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A random maintenance scheduling model to reduce fault diagnosis time

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  • Pritibhushan Sinha

Abstract

We present a random model for a situation in which some tests of fault detection are to be scheduled to diagnose what type of fault, out of some possible types of faults, has occurred. There are two variants of the model. In the first, the objective is average total diagnosis time. In the second, the objective is a linear combination of average and standard deviation of the diagnosis time, where standard deviation is multiplied with a positive weight. We give an exact solution method for the first case and a heuristic method for the second. A numerical experiment with randomly generated instances is done for the heuristic method. The methods appear to be suitable for practical applications. Copyright Springer Science+Business Media, LLC 2012

Suggested Citation

  • Pritibhushan Sinha, 2012. "A random maintenance scheduling model to reduce fault diagnosis time," Annals of Operations Research, Springer, vol. 201(1), pages 441-447, December.
    • Handle: RePEc:spr:annopr:v:201:y:2012:i:1:p:441-447:10.1007/s10479-012-1180-8
    DOI: 10.1007/s10479-012-1180-8
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    References listed on IDEAS

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    1. Nima Safaei & Dragan Banjevic & Andrew Jardine, 2011. "Workforce-constrained maintenance scheduling for military aircraft fleet: a case study," Annals of Operations Research, Springer, vol. 186(1), pages 295-316, June.
    2. Nawaz, Muhammad & Enscore Jr, E Emory & Ham, Inyong, 1983. "A heuristic algorithm for the m-machine, n-job flow-shop sequencing problem," Omega, Elsevier, vol. 11(1), pages 91-95.
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