In the industrial context, the main goal of the maintenance team is to avoid sudden failures that can cause the stoppage of the system with a consequent loss of production. This means that each maintenance action must be performed before the degradation level of a system exceeds a critical threshold beyond which the failure probability becomes high. The increasing importance given to maintenance is shown not only by the great deal of literature on the topic, but also by the interest in transforming this area from a managerial area to a branch of applied mathematics (Operational Research or Statistics). Maintenance is now considered as a subject and much research activity is concerned with its mathematical modeling rather than with the management processes relating to maintenance itself. In [1], Scarf evidences the great importance of the mathematical modeling of maintenance and the correlated strategic support given by the maintenance management information systems. Nevertheless, no model can be built without an exhaustive collection of data. By data, Author means not only specific figures regarding, for example, failure times, but all information related to the process under study. With the recent advent of condition monitoring and the development of appropriate decision models, critical components of a system can be tracked through appropriate variable(s) correlated to their degradation process, logistic support (for example, spares inventory) can be provided, maintenance history can be stored, predetermined maintenance activity can be alarmed and management reports can be produced. The use of condition monitoring techniques reduces the uncertainty operators feel about the current state of the plant. For example, knowledge about the vibration levels of a rotating bearing gives engineers confidence about its operation in the short term. Data acquired by monitoring systems, maintenance histories collected for specific components can be considered fundamental resources for the mathematical modeling of the maintenance activities. This paper is the first part of two [2], presenting the transition from preventive maintenance policy to the predictive one. In particular, the paper presents a brief review of the subject and some critical considerations about the two maintenance policies.

System monitoring and maintenance policies: a review / Curcurù, Giuseppe; Cocconcelli, Marco; Rubini, Riccardo; Galante, Giacomo Maria. - (2017). (Intervento presentato al convegno The International Conference Surveillance 9 tenutosi a Fes (Marocco) nel 22-24 May 2017).

System monitoring and maintenance policies: a review

COCCONCELLI, Marco;RUBINI, Riccardo;
2017

Abstract

In the industrial context, the main goal of the maintenance team is to avoid sudden failures that can cause the stoppage of the system with a consequent loss of production. This means that each maintenance action must be performed before the degradation level of a system exceeds a critical threshold beyond which the failure probability becomes high. The increasing importance given to maintenance is shown not only by the great deal of literature on the topic, but also by the interest in transforming this area from a managerial area to a branch of applied mathematics (Operational Research or Statistics). Maintenance is now considered as a subject and much research activity is concerned with its mathematical modeling rather than with the management processes relating to maintenance itself. In [1], Scarf evidences the great importance of the mathematical modeling of maintenance and the correlated strategic support given by the maintenance management information systems. Nevertheless, no model can be built without an exhaustive collection of data. By data, Author means not only specific figures regarding, for example, failure times, but all information related to the process under study. With the recent advent of condition monitoring and the development of appropriate decision models, critical components of a system can be tracked through appropriate variable(s) correlated to their degradation process, logistic support (for example, spares inventory) can be provided, maintenance history can be stored, predetermined maintenance activity can be alarmed and management reports can be produced. The use of condition monitoring techniques reduces the uncertainty operators feel about the current state of the plant. For example, knowledge about the vibration levels of a rotating bearing gives engineers confidence about its operation in the short term. Data acquired by monitoring systems, maintenance histories collected for specific components can be considered fundamental resources for the mathematical modeling of the maintenance activities. This paper is the first part of two [2], presenting the transition from preventive maintenance policy to the predictive one. In particular, the paper presents a brief review of the subject and some critical considerations about the two maintenance policies.
2017
The International Conference Surveillance 9
Fes (Marocco)
22-24 May 2017
Curcurù, Giuseppe; Cocconcelli, Marco; Rubini, Riccardo; Galante, Giacomo Maria
System monitoring and maintenance policies: a review / Curcurù, Giuseppe; Cocconcelli, Marco; Rubini, Riccardo; Galante, Giacomo Maria. - (2017). (Intervento presentato al convegno The International Conference Surveillance 9 tenutosi a Fes (Marocco) nel 22-24 May 2017).
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1144821
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