A Study on System Availability Analysis Utilizing Markov Process

마르코프 프로세스를 활용한 시스템 가용도 분석 방법 고찰

  • Kim, Bohyeon (Department of Mechanical System Engineering, Kumoh National Institute of Technology) ;
  • Kim, Seongkyung (Department of Mechanical System Engineering, Kumoh National Institute of Technology) ;
  • Pagulayan, Dhominick (Department of Mechanical System Engineering, Kumoh National Institute of Technology) ;
  • Hur, Jangwook (Department of Mechanical System Engineering, Kumoh National Institute of Technology)
  • 김보현 (금오공과대학교 기계시스템공학과) ;
  • 김성경 (금오공과대학교 기계시스템공학과) ;
  • ;
  • 허장욱 (금오공과대학교 기계시스템공학과)
  • Received : 2016.08.10
  • Accepted : 2016.10.25
  • Published : 2016.12.25

Abstract

Purpose: This paper presents an application of Markov Process to reliability and availability analysis. In order to do that of analysis, we set up a specific case of Tablet PC and it's usage scenario. The case has it some spares and maintenance and repair processes. Methods: Different configurations of the tablet PC and as well as their functions are defined. The system configuration and calculated failure rates of components are modeled from Windchill Quality Solution. Two models, without a spare and with spare, are created and compared using Markov Process. The Matlab numerical analysis is used to simulate and show the change of state with time. Availability of the system is computed by determining the time the system stays in different states. Results: The mission availability and steady-state condition availability in accordance with the mission are compared and the availability of the system with spares have improved availability than without spares. Simulated data shows that downtime of the system increased which results in greater availability through the consideration of spares. Conclusion: There's many techniques and methods to do reliability and availability analysis and mostly are time-independent assumptions. But Markov Process, even though its steady-state and ergodic properties, can do time analysis any given time periods.

Keywords

References

  1. http://reliawiki.org/index.php/RBDs_and_Analytical_System_Reliability.
  2. http://reliawiki.org/index.php/Fault_Tree_Diagrams_and_System_Analysis.
  3. Practical Guidebook of Reliability Analysis of Weapon System. (2012). "Reliability prediction standards and methods". Republic of Korea Army.
  4. Lee, S. K. (2013). "Reliability and Availability Analysis for UAS by Using Hierarchical Fault Tree and Continuous Time Markov Chain". Department of Computer Engineering, Graduate School of Korea Aerospace University.
  5. Kim, D. M., Choi, Y. H., Seok, J. Y. and Yu, C. S. (2003). "An Investigation on the Reliability of the Flight Control System for an Unmanned Aerial Vehicle". The Korean Society For Aeronautical And Space Sciences, Vol. 11, pp. 1149-1152.
  6. Kim, S. S. and Park, C. B. (2005). "Design for Flight Control System Focused on Reliability". Journal of The Korean Society for Aeronautical and Space Sciences, Vol. 11, pp. 33-40.
  7. Kim, J. H. and Lyou, J. (1999). "A computation method of reliability for preprocessing filters in the fire control system using Markov process and state transition probability matrix". The Korea Institute of Military Science and Technology, Vol. 2, No. 2, pp. 131-139.
  8. Hoang, Y. J. and Shin, D. J. (2016). "A Study on Elementary School Teachers' Recognition for Using Tablet PC in Art Class". Journal of are education, Vol. 44, pp. 247-263.
  9. Oliver Ibe. (2013). "Markov Processes For Stochastic Modeling 2nd Edition". Elsevier.
  10. MIL-HDBK-217F. (1965). Military Handbook, Reliability Prediction of Electronic Equipment, Department of Defense.
  11. MIL-HDBK-217F Notice 2. (1995). Military Handbook, Reliability Prediction of Electronic Equipment, Department of Defense.
  12. NPRD. (2016). Reliability Databook Series(failure data for a wide variety of component types), QUANTERION.