ELEKTRİK MOTORLARINDA UYGULANAN BAKIM YÖNTEMLERİNİN İNCELENMESİ, KARŞILAŞTIRILMASI VE UZAKTAN ERİŞİMİN KESTİRİMCİ BAKIMA ETKİSİ

Year 2020, , 889 - 905, 01.12.2020

Abdülsamed Tabak , Prof. Dr. Mehmet Özkaymak

https://doi.org/10.36306/konjes.750404

Abstract

Sanayi devriminden günümüze kadar gelinen süreçte tüketici talepleri sürekli artmış ve bu talebi karşılamak adına üreticiler yeni arayışlar içerisine girmiştir. Buna bağlı olarak üretimdeki devamlılığın sağlanması için ekipmanlara daha fazla değer verilmiş, ekipmanlardaki arıza ve duruş istenmez hale gelmiş ve bakım yöntemlerine duyulan ilgi artmıştır. Özellikle endüstride üretimin kalbi niteliğindeki elektrik motorlarında uygulanan bakım yöntemleri ilk zamanlardan beri sürekli geliştirilmiş ve en uygun bakım yöntemi her zaman aranmıştır. Çalışmamızda sanayideki elektrik motorları üzerinde yapılan bakımlar ilkelden gelişmişe doğru sınıflandırılmış ve irdelenmiştir. Bu bakım yöntemleri hem maddi açıdan hem de birtakım avantaj/dezavantajları açısından birbirleri ile karşılaştırılarak uygulamada teknik personel için en uygun bakım yönteminin seçimi hakkında bilgi verilmiştir. Ardından, durum bazlı bakım olarak da bilinen kestirimci bakım yönteminin en yaygın kullanılan teknikleri irdelenmiştir. Bunların yanında internet ve uzaktan erişim sistemlerinin kestirimci bakıma olan katkısı incelenmiş ve bakımın önemi her açıdan ortaya konmuştur.

Keywords

Elektrik motorlarında bakım, Kestirimci bakım, Bakım yöntemlerinin karşılaştırılması, Uzaktan erişim

The Investigation and Comparison of Maintenance Methods Applied In Electric Motors and The Effect Of Remote Access To Predictive Maintenance

Abstract

In the period from the industrial revolution to the present day, consumer demands have continuously increased and manufacturers have been in search of new products to meet this demand.
Therefore, more value was given to equipment to ensure continuity in production, fault and downtime in equipment became undesirable, and interest in maintenance methods increased. Especially in the industry, the maintenance methods applied in electric motors, which are the heart of production, have been continuously improved since the early days and the most appropriate maintenance method has always been sought. In our study, the maintenance performed on the electric motors in the industry was classified from primitive to advanced and examined. These maintenance methods were compared with each other both financially and in terms of a number of advantages/disadvantages, and information was given about the selection of the most appropriate maintenance method for technical personnel in practice.
The most commonly used techniques of the predictive maintenance method, also known as condition- based maintenance, were discussed. In addition, the contribution of internet and remote access systems to predictive maintenance were examined and the importance of maintenance were demonstrated in every respect.

Keywords

Maintenance of electric motors, Predictive maintenance, Comparison of maintenance methods, Remote access

References

• Ahmad, R., & Kamaruddin, S. (2012). An overview of time-based and condition-based maintenance in industrial application. Computers and Industrial Engineering, 63(1), 135–149. https://doi.org/10.1016/j.cie.2012.02.002 Barnish, T. J., Muller, M. R., & Kasten, D. J. (1997). Motor maintenance: A survey of techniques and results. Proceedings ACEEE Summer Study on Energy Efficiency in Industry, 287–297.
• Bauer, B., Geropp, B., & Seeliger, A. (1997). Condition Monitoring and Predictive Maintenance in Mining Industry Using Vibration Analysis for Diagnosis of Gear Boxes. IFAC Proceedings Volumes, 30(18), 989–992. https://doi.org/10.1016/s1474-6670(17)42529-8
• Börjesson, A., & Svensson, A. (2011). Critical equipment classification and cost reduction within professional maintenance. 1–115.
• Brown, P., & Sondalini, M. (2015). Asset maintenance management - The path toward defect elimination. Lifetime Reliability Solutions, 3.
• Buckley, J. M. (2007). AN OVERVIEW OF THE PREDICTIVE MAINTENANCE APPLICATIONS OF AIRBORNE ULTRASOUND TESTING . INTRODUCTION A Note on Terminology Principles of Operation. 4th IInternational Conference on NDT.
• Crespo Márquez, A. (2007). The Maintenance Management Framework. The Maintenance Management Framework. https://doi.org/10.1007/978-1-84628-821-0 Duyar, A. (2009). Model Bazli Ariza Analizi ve Kestirimci Bakim. Mühendis ve Makina, 50(598), 1–9.
• Duyar, A., Önel, İ. Y., & Özdemir, H. (2016). İnovatif Model Bazlı Arıza Erken Uyarı Yazılımıyla Beklenmedik Duruşlara Son Verme. Mühendis ve Makina, 57(672), 44–48.
• Enerji Verimliliği ve Çevre Dairesi Başkanlığı, “EnVer Motor Hareketi,” TC Enerji ve Tabii Kaynaklar Bakanlığı. [Online]. Available: http://www.yegm.gov.tr/verimlilik/b_en_mot_ hareketi.aspx. [Accessed: 08-Apr-2020].
• Geitner, F. K., & Bloch, H. P. (2012). Machinery Failure Analysis And Troubleshooting, Practical Machinery Management for Process Plants. TX, USA: Butterworth-Heinemann.
• Goyal, D., & Pabla, B. S. (2015). Condition based maintenance of machine tools-A review. CIRP Journal of Manufacturing Science and Technology, 10, 24–35. https://doi.org/10.1016/j.cirpj.2015.05.004
• Gresham, R. M., & Totten, G. E. (2009). Lubrication and Maintenance of Industrial Machinery: Best Practices and Reliability. London: CRC Press, Taylor & Francis Group.
• Gun, B., Jae, W., Huang, A., Sutherland, J. W., Jae, W., & Sutherland, W. (2020). Development and Application of a Method for Real Time Motor Fault Detection. Procedia Manufacturing, 49, 94–98. https://doi.org/10.1016/j.promfg.2020.07.002 Huda, A. S. N., & Taib, S. (2013).
• Application of infrared thermography for predictive/preventive maintenance of thermal defect in electrical equipment. Applied Thermal Engineering, 61(2), 220–227. https://doi.org/10.1016/j.applthermaleng.2013.07.028
• Jadin, M. S., & Taib, S. (2012). Recent progress in diagnosing the reliability of electrical equipment by using infrared thermography. Infrared Physics and Technology, 55(4), 236–245. https://doi.org/10.1016/j.infrared.2012.03.002
• Jardine, A. K. S., Lin, D., & Banjevic, D. (2006). A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing, 20(7), 1483– 1510. https://doi.org/10.1016/j.ymssp.2005.09.012
• Kirazlılar, B. (2007). Endüstriyel Bakım: Kestirimci Bakım ve Önleyici Bakımın Temelleri ve Ustalarına Pratik Metotları. İstanbul: Birsen Yayınevi.
• Klutke, G. A., Kiessler, P. C., & Wortman, M. A. (2003). A critical look at the bathtub curve. IEEE Transactions on Reliability, 52(1), 125–129. https://doi.org/10.1109/TR.2002.804492 Lee, J., & Wang, B. (1999). Computer Aided Maintenance (p. 7). p. 7. New York: Springer.
• Levitt, J. (2011). Complete Guide to Preventive and Predictive Maintenance. New York: Industrial Press Inc. Lin, C. C., & Tseng, H. Y. (2005).
• A neural network application for reliability modelling and condition- based predictive maintenance. International Journal of Advanced Manufacturing Technology, 25(1–2), 174–179. https://doi.org/10.1007/s00170-003-1835-3
• Martin, K. F. (1994). A review by discussion of condition monitoring and fault diagnosis in machine tools. International Journal of Machine Tools and Manufacture, 34(4), 527–551. https://doi.org/10.1016/0890- 6955(94)90083-3
• Mehala, N., & Dahiya, R. (2007). Motor Current Signature Analysis and its Applications in Induction. International Journal, 2(1), 29–35.
• Mergen, F., & Zorlu, S. (2009). Elektrik Makineleri 2 Asenkron Makineler. İstanbul: Birsen Yayınevi. NASA. (2000).
• Reliability Centered Maintenance Guide for Facilities and Collateral Equipment. Washington, D.C. Nowlan, F. S., & Heap, H. F. (1978).
• Reliability-Centered Maintenance. United Airlines and Dolby Press, sponsored and published by the Office of Assistant Secretary of Defense.
• Onawoga, D. T., & Akinyemi, O. O. (2010). Development of Equipment Maintenance Strategy for Critical Equipment . Pacific Journal of Science and Technology, 11(1), 328–342.
• Piotrowski, J. (n.d.). Effective Predictive and Pro-Active Maintenance for Pumps. Retrieved April 8, 2020, from http://www.maintenanceworld.com/effective-predictive-and-pro-active-maintenance-for- pumps/
• Scheffer, C., & Girdhar, P. (2004). Practical Machinery Vibration Analysis and Predictive Maintenance. https://doi.org/http://dx.doi.org/10.1016/B978-075066275-8/50001-1
• Selcuk, S. (2017). Predictive maintenance, its implementation and latest trends. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 231 (9), 1670-1679. https://doi.org/10.1177/0954405415601640
• Singh, G., Anil Kumar, T. C., & Naikan, V. N. A. (2019). Efficiency monitoring as a strategy for cost effective maintenance of induction motors for minimizing carbon emission and energy consumption.
• Reliability Engineering and System Safety, 184 (February 2018), 193-201. https://doi.org/10.1016/j.ress.2018.02.015
• Singh, S., Kumar, A., & Kumar, N. (2014). Motor Current Signature Analysis for Bearing Fault Detection in Mechanical Systems. Procedia Materials Science, 6(Icmpc), 171-177. https://doi.org/10.1016/j.mspro.2014.07.021
• Sullivan, G. P., Pugh, R., Melendez, A. P., & Hunt, W. D. (2010). Operations & Maintenance Best Practices: A Guide to Achieving Operational Efficiency. Federal Energy Management Program, (August 2010), 321. https://doi.org/10.2172/1034595
• Sullivan, G., Pugh, R., Melendez, A., & Hunt, W. (2002). Best Practices A Guide to Achieving Operational Efficiency.
• Tabak, A. (2014). Ekipmanlarda Kestirimci Bakım Teknolojilerinin Araştırılması Ve Seçilen Bir Yöntemin Uygulandığı Sanayi Tesisinde Elde Edilen Neticelerin İrdelenmesi. Karabük Üniversitesi.
• Tabak, A. (2020). Fırçasız Doğru Akım Motor larının Hız Kontrolünü Gerçekleştirmek İçin PID / PD Kontrolcü Tasarımı ve Performans İncelemesi. Avrupa Bilim ve Teknoloji Dergisi, (19), 145-155. https://doi.org/10.31590/ejosat.707004
• TERZİOĞLU, H., & SELEK, M. (2017). Determination of Equivalent Circuit Parameters of Induction Motors By Using Heuristic Algorithms. Selcuk University Journal of Engineering ,Science and Technology, 5(2), 170-182. https://doi.org/10.15317/scitech.2017.80
• Thomas, J. (2007). A History of Maintenance: Implementing MP2 (Western Kentucky University). Retrieved from http://digitalcommons.wku.edu/stu_hon_theseshttp://digitalcommons.wku.edu/stu_hon_theses/14 1%0Ahttp://digitalcommons.wku.edu/stu_hon_theses/141/
• TÜİK. (2019). Net Elektrik Tüketiminin Sektörlere Göre Dağılımı, Türkiye İstatistik Kurumu, Ankara.
• UGECHI, C. I., OGBONNAYA, E. A., LILLY, M. T., OGAJI, S. O. T., & PROBERT, S. D. (2009). ConditionBased Diagnostic Approach for Predicting the Maintenance Requirements of Machinery. Engineering, 01(03), 177-187. https://doi.org/10.4236/eng.2009.13021
• Verimlilik Genel Müdürlüğü (2015). Elektrik Motorlarında Enerji Verimliliği, T.C. Bilim, Sanayi ve Teknoloji Bakanlığı Ankara.
• Waide, P., & Brunner, C. U. (2011). Energy-Efficiency Policy Opportunities for Electric Motor-Driven Systems. Paris, France.
• Wakiru, J. M., Pintelon, L., Muchiri, P. N., & Chemweno, P. K. (2019). A review on lubricant condition monitoring information analysis for maintenance decision support. Mechanical Systems and Signal Processing, 118, 108-132. https://doi.org/10.1016/j.ymssp.2018.08.039
• Wyrwas, E., Condra, L., & Hava, A. (2011). Accurate quantitative physics-of-failure approach to integrated circuit reliability. IPC APEX EXPO Technical Conference 2011, 3(August), 1776-1815.