenishahraki, “Reliability and Maintenance Performance Analysis of a 1600 - ton Press Machine Using MTBF , MTTR , KPI , and Downtime Indicators,” Ind. Eng., vol. 9, no. 2, pp. 36–41, 2025.
[10] S. Alfionita and F. I. Alifin, “Preventive Maintenance Analysis Based on Mean Time Between Failure ( MTBF ) and Mean Time to Repair ( MTTR ),” Angkasa J. Ilm. Bid. Teknol., vol. 15, no. 2, 2023, doi: 10.28989/angkasa.v15i2.1833.
[11] L. Marbun and A. Indra, “Analisis Preventive Maintenance Pada Generator Set ( Genset ) Dengan Metode Mean Time Between Failure ( Mtbf ) Dan Mean Time To Repair,” J. Inovtek Seri Mesin, vol. 2, no. 1, pp. 39–47, 2025.
[12] I. S. Lopes, M. C. Figueiredo, and V. Sá, “Criticality evaluation to support maintenance management of manufacturing systems,” Int. J. Ind. Eng. Manag., vol. 11, no. 1, pp. 3–18, 2020.
[13] N. R. Wicaksono and S. D. N. Rosady, “Penerapan Metode Reliability Centered Maintenance ( RCM ) untuk Menentukan Strategi Perawatan Mesin Pencacah Sampah Organik,” J. Mech. Eng., vol. 1, no. 4, pp. 1–15, 2024.
[14] A. P. Maysarah, F. T. D. Atmaji, and J. Alhilman, “PERANCANGAN SIMULASI MONITORING JARAK JAUH DENGAN SENSOR GETARAN UNTUK MEMPREDIKSI KERUSAKAN MESIN CNC MILLING A PADA DESIGN OF DISTANCE MONITORING SIMULATION WITH VIBRATION SENSOR TO PREDICT THE DAMAGE OF CNC MILLING A MACHINES IN,” in e-Proceeding of Engineering, 2019, vol. 6, no. 2, pp. 7130–7136.
[15] H. Tian et al., “OPEN A novel FMECA method for CNC machine tools based on D-GRA and data envelopment analysis,” Sci. Rep., vol. 14, pp. 1–21, 2024.
[16] S. V. I. Pratiwi and H. Murnawan, “Analisa Perbaikan Mesin Cutting Guna Mengurangi Frekuensi Kerusakan dan Jam Perbaikan Mesin,” JUTIN J. Tek. Ind. Terintegrasi, vol. 7, no. 2, pp. 1083–1092, 2024, doi: 10.31004/jutin.v7i2.27800.
[17] F. J. Á. García and D. R. Salgado, “Analysis of the Influence of Component Type and Operating Condition on the Selection of Preventive Maintenance Strategy in Multistage Industrial Machines : A Case Study,” Machines, vol. 10, 2022.
[18] A. Setiawan, H. Windyatri, and Suhendra, “PENERAPAN PREVENTIVE MAINTENANCE MENGGUNAKAN METODE RELIABILITY CENTERED MAINTENANCE ( RCM ) UNTUK,” J. DESIMINASI Teknol., vol. 12, no. 2, pp. 89–94, 2024.
[19] S. Li et al., “Failure Analysis for Hydraulic System of Heavy-Duty Machine Tool with Incomplete Failure Data,” Appl. Sci., vol. 11, 2021.
[20] M. Gopalakrishnan, M. Subramaniyan, and A. Skoogh, “Data-driven machine criticality assessment – maintenance decision support for increased productivity,” Prod. Plan. Control, vol. 33, no. 1, pp. 1–19, 2022, doi: 10.1080/09537287.2020.1817601.
[21] N. Ahmadi and N. Y. Hidayah, “Analisis Pemeliharaan Mesin Blowmould Dengan Metode RCM Di PT . CCAI,” J. Optimasi Sist. Ind., vol. 16, no. 2, pp. 167–176, 2017.
[22] S. Muhiu, “Reliability-Based Preventive Maintenance Scheduling of a Multi-unit Injection Molding System : A Case Study,” Int. J. Ind. Eng. Manag., vol. 16, no. 1, pp. 24–39, 2025.
[23] F. S. Al-duais, A. A. Mohamed, T. M. Jawa, and N. Sayed-ahmed, “Optimal Periods of Conducting Preventive Maintenance to Reduce Expected Downtime and Its Impact on Improving Reliability,” Hindawi, vol. 2022, 2022, doi: 10.1155/2022/7105526.
[24] S. D. SIREGAR, “IMPLEMENTATION OF MAINTENANCE STRATEGY AND ASSET HEALTH MONITORING ON UNDERGROUND GBC Business Administration Program ) INSTITUT TEKNOLOGI BANDUNG JULY 2023 ABSTRACT IMPLEMENTATION OF MAINTENANCE STRATEGY AND ASSET HEALTH MONITORING ON UNDERGROUND GBC Sah,” INSTITUT TEKNOLOGI BANDUNG, 2023.
[25] N. Chambi et al., “Predictive Maintenance in Underground Mining Equipment Using Artificial Intelligence,” Eng, vol. 6, no. 261, pp. 1–22, 2025.
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Arief Syaefudin, Deri Teguh Santoso, Jojo Sumarjo, Ratna Dewi Anjani

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Copyright on any article is retained by the author(s).
- The author grants the journal, right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgment of the work’s authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal’s published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.
- The article and any associated published material is distributed under the Creative Commons Attribution-ShareAlike 4.0 International License


