Analisis dan Peningkatan Efektivitas Mesin Produksi Menggunakan Metode Overall Equipment Effectiveness (OEE) dan Failure Mode and Effects Analysis (FMEA) pada PT Alcotraindo Batam
DOI:
https://doi.org/10.38035/gijes.v4i2.998Keywords:
Overall Equipment Effectiveness (OEE), Failure Mode and Effects Analysis (FMEA), Machine Effectiveness, Productivity, Manufacturing IndustryAbstract
In the manufacturing industry, machine effectiveness plays a crucial role in achieving production targets, maintaining product quality, and improving operational efficiency. PT Alcotraindo Batam, as a manufacturing company, relies heavily on production machines to support its operational activities. However, machine downtime, performance losses, and equipment failures can reduce productivity and hinder the achievement of production objectives. Therefore, this study aims to analyze the effectiveness of production machines using the Overall Equipment Effectiveness (OEE) method and identify critical failure factors using Failure Mode and Effects Analysis (FMEA). This research employed a quantitative descriptive approach using production data, machine downtime records, maintenance reports, and quality data collected over a six-month observation period. The OEE analysis showed that the average machine effectiveness value was 76.40%, which is below the world-class standard of 85%. The average Availability Rate, Performance Rate, and Quality Rate were 88.32%, 88.00%, and 98.30%, respectively. Furthermore, the Six Big Losses analysis revealed that Equipment Failure Losses were the largest contributor to productivity losses, accounting for 35.14% of total losses. The FMEA results indicated that conveyor motor overheating was the most critical failure mode, with the highest Risk Priority Number (RPN) value of 320, followed by sensor malfunction (245) and roller wear (210). Based on these findings, several improvement strategies are recommended, including strengthening preventive maintenance programs, conducting routine inspections of critical components, enhancing operator training, and improving machine monitoring systems. The integration of OEE and FMEA proved effective in identifying machine performance losses and determining improvement priorities. The implementation of these recommendations is expected to increase machine effectiveness, reduce downtime, and improve overall production productivity at PT Alcotraindo Batam.
References
Akturk, M. S., Ketzenberg, M., & Heim, G. R. (2018). Assessing impacts of introducing ship-to-store service on sales and returns in omnichannel retailing: A data analytics study. Journal of Operations Management, 61(1), 15–45. https://doi.org/10.1016/j.jom.2018.06.004
Gupta, P., & Vardhan, S. (2016). Optimizing OEE, productivity and production cost for improving sales volume in an automobile industry through TPM: A case study. International Journal of Production Research, 54(10), 2976–2988. https://doi.org/10.1080/00207543.2015.1076192
Liu, H. C., Liu, L., & Liu, N. (2013). Risk evaluation approaches in failure mode and effects analysis: A literature review. Expert Systems with Applications, 40(2), 828–838. https://doi.org/10.1016/j.eswa.2012.08.010
Muchiri, P., & Pintelon, L. (2008). Performance measurement using overall equipment effectiveness (OEE): Literature review and practical application discussion. International Journal of Production Research, 46(13), 3517–3535. https://doi.org/10.1080/00207540601142645
Nakajima, S. (1988). Introduction to TPM: Total productive maintenance. Productivity Press.
Prabowo, H. A., Setiawan, H., & Nugroho, S. (2021). Analysis of machine effectiveness using Overall Equipment Effectiveness (OEE) and Failure Mode and Effects Analysis (FMEA) methods in manufacturing industry. Journal of Industrial Engineering and Management Research, 2(5), 120–130.
Stamatis, D. H. (2003). Failure mode and effect analysis: FMEA from theory to execution (2nd ed.). ASQ Quality Press.
Wireman, T. (2004). Total productive maintenance (2nd ed.). Industrial Press.
Borris, S. (2006). Total productive maintenance. McGraw-Hill Professional.
Blanchard, B. S. (2004). Logistics engineering and management (6th ed.). Pearson Prentice Hall.
Heizer, J., Render, B., & Munson, C. (2020). Operations management: Sustainability and supply chain management (13th ed.). Pearson.
Mobley, R. K. (2002). An introduction to predictive maintenance (2nd ed.). Butterworth-Heinemann.
Montgomery, D. C. (2020). Introduction to statistical quality control (8th ed.). John Wiley & Sons.
Assauri, S. (2016). Manajemen operasi produksi: Pencapaian sasaran organisasi berkesinambungan (3rd ed.). Rajawali Pers.
Gaspersz, V. (2018). Total quality management. Gramedia Pustaka Utama.
Sutalaksana, I. Z., Anggawisastra, R., & Tjakraatmadja, J. H. (2006). Teknik tata cara kerja. Institut Teknologi Bandung.
Wignjosoebroto, S. (2008). Ergonomi: Studi gerak dan waktu. Guna Widya.
Jay Heizer, Barry Render, & Chuck Munson. (2020). Operations management: Sustainability and supply chain management (13th ed.). Pearson Education.
Moubray, J. (1997). Reliability-centered maintenance (2nd ed.). Butterworth-Heinemann.
Smith, A. M., & Hinchcliffe, G. R. (2004). RCM—Gateway to world class maintenance. Elsevier Butterworth-Heinemann.
Corder, A. S., & Hadi, K. (1992). Teknik manajemen pemeliharaan. Erlangga.
Kurniawan, F. (2013). Manajemen perawatan industri: Teknik dan aplikasi implementasi total productive maintenance (TPM), preventive maintenance, dan reliability centered maintenance (RCM). Graha Ilmu.
Sugiyono. (2023). Metode penelitian kuantitatif, kualitatif, dan R&D (edisi terbaru). Alfabeta.
Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.
Sekaran, U., & Bougie, R. (2019). Research methods for business: A skill-building approach (8th ed.). John Wiley & Sons.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage Learning.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Arif Disa Putra, Hery Irwan

This work is licensed under a Creative Commons Attribution 4.0 International License.
Copyright:
Authors who publish their manuscripts in this journal agree to the following conditions:
- Copyright in each article belongs to the author.
- The author acknowledges that Greenation International Journal of Engineering Science (GIJES) has the right to be the first to publish under a Creative Commons Attribution 4.0 International license (Attribution 4.0 International CC BY 4.0).
- Authors can submit articles separately, arrange the distribution of non-exclusive manuscripts that have been published in this journal to other versions (for example, sent to the author's institutional repository, publication in books, etc.), acknowledging that the manuscript has been published for the first time in GIJES.
























