Profit optimalization in operation systems

• Autorzy: Knopik L. , Migawa K. , Wdzięczny A.

Identyfikatory

DOI

10.1515/pomr-2016-0013

• Języki publikacji: EN

Abstrakty

EN

The aim of this study is to analyse the effect of reducing the number of secondary damage to profit from the work of a technical object. Considering the criterion function that describes the average profit from the work of a technical object in the operation system. The study analyses a model of profit optimization, in which the design criterion function is based on the properties of Poisson branch process. Criterion function that describes the average gain is considered in the work at sufficiently general factors. Profit lifting model from the work of a technical facility is numerically exemplified. For the analysed electrical subsystem, intervals of time between the initial damage have exponential distribution, and between secondary damage - gamma distribution. In the presented example, the ability of profit optimization in operation systems of technical objects is demonstrated.

Słowa kluczowe

EN

Branching Poisson process; primary failure; secondary failures; gamma distribution; mean profit; hazard function

• Wydawca: Gdańsk University of Technology, Faculty of Ocean Engineering & Ship Technology
• Czasopismo: Polish Maritime Research
• Rocznik: 2016
• Tom: nr 1
• Strony: 93--98
• Opis fizyczny: Bibliogr. 23 poz., rys.

Twórcy

autor

Knopik L.

• Faculty of Management Bydgoszcz University of Science and Technology Fordońska 430 St. 85-790 Bydgoszcz Poland

autor

Migawa K.

• Faculty of Mechanical Engineering, Bydgoszcz University of Science and Technology Prof. S. Kaliskiego 7 St. 85-763 Bydgoszcz Poland

autor

Wdzięczny A.

• Faculty of Mechanical Engineering Bydgoszcz University of Science and Technology Prof. S. Kaliskiego 7 St. 85-763 Bydgoszcz Poland

Bibliografia

• 1. Aitchison, I.: On the distribution of a positive random variable having a discrete probability mass at origin, Journal of the American Statistical Associations, vol. 50, pp. 901−908, 1955
• 2. Bartlett, M. S.: The spectral analysis of point processes, Journal Royal Statistical Society, Series B 25, pp. 264−296, 1963
• 3. Cox, D.R. and Lewis, P.A.W.: The Statistical Analysis of Series of Events, Methuen, NewYork, John Wiley, 1966.
• 4. Deshapande, J. V. and Kochar, S.C.: Aspects in positive ageing, Journal of Applied Probability, 23, pp. 748−758, 1986
• 5. Ghai, G.L. and Mi, J.: Mean residual life and its association with failure rate, IEEE Transactions on Reliability, vol. 48, No. 3, pp. 262−266, 1999
• 6. Girtler, J.: Application of theory of semi-Markov processes to determining distribution of probabilistic process of marine accidents resulting from collision of ships. Polish Martime Research 1(81) 2014, vol.21
• 7. Girtler J., Kitowski Z.:, Kuriata A.: Safety of ship at sea (in Polish), WKiŁ, Warszawa 1995
• 8. Girtler J. : Availability of sea transport means. Archives of Transport, Polish Academy of Sciences Committee of Transport, Quarterly, vol. 9, pp. 3-4, Warsaw 1997
• 9. Girtler J. : Possibility of marine diesel engines. Journal of Polish CIMAC, No. 1 vol. 4, Gdańsk 2009
• 10. Guess, F. and Proschan, F.: Mean Residual Life: Theory and Applications, Handbook of Statistics, Editors: Krishnaiah, P.R. and Rao, C.R., Elsevier Science Publishers, Amsterdam, vol. 7, pp. 215−224, 1988
• 11. Hall, W.J. and Wellner, J.A.: Mean residual life, Statistics and Related Topics, Eds. Csorgo J.N., Rao J.N.K. and Saleh A.K. Md, E., North Holland, Amsterdam, pp. 169−184, 1981
• 12. Jayade, V. P. and Parasad, M. S.: Estimations of parameters of mixed failure time distribution, Communications Statistics, Theory and Method, vol. 19, pp. 4667−4677, 1996
• 13. Kale, B. K. and Muralidharan, K.: Optimal estimating equations in mixture distributions accommodating instantaneous or early failures, Journal Indian Statistical Associations, vol. 38, pp. 317−329, 2000
• 14. Kleyle, R.M. and Dahiyam R.L.: Estimation of parameters of mixed failure time distribution from censored data, Communications Statistics, Theory and Method, vol. 4, pp. 873−882, 1975
• 15. Knopik, L.: Mixture of distributions as a lifetime distribution of a technical object, Scientific Problems of Machines Operation and Maintenance, vol. 45, 2(165), pp. 53−60, 2010
• 16. Knopik, L.: Model for instantaneous failures, Scientific Problems of Machines Operation and Maintenance vol. 46, 2(166), pp. 37−48, 2011
• 17. Knopik, L.: Statistical analysis of failures, Journal of Polish CIMAC, diagnosis, reliability and safety, vol. 7, No. 2, pp. 91−96, 2012
• 18. Knopik, L.: Model of profit improvement in maintenance system, Journal of Polish CIMAC, diagnosis, reliability and safety, vol. 7, No. 2, pp. 91−96, 2013
• 19. Lewis, P.A.W.: A branching Poisson process model for the analysis of computer failure patterns, Journal Royal Statistical Society, B 26, pp. 398−456, 1963
• 20. Muralidharan, K.: Test for mixing proportion in mixture of a degenerate and exponential distributions, Journal Indian Statistical Associations, vol. 37, pp. 105−119, 1999
• 21. Muralidharan, K.: The UMVUE and Bayes estimate of reliability of mixed failure time distribution, Communications Statistics, Simulation Computer, vol. 29, No. 2, pp. 603−158, 2000
• 22. Muralidharan, K. and Kale B.K.: Modified gamma distribution with singularity at zero, Communications Statistics, Simulation Computer, vol. 31, No. 1, pp. 143−158, 2002
• 23. Muralidharan, K. and Lathika, P.: Analysis of instantaneous and early failures in Weibull distribution, Metrika vol. 64, pp. 305−316, 2006

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.