Achieving growth in reliability

Annals of Operations Research

Volumn 91, Issue , 1999, Pages 11-24

  Ansell, Jake ^a   Walls, Lesley ^b   Quigley, John ^b  

^a UNIVERSITY OF EDINBURGH   (United Kingdom)

^b UNIVERSITY OF STRATHCLYDE   (United Kingdom)

Author keywords

Bayesian statistics; Data analysis; Importance measures; Innovation; Monte Carlo Markov chains; Reliability growth

Indexed keywords

EID: 0033471658     PISSN: 02545330     EISSN: 15729338     Source Type: Journal    
DOI: 10.1023/a:1018985303897     Document Type: Article

References (49)

1. J.I. Ansell and M.J. Phillips, Practical problems in the statistical analysis of reliability data (with discussion), Appl. Stat. 38(1989)205-247.
2. J.I. Ansell and M.J. Phillips, Practical Methods for Reliability Data Analysis, Oxford University Press, 1994.
3. J.I. Ansell, J.L. Quigley and L.A. Walls, Growth and innovation, in: Stochastic Modelling in Innovative Manufacturing, eds. A.H. Christer, S. Osaki and L.C. Thomas, Springer, 1997.
4. H. Ascher and H. Feingold, Repairable Systems Reliability, Marcel Dekker, New York, 1984.
5. R. Baker, Software reliability growth model for discrete and incomplete testing, in: Stochastic Modelling in Innovative Manufacturing, eds. A.H. Christer, S. Osaki and L.C. Thomas, Springer, 1997.
6. R.E. Barlow and F. Proschan, Statistical Theory of Reliability, Wiley, 1975.
7. G. Bhattacharyya, A. Fries and R. Johnson, Properties of continuous analog estimators for a discrete reliability-growth model, IEEE Trans. Reliab. R-38(1989)373-378.
8. BS5760, Part 6, Reliability of Systems, Equipment and Components: Guide to Programmes for Reliability Growth, 1991.
9. S. Campodinico and N.D. Singpurwalla, Inference and prediction from Poisson point process incorporating expert judgement, J. Amer. Statist. Assoc. 90(1995)220-226.
10. A. Cowling, P. Hall and M.J. Phillips, Bootstrap confidence regions for the intensity of a Poisson point process, J. Amer. Statist. Assoc. 90(1996)1516-1524.
11. L.H. Crow, Reliability analysis for complex repairable systems, in: Reliability and Biometry, eds. F. Proschan and R.J. Serfling, SIAM, 1974.
12. L.H. Crow, Confidence interval procedures for the Weibull process with application to reliability growth, Technometrics 24(1982)251-256.
13. J.T. Duane, Learning curve approach to reliability monitoring, IEEE Trans. Aerospace 2(1964)563-566.
14. N. Ebrahimi, How to model the growth when times of design modifications are known, IEEE Trans. Reliab. R-45(1996)54-58.
15. N. Ford and D. Dietrich, A Bayes reliability growth model for a development testing program, IEEE Trans. Reliab. R-36(1987)568-572.
16. J. Finkelstein, Starting and limiting values for reliability growth, IEEE Trans. Reliab. R-28(1979) 111-114.
17. E.H. Forman and N.D. Singpurwalla, An empirical stopping rule for debugging and testing computer software, J. Amer. Statist. Assoc. 72(1977)750-757.
18. W.R. Gilks, S. Richardson and D.J. Spiegelhalter, Monte Carlo Markov Chains in Practice, Chapman and Hall, 1996.
19. J. Gittins, Algorithm for allocating resources to multi-stage pharmaceutical research project, in: Stochastic Modelling in Innovative Manufacturing, eds. A.H. Christer, S. Osaki and L.C. Thomas, Springer, 1997.
20. A. Goel, Software reliability models: Assumptions, limitations and applicability, IEEE Trans. Software Engineering SE-11(1985)1411-1423.
21. P. Gottfried, Some aspects of reliability growth, IEEE Trans. Reliab. R-36(1987)11-16.
22. J. Higgins and C. Tsokos, A quasi-Bayes estimate of the failure intensity of a reliability-growth model, IEEE Trans. Reliab. R-30(1981)471-475.
23. A. Hoyland and M. Rausand, System Reliability Theory, Wiley, 1994.
24. IEC 1164, Reliability Growth - Statistical Tests and Estimation Methods, 1995.
25. Z. Jelinski and P. Moranda, Software reliability research, in: Statistical Computer Performance Evaluation, ed. W. Freiburger, Academic Press, 1972.
26. W.A. Jewell, General framework for learning curve reliability growth models, Operations Research 32(1984)547-558.
27. W.A. Jewell, Bayesian extensions to a basic model of software reliability, IEEE Trans. Software Engineering SE-11(1985) 1465-1471.
28. N. Kareer, P. Kapur and P. Grover, An S-shaped software reliability growth model with two types of errors, Microelectronic Reliability 301990)1085-1090.
29. H. Langseth and J. Vatn, A model for predicting failure rates for equipment subject to improvements, presented at SINTEF Safety and Reliability in Industrial Management Conference, Trondheim, 1996.
30. B. Littlewood and A. Verral, Bayesian reliability growth model for computer software, Appl. Stat. 22(1973)332-346.
31. B. Littlewood, Rationale for a modified Duane model, IEEE Trans.Reliab. R-33(1984)157-159.
32. T. Mazzuchi and R. Soyer, A Bayes empirical-bayes model for software reliability, IEEE Trans. Reliab. R-37(1988)248-254.
33. T. Mazzuchi and S. Soyer, A Bayes method for assessing product reliability during development testing, IEEE Trans. Reliab. R-42(1993)503-510.
34. R. Meinhold and N. Singpurwalla, Bayesian analysis of a commonly used model for describing software failures, The Statistician 32(1983)168-173.
35. P.D.T. O'Connor, Practical Reliability Engineering, Wiley, 1991.
36. U.D. Perera, Reliability growth models and their application to a processor, Proc. 12th ARTS, ed. P. Comer, Elsevier Applied Science, 1990, pp. 86-102.
37. J.L. Quigley, Managing information from reliability growth test programme, unpublished Ph.D. Dissertation, Department of Management Science, University of Strathclyde, Glasgow, 1998.
38. J.L. Quigley, L.A. Walls and E. MacArthur, Reliability growth analysis of complex electronic systems, Proceedings of the ESREL '95 Conference, Bournemouth, 1995, pp. 175-189.
39. J.L. Quigley, L.A. Walls, J.M. Marshall and E. MacArthur, Practical issues concerning the elicitation of prior distributions for Bayesian reliability growth models, Proc. ARTS 12, Manchester University, 1996.
40. J.L. Quigley and L.A. Walls, Learning from failures, EURO Conference, Barcelona, 1997.
41. D. Robinson and D. Dietrich, A new non-parametric growth model, IEEE Trans. Reliab. R-36 (1987)411-418.
42. D. Robinson and D. Dietrich, A non-parametric-Bayes reliability growth model, IEEE Trans. Reliab. R-38(1989)591-598.
43. N.D. Singpurwalla and R. Soyer, Non-homogeneous autoregressive processes for tracking (software) reliability growth and their Bayesian analysis, J. Roy. Statist. Soc. B54(1992)145-156.
44. N.D. Singpurwalla and S.P. Wilson, Software reliability modelling, Int. Statist. Rev. 62(1994)289-317.
45. R.M. Sinnamon and J.D. Andrews, Improved accuracy in quantitative fault tree analysis, Proc. ARTS 12, Manchester University, 1996.
46. L.A. Walls and J.L. Quigley, Eliciting prior distributions from engineering experts to support Bayesian reliability growth modelling, Working Paper, Department of Management Science, University of Strathclyde, Glasgow, 1998.
47. M. Xie, Software reliability models - a selected annotated bibliography, Software Testing, Verification and Reliability 3(1993)3-28.
48. M. Xie and M. Zhao, On some reliability growth models with simple graphical interpretations, Microelectronic Reliability 33(1993)149-167.
49. S. Yamada and S. Osaki, Software reliability growth modelling: Models and applications, IEEE Trans. Software Engineering SE-11(1985)1431-1437.