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Introducing buffer inventories in the RBD analysis of process production systems

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  • Macchi, Marco
  • Kristjanpoller, Fredy
  • Garetti, Marco
  • Arata, Adolfo
  • Fumagalli, Luca

Abstract

The throughput analysis is an important issue for the design and operations management of process production lines. The throughput of a line depends on the availability and nominal throughput of its machines. Further on, it is influenced by the accumulation process of production material stocked into buffers along the line; hence, the buffer inventory level is also a relevant variable that has to be considered when assessing the throughput of the line. The present paper is particularly concerned with using such an assessment for supporting maintenance decisions. The buffer inventory level should provide the proper isolation time before the buffer becomes empty, so that, during this time, a maintenance intervention can be carried on at a failed machine upward, without causing a propagation of the effect of the failure in the machines downward (the so called ‘material starvation’). Alike, it should guarantee the proper isolation time before reaching the complete utilisation of the buffer capacity, so that also during this time a maintenance intervention is possible at a failed machine downward without causing a propagation of the effect of the failure in the machines upward (the so called ‘blocking of production’). This strategy is particularly interesting in the process industry where the capital cost of equipment is high and the holding cost of material is low. Hence, the isolation times before reaching ‘material starvation’ or ‘blocking of production’ have to be properly studied in order to make an accurate analysis of their effect on the throughput of the line. The present paper provides a model to this end, derived by extending the well known Reliability Block Diagram (RBD) method, currently used in the normal duties of a maintenance engineer. The usual RBD availability analysis is integrated by a state space analysis through which isolation times can be analysed. Besides, an empirical study – the case of a production line taken out from the mining industry – is carried on in order to demonstrate the use of the integrated tool in practice.

Suggested Citation

  • Macchi, Marco & Kristjanpoller, Fredy & Garetti, Marco & Arata, Adolfo & Fumagalli, Luca, 2012. "Introducing buffer inventories in the RBD analysis of process production systems," Reliability Engineering and System Safety, Elsevier, vol. 104(C), pages 84-95.
    • Handle: RePEc:eee:reensy:v:104:y:2012:i:c:p:84-95
    DOI: 10.1016/j.ress.2012.03.015
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    References listed on IDEAS

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    1. Horton, Graham & Kulkarni, Vidyadhar G. & Nicol, David M. & Trivedi, Kishor S., 1998. "Fluid stochastic Petri nets: Theory, applications, and solution techniques," European Journal of Operational Research, Elsevier, vol. 105(1), pages 184-201, February.
    2. Papadopoulos, H. T. & Heavey, C., 1996. "Queueing theory in manufacturing systems analysis and design: A classification of models for production and transfer lines," European Journal of Operational Research, Elsevier, vol. 92(1), pages 1-27, July.
    3. Barabady, Javad & Kumar, Uday, 2008. "Reliability analysis of mining equipment: A case study of a crushing plant at Jajarm Bauxite Mine in Iran," Reliability Engineering and System Safety, Elsevier, vol. 93(4), pages 647-653.
    4. Lisnianski, Anatoly, 2007. "Extended block diagram method for a multi-state system reliability assessment," Reliability Engineering and System Safety, Elsevier, vol. 92(12), pages 1601-1607.
    5. Sorensen, Kenneth & Janssens, Gerrit K., 2004. "A Petri net model of a continuous flow transfer line with unreliable machines," European Journal of Operational Research, Elsevier, vol. 152(1), pages 248-262, January.
    6. Herder, P.M. & van Luijk, J.A. & Bruijnooge, J., 2008. "Industrial application of RAM modeling," Reliability Engineering and System Safety, Elsevier, vol. 93(4), pages 501-508.
    7. Levitin, Gregory, 2007. "Block diagram method for analyzing multi-state systems with uncovered failures," Reliability Engineering and System Safety, Elsevier, vol. 92(6), pages 727-734.
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