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Models to Deal with Maintenance Scheduling Issues

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Book cover The Maintenance Management Framework

Part of the book series: Springer Series in Reliability Engineering ((RELIABILITY))

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14.5 References

  1. Duffua SO, Raouf A, Campbell JD, (2000) Planning and control of maintenance systems: Modelling and analysis. New York: John Wiley and Sons.

    Google Scholar 

  2. Chase RB, Aquilano NJ, (1977) Production and operations management. A life cycle approach. Homewood, Illinois: Irwin.

    Google Scholar 

  3. Chang LY, (2002) WinQSB: Software and manual, Version 2.0. New York: John Wiley and Sons.

    Google Scholar 

  4. Liu J, Rahbar F, (2004) Project time-cost trade-off optimization by maximal flow theory. Journal of Constuction Engineering and Management, 130(4): 607–609.

    Article  Google Scholar 

  5. Ford LR, Fulkerson DR, (1962) Flows in networks. Princeton, NJ: Princeton Univ. Press.

    MATH  Google Scholar 

  6. Hoyland A, Rausand M, (1995) System reliability theory. Models and statistical methods. New York: John Wiley and Sons Inc.

    Google Scholar 

  7. Pidd M, (2003) Tools for thinking. Modelling in Management Science. 2nd. Edition. Chichester, England: Wiley.

    Google Scholar 

  8. Marseguerra M, Zio E, (2002) Basics of the Monte Carlo method with applications to system reliability. Hagen, Germany: LiLoLe-Verlag GmbH.

    Google Scholar 

  9. Chen F, Drezner Z, Ryan JK, Simichi-Levy D, (1999) The bullwhip effect: managerial insights on the impact of forecasting and information on variability in a supply chain. In: Mayur, Ganeshan and Magazine (Eds.) Quantitative models for SCM. International Series in Operations Research and Management Science, 17: 419–439.

    Google Scholar 

  10. Sanders NR, (1994) Forecasting practices in United-States corporations. Survey results. Interfaces, 24(2): 92–100.

    Google Scholar 

  11. Makridakis S, Wheelwright S, Hyndman R, (1998) Forecasting methods and applications. New York: John Wiley and Sons.

    Google Scholar 

  12. Evers PT, (1999) The effect of lead times on safety stocks. Production and Inventory Management Journal, 40(2): 6–10.

    Google Scholar 

  13. Tersine RJ, (1994) Principles of Inventory and Materials management. 4th. Edition. Englewood Cliffs. NJ. Prentice-Hall.

    Google Scholar 

  14. Aucamp DC, Barringer RL, (1987) A table for the calculation of safety stock. Journal of Operations Management, 7: 153–163.

    Article  Google Scholar 

  15. Tversky A, Kahneman D, (1974) Judgment under uncertainty. Heuristics and biases. Science, 185: 1124–1131.

    Article  Google Scholar 

  16. Sterman JD, (1989) Modelling managerial behaviour: Misperceptions of feedback in a dynamic decision making experiment. Management Science, 35(3): 321–339.

    Article  Google Scholar 

  17. Dohi T, Kaio N, Osaki S, (2000) Basic preventive maintenance policies and their variations. In: Ben-Daya M, Duffuaa SO, Raouf A, (Eds.) Maintenance Modelling and Optimization, 155–183. Boston: Kluwer Academic Publishers.

    Google Scholar 

  18. Van der Duyn Schouten FA, Vanneste SG, (1995) Maintenance optimization of a production system with buffer capacity. European Journal of Operations Research, 82:323–338.

    Article  MATH  Google Scholar 

  19. Lacksonen T, (2001) Empirical comparison of search algorithms for discrete event simulation. Computers and Industrial Engineering, 40(1–2): 133–148.

    Article  Google Scholar 

  20. Bengu G, Haddock J, (1984) A generative simulation-optimization system. Computers and Industrial Engineering, 10: 301–313.

    Article  Google Scholar 

  21. Nelder JA, (1965) A simplex method for function minimization. Computer Journal, 7:308–313.

    MATH  Google Scholar 

  22. Glover F, (1986) Future paths for integer programming and links to artificial intelligence. Computers and Operations Research, 5: 533–549.

    Article  MathSciNet  Google Scholar 

  23. Aarts E, Lenstra JK, (1997) Local search in combinatorial optimization. Chichester, England: Wiley.

    MATH  Google Scholar 

  24. Kirpatrick S, Gelatt CD, Vecchi MP, (1983) Optimization by simulated annealing. Science, 221: 671–680.

    Article  Google Scholar 

  25. Goldberg DE, Deb K, (1991) A comparative analysis of selection schemes used in genetic algorithms. Foundations of Genetics Algorithms, 1: 69–93.

    MathSciNet  Google Scholar 

  26. Powell MJD, (1964) An efficient method for finding the minimum of a function of several variables without calculating derivatives. Computer Journal, 7(2): 155–62.

    Article  MATH  MathSciNet  Google Scholar 

  27. Ventana System Inc, (2006) VENSIM: Ventana simulation environment. Version 5.6. Cambridge, MA.

    Google Scholar 

  28. Okamotoa M, Nonakaa T, Ochiaia S, Tominagaa D, (1998) Nonlinear numerical optimization with use of a hybrid genetic algorithm incorporating the modified Powell method. Applied Mathematics and Computation, 91(1): 63–72.

    Article  MathSciNet  Google Scholar 

  29. Coleman BJ, (2000) Determining the correct service level target. Production and Inventory management Journal, 41(2): 19–23.

    Google Scholar 

  30. Ignizio JP, (1976) Goal programming and extensions. Lexington, MA: Lexington Books.

    Google Scholar 

  31. Saaty TL, (1990) How to make a decision. The analytic hierarchy process. European Journal of Operational Research, 48: 9–26.

    Article  MATH  Google Scholar 

  32. Crespo Marquez A, Gupta JND, Sánchez Herguedas A, (2003) Maintenance policies for a production system with constrained production rate and buffer capacity. International Journal of Production Research. 41(9): 1909–1926.

    Article  MATH  Google Scholar 

  33. Crespo Marquez A, Gupta JND, Ignizio J, (2006) Improving preventive maintenance scheduling in semiconductor fabrication facilities. Production Planning and Control. 17(7): 742–754.

    Article  Google Scholar 

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© 2007 Springer-Verlag London Limited

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(2007). Models to Deal with Maintenance Scheduling Issues. In: The Maintenance Management Framework. Springer Series in Reliability Engineering. Springer, London. https://doi.org/10.1007/978-1-84628-821-0_14

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  • DOI: https://doi.org/10.1007/978-1-84628-821-0_14

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-84628-820-3

  • Online ISBN: 978-1-84628-821-0

  • eBook Packages: EngineeringEngineering (R0)

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