Updated Operational Reliability from Degradation Indicators and Adaptive Maintenance Strategy

This chapter is dedicated to the reliability and maintenance of assets that are characterized by a degradation process. The item state is related to a degradation mechanism that represents the unit-to-unit variability and time-varying dynamics of systems. The maintenance scheduling has to be updated considering the degradation history of each item. The research method relies on the updating process of the reliability of a specific asset. Given a degradation process and costs for preventive/corrective maintenance actions, an optimal inspection time is obtained. At this time, the degradation level is measured and a prediction of the degradation is conducted to obtain the next inspection time. A decision criterion is established to decide whether the maintenance action should take place at the current time or postpone. Consequently, there is an optimal number of inspections that allows to extend the useful life of an asset before performing the preventive maintenance action. A numerical case study involving a non-stationary Wiener-based degradation process is proposed as an illustration of the methodology. The results showed that the expected cost per unit of time considering the adaptive maintenance strategy is lower than the expected cost per unit of time obtained for other maintenance policies

Cutting tools reliability and residual life prediction from degradation indicators in turning process

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Estimate of Cutting Tool Lifespan through Cox Proportional Hazards Model

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A comparative study of the gamma and Wiener processes for track geometry degradation modeling

Dans cette communication, nous proposons une comparaison des processus stochastiques gamma et Wiener pour la modélisation des défauts de géométrie de voie. A partir de mesures relevées sur plusieurs sections, les deux processus sont estimés et simulés. Les deux modèles obtenus sont alors comparés sur base de l’évolution de leur espérance mathématique et de leur variance. Finalement, un modèle de durée de vie résiduelle est proposé pour ces deux processus en calculant la distribution des temps d’atteinte d’un seuil critique de dégradation de géométrie de voie. Les implications pratiques de cette étude viseront à émettre des recommandations sur le choix d’un processus stochastique pour modéliser des dégradations de géométrie de voie.The purpose of this study is to compare the gamma and Wiener stochastic processes to model the track geometry degradation. Firstly, both the gamma and Wiener processes are estimated from field data. After that, the mathematical expectation and the variance of the aforementioned models are compared. Finally, a mean residual life model is proposed for both models by computing the distribution of the hitting times of a given track geometry degradation threshold. Practical implications of this study will consist in giving guidance for the choice of a stochastic process to model track geometry degradation

Cost-Based Optimization of Track Geometry Inspection

Track geometry bear huge static and dynamic forces that accelerate degradation process. As a result, railway track should be inspected regularly to detect geometry faults and to plan maintenance actions in advanced. An inspection plan that minimizes track maintenance cost is highly desirable by infrastructure managers. This paper proposes constructing an integrated model to identify the optimum track geometry inspection interval. To this end, it develops a long term prediction model combining degradation, shock event, and tamping recovery models. It applies the Wiener process to model track geometry degradation, simulates shock event times using an exponential distribution, and uses a probabilistic model to model recovery after tamping. With the proposed integrated model and simulation, it is possible to identify the optimum track geometry inspection frequencies that minimize total track maintenance costs.Godkänd; 2016; 20160826 (solmei)</p