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Basic Models and Methods for Maintenance of Production Systems

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

Abstract

The European standard EN 13306 (Maintenance terminology) distinguishes two main types of maintenance, called “maintenance strategies,” as:

• “Preventive maintenance ... carried out at predetermined intervals or according to prescribed criteria and intended to reduce the probability of failure or the degradation of the functioning of an item”;

• “Corrective maintenance ... carried out after fault recognition and intended to put an item into a state in which it can perform a required function”.

One of the most critical decisions for the analyst, i. e., the maintenance manager, is the determination of the items subject to preventive maintenance, then the time schedule or the number of units of use suitable for performing the maintenance actions. A famous proverb, also used a lot in television spots of a well-known toothpaste, is “prevention is better than cure,” known as “prevenire è meglio che curare” by the Italian authors of this book. This is the Hamlet-like maintenance issue against the “outrageous fortune,” as William Shakespeare calls stochastic processes: “is it better to prevent or wait and see?: that is the question”. This is the question of strategy in maintenance management and this chapter introduces models, methods, and significant applications to support the choice of the best reply and reaction to it. Other very important questions deal with the identification of the production system’s performance and parameters subject to monitoring and inspection activities, monitoring or inspection?, deferred or immediate maintenance?, on-line or off-line maintenance?, on-site or off-site and/or remote maintenance? replacement or overhaul or rebuilding?

Keywords

Weibull Distribution Preventive Maintenance Maintenance Action Maintenance Strategy Corrective Maintenance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 2010

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