Simultaneous effect of RCM key indicators, related to equipment lifecycle for maintenance strategies (in production systems)

  • Abstract
  • Keywords
  • References
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  • Abstract

    In the modern industrial world, effective role of maintenance activities in the survival of organizations and enhancing their productivity is undeniable.

    Variety of equipments in the industrial organizations and their exclusivities in terms of longevity and failures modes, clear the importance of choosing a strategy for the maintenance of any equipment. Thus, knowing the type of the failure is so important for maintenance manager and engineers.

    Important introduced indicators in this domain such as indicator of reliability, MTBF and MTTR can be used to predicting and detecting approximate failure time and analyzing life cycle status.

    On the other hand, due to fluctuating time of system availability because of work continuity and loss of a performance indicator, by combining RCM indicators and Overall Equipment Effectiveness (OEE) indicator the most compatible strategy could be chosen. The aim of this article which differs from other studies in this field is to apply a composed indicator, including different parameters of RCM, which is obtained based on the equipment life status.

  • Keywords

    Maintenance; Reliability; Key Performance Indicators; Weibull Analysis; Life Cycle.

  • References

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      [2] Moubray,John. Reliability centered maintenance, second Edition. (1990).

      [3] Haj shirmohamadi, A. Maintenance Planning, Iran, University of Isfahan, (2010).

      [4] Kumar, D., Knezevic, J. Maintenance free operating period an alternative measure to MTBF and failure rate for specifying reliability. Reliability Engineering and System Safety, 64 (1999) pp: 127–131.

      [5] Valdebenito, MA. Beaurepaire, P. Reliability based optimization of maintenance scheduling of mechanical components under fatigue. Comput. Methods Appl. Mech. Engrg. 221–222 (2012) pp: 24–40.

      [6] Bernethy,R. The new Weibull Handbook, Reliability & Statistical Analysis, British Library, London, Fourth Edition (2001).




Article ID: 4006
DOI: 10.14419/ijet.v4i3.4006

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