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A stochastic reward net approach for reliability analysis of a flexible manufacturing module

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Abstract

The machines and robots in a flexible manufacturing module (FMM) are more prone to failures as compared to the traditional manufacturing systems. The failures due to wear and tear of the machine components can be eliminated by properly scheduling the preventive maintenance operations but the failures due to random causes are unpredictable and cannot be eliminated. A corrective maintenance strategy is necessary to deal with such failures and due to these failures a lot of production time is lost. Keeping in mind the higher initial investments required in acquiring the FMM systems it is necessary to study the effect of the system reliability in system performance. Markov models have been used extensively for such studies but in many cases the system designer or reliability engineer faces a major difficulty in transforming the problem into a Markov chain due to the huge state space associated with the models. To this effect the authors of this paper make use of a higher class of Petri nets called stochastic reward nets (SRNs) to model and analyze the FMM system. The use of SRNs helps in combining the modeling power of Petri nets and analytical tractability of Markov processes for carrying out the reliability analysis of the FMM.

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Authors and Affiliations

  1. Department of Mechanical Engineering, National Institute of Technology, Hamirpur, Hamirpur, 177005, India

    Ajay Philip & Rajiv Kumar Sharma

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  1. Ajay Philip
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  2. Rajiv Kumar Sharma
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Correspondence to Ajay Philip.

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Philip, A., Sharma, R.K. A stochastic reward net approach for reliability analysis of a flexible manufacturing module. Int J Syst Assur Eng Manag 4, 293–302 (2013). https://doi.org/10.1007/s13198-013-0175-4

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  • DOI: https://doi.org/10.1007/s13198-013-0175-4

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