Estimating the Reliability of Commercial Products in a Military Operational Environment Utilizing Field Data

사용현장 데이터를 이용한 군 운용 환경에서의 상용품목 신뢰도 예측

  • 임태진 (숭실대학교 공과대학 산업.정보시스템공학과) ;
  • 박준수 (한국국방연구원 국방획득연구센터, 숭실대학교 대학원) ;
  • 고병성 (한국국방연구원 국방획득연구센터, 숭실대학교 대학원) ;
  • 성인철 (국방기술품질원 품질경영본부) ;
  • 조문수 (숭실대학교 공과대학 산업.정보시스템공학과) ;
  • 김성철 (숭실대학교 자연과학대학 정보통계.보험수리학과)
  • Received : 2010.01.29
  • Accepted : 2010.04.13
  • Published : 2010.04.30

Abstract

Adapting commercial equipments to military operations may provide the advantage of low cost, reduced acquisition time, and technology advancement. On the other hand, it may also offer the opportunity for a reliability and logistics risk because commercial products, standards, and practices may not meet military requirements. In addition to this, commercial vendors have little experience in providing the technical data required to support military deployment logistics. As more companies are equipped with data aquisition systems for their products, considerable amount of field warranty data has been accumulated. Typically, the field data for a given product comprise with the sales volume and the number of the claims for each period. Three types of product data are considered in this study: military designed equipment operating in a military environment, commercial equipment operating in a military environment, and commercial equipment operating in a commercial environment. We construct a estimation model for each type of data and propose an reliability transform method from a commercial environment to a military environment. Parametric methods for estimating the product reliability are proposed based on maximum likelihood criteria and least square criteria. Then a reliability transform procedure for handling different types of data is proposed in a consistent fashion. A case study is investigated to characterize our model based on a real field warranty data set.

상용품목을 군용환경에서 적용하면 저비용, 빠른 조달시간, 기술적 발전 등 여러 가지 이점이 있다. 반면에 상용 제품, 표준, 관행 등이 군용 요구조건에 미달됨으로 인하여 신뢰도 및 병참 상의 문제가 발생할 수도 있다. 또한 상용 공급자들은 군용 병참을 지원하는데 필요한 기술적 자료를 제공한 경험이 거의 없을 수도 있다. 보다 많은 회사들이 제품 관련 데이터 수집 시스템을 구축하고 있어 상당한 분량의 사용현장 보증 데이터가 수집되었다. 사용현장 데이터는 전형적으로 주기별 판매량과 클레임 건수로 구성된다. 본 연구에서는 군용환경에서 작동하는 군용설비, 군용환경에서 작동하는 상용설비, 상용환경에서 작동하는 상용설비 등 세 가지 유형의 데이터를 고려하였다. 최대우도 기준 및 최소제곱 기준에 기초한 제품 신뢰도 추정 방법을 제안하고, 각 유형의 데이터에 대한 추정 모형을 구축하고 상용환경에서 군용환경으로 전환하는 신뢰도 변환방법을 제안하였다. 사례연구를 통하여 제안된 방법의 적용 가능성을 검증하였다.

Keywords

Acknowledgement

Supported by : 국방기술품질원

References

  1. Attardi, L., Guida, M., and Pulcini, G., "A Mixed-Weibull Regression Model for the Analysis of Automotive Warranty Data," Rel. Eng & Sys. Safety, 87, pp.265-273, 2005. https://doi.org/10.1016/j.ress.2004.05.003
  2. Baxter, L. A., "Estimation from Quasi Life Tables," Biometrika, 81(3), pp.567-577, 1994. https://doi.org/10.1093/biomet/81.3.567
  3. Blischke, W. R. and Murthy, P., Case Studies in ReliabiIity and Maintenance, Ch.27, Wiley, 2003.
  4. Coit, D. W. and Dey, K. A., "Analysis of Grouped data from Field-Failure Reporting Systems," Rel. Eng & Sys. Safety, 65, pp.95-101, 1999. https://doi.org/10.1016/S0951-8320(98)00089-1
  5. Demko, E., "Commercial-Off-The Shelf (COTS): A Challenge To Military Equiprnent Reliability," RAMS, pp.7-12, 1996.
  6. Dempster, A. P., Laird, N. M., and Rubin, D. B., "Maximum LikeIihood from Incomplete Data via the EM Algorithm," Journal of Royal Statistical Society, Series B, 39, pp.1-22, 1977.
  7. Jung, M. and Bai, D. S., "Analysis of Field Data under Two-Dimensional Warranty," Rel. Eng & Sys. Safety, 92, pp.135-143, 2007.
  8. Kalbfleisch, J. D., and Lawless, J. F., "Estimation of Reliability in Field-Performance Studies," Technometrics, 30(4), pp.365-378, 1988. https://doi.org/10.2307/1269797
  9. Kalbfleisch, J. D., Lawless, J. F., and Robinson, J. A., "Methods for the Analysis and Prediction of Warranty Claims," Technometrics, 33(3), pp.273-285, 1991. https://doi.org/10.2307/1268780
  10. Kaplan, E. and Meier, P., "Nonparametric Estimation from Incomplete Observation," Jour. Amer. Statist. Assoc., 53, pp.457-481, 1958. https://doi.org/10.2307/2281868
  11. Karim, M. R , Yamamoto, W., and Suzuki, K., "Statistical Analysis of Marginal Count Faiolure Data," Lifetime Data Analysis, 7(2), pp.173-186, 2001. https://doi.org/10.1023/A:1011300907152
  12. Lawless, J. F., "Statistical Method in Reliability," Technometrics, 25, pp.305-335, 1983. https://doi.org/10.2307/1267846
  13. Lim, T., "Estimation of Product Reliability with Incomplete Field Warranty Data," Jour. Korean Ins. Ind. Eng., 28(4), pp.368-378, 2002.
  14. Lim, T., "Nonparametric Estimation of the Product Reliability from Grouped Warranty Data, with Unknown Start-up Time," Int. Jour. Ind. Eng., 10(4), pp.474-481, 2003.
  15. Mohan, K., Cline, B., and Akers, J., "A Practical Method for Failure Analysis Using Incomplete Warranty Data," RAMS, 2008.
  16. Oh, Y. S. and Bai, D. S., "Field Data Analysis with Additional After-Warranty Failure Data," Rel. Eng & Sys. Safety, 72, pp.1-8, 2001. https://doi.org/10.1016/S0951-8320(00)00056-9
  17. SRC, Reliability Prediction Environmental Conversion Matrix
  18. Suzuki., "Estimation of Lifetime Parameters from Incomplete Field Data," Technometrics, 27(3), pp.263-271, 1985. https://doi.org/10.2307/1269707
  19. Suzuki, K., "Nonparametric Estimation of Lifetime Distributions from a Record of Failurles and Follow-ups," Journal Amer. Statistical Assoc. 80, pp.68-72, 1985. https://doi.org/10.2307/2288041
  20. Tortorella, M., "Life Estimation from Pooled Discrete Renewal Counts," in N. P. Jewell et al. (eds.) Lifetime Data: Models in Reliability and Survival Analysis, pp.331-338, 1996.
  21. Yang, G., Life Cycle Reliability Engineering, Ch. 11, Wiley, 2007.