Journals / Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi / 2026 / Cilt: 40 Sayı: 2

MTBF Analysis of Systems in Defense Industry

Savunma Sektöründeki Sistemlerin Arızalar Arası Ortalama Süre Analizi

Pages
331–337
Publication Date
2024-08-31
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

On the conclusion of the article; the results are examined and as a result, it is recommended that It can be find out a correction coefficient that would make MIL-HDBK-217F standard better for more reliable MTBF values.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:For high technology working environment Reliability Analysis is done according to many different methodologies such as MIL-HDBK-217F and Telcordia SR-332 in design phase or Weibull Distribution with field data in usage phase.
📊
Key Findings & Data:The objective of this paper is to compare MTBF calculation methods in order to get a methodology for more accurate MTBF values.
💡
Conclusion & Impact:On the conclusion of the article; the results are examined and as a result, it is recommended that It can be find out a correction coefficient that would make MIL-HDBK-217F standard better for more reliable MTBF values.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Güvenilirlik · AAOS Analizi · Güvenilirlik Analizi

Abstract

For high technology working environment Reliability Analysis is done according to many different methodologies such as MIL-HDBK-217F and Telcordia SR-332 in design phase or Weibull Distribution with field data in usage phase. The objective of this paper is to compare MTBF calculation methods in order to get a methodology for more accurate MTBF values. In this article; Mean Time Between Failure (MTBF) values calculated based on MIL-HDBK-217F standard and Weibull Distribution are compared for the systems used Defense Industry. On the conclusion of the article; the results are examined and as a result, it is recommended that It can be find out a correction coefficient that would make MIL-HDBK-217F standard better for more reliable MTBF values.

Özet

Yüksek teknolojili çalışma ortamları için Güvenilirlik Analizi, tasarım aşamasında MIL-HDBK-217F ve Telcordia SR-332 veya kullanım aşamasında saha verileriyle Weibull Dağıtımı gibi birçok farklı metodolojiye göre yapılmaktadır. Bu makalenin amacı, daha doğru Arızalar Arası Ortalama Süre (AAOS) değerleri için bir metodoloji elde etmek amacıyla AAOS hesaplama yöntemlerini karşılaştırmaktır. Bu makalede; Savunma Sanayiinde kullanılan sistemler için MIL-HDBK-217F standardı ve Weibull Dağılımı baz alınarak hesaplanan AAOS değerleri karşılaştırılmıştır. Yazının sonuç kısmında; sonuçlar incelenmiş olup daha güvenilir AAOS değerleri için MIL-HDBK-217F standardını daha iyi hale getirecek bir düzeltme katsayısının bulunabileceği önerilmektedir.

🔖

Cite This Article

Karaköse, G., Çağlar, M., Demir, H., Aksoy, H. K., Aydın, A., Arıcan, U., Kalender, F. Y. (2024). MTBF Analysis of Systems in Defense Industry. Erciyes Üniversitesi Fen Bilimleri Enstitüsü Fen Bilimleri Dergisi, Cilt: 40 Sayı: 2, 331–337. https://ajindex.com/articles/1266728

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (19)

  1. Kimura, M., Yamada, S., Osaki, S., 1995. Statistical Software Reliability Prediction and Its Applicability Based on Mean Time between Failures, Mathematical and Computer Modelling, 149-155.
  2. Wang, H., Pham, H., 1996. Survey of Reliability and Availability Evaluation of Complex Networks Using Monte Carlo Techniques, Microelectronics Reliability, 187-209.
  3. Angus, J.E., 1988. On Computing MTBF for a k-out-of-n: G Repairable System, IEEE Transactions on Reliability, 312-313.
  4. Kumar, U.D., Knezevic, J., Crocker J., 1999. Maintenance free operating period – an alternative measure to MTBF and failure rate for specifying reliability, Reliability Engineering and System Safety, 127-131.
  5. Elerath, J. G., 2000. Specifying Reliability in the Disk Drive Industry: No More MTBF’s. Annual, Reliability and Maintainability Symposium, 198-199.
  6. Dai, Y., Zhou, Y., Jia, Y., 2002. Distribution of time between failures of machining center based on type I censored data, Reliability Engineering and System Safety, 377–379.
  7. Mondro, M. J., 2002. Approximation of Mean Time Between Failure When a System has Periodic Maintenance, IEEE Transactions on Reliability, 166-167.
  8. Carlson, J., Murphy, R. R., Nelson, A., 2004. Follow-up Analysis of Mobile Robot Failures, IEEE International Conference on Robotics 8 Automation, 4987-4994.
  9. Sharma, R.K., Kumar, S., 2008. Performance modeling in critical engineering systems using RAM analysis, Reliability Engineering and System Safety, 913–919.
  10. Juang, Y., Lin, S., Kao, H., 2008. A knowledge management system for series-parallel availability optimization and design, Expert Systems with Applications, 181–193.
  11. Krasich, M., 2009. How to Estimate and Use MTTF/MTBF Would the Real MTBF Please Stand Up?, Annual Reliability and Maintainability Symposium, 353-359.
  12. Wang, J., Fu, C, Yang, K., Zhang, X., Shi, G., Zhai, J., 2013. Reliability and availability analysis of redundant BCHP (building cooling, heating and power) system, Energy, 531-540.
  13. Memon, H.H., Alam, M.M., 2016. Reliability, Maintainability, Availability and Failure rate Analysis of IGBT Triggering System Designed for Marine Environment, 13th International Bhurban Conference on Applied Sciences & Technology, 295-299.
  14. Ferreira, F.J.T.E, 2016. Reliability and Operation of High-Efficiency Induction Motors, IEEE Transactions on Industry Applications, 4628-4637.
  15. Liu,Y., Gusak, A., Jing, S., Tu, K.N., 2022. Fast prediction of electromigration lifetime with modified mean-time- to-failure equation, Materials Letters, 325p.
  16. Duer, S. Woźniak, M., Paś, J., Zajkowski, K., Bernatowicz, D., Ostrowski, A., Budniak, Z., 2023. Reliability Testing of Wind Farm Devices Based on the Mean Time between Failures (MTBF), Energies, 1659p.
  17. McLinn, J.A, 2010. Practical Weibull Analysis Techniques, Fifth Edition.
  18. MIL-217 Military Handbook, 1991. Reliability Prediction of Electronic Equipment, Department of Defense, Washington DC.
  19. Drake, G., Corradi, G., 2020. A Reliability Analysis of the Mu2e Calorimeter Front End Amplifier Board, The Mu2e Project, 1-59.