A unified treatment of single component replacement models

In this paper we discuss a general framework for single component replacement models. This framework is based on the regenerative structure of these models and by using results from renewal theory a unified presentation of the discounted and average finite and infinite horizon cost models is given. Finally, some well-known replacement models are discussed, and making use of the previous results an easy derivation of their cost functions is presented

Identificación del índice de vulnerabilidad territorial a partir de modelos jerárquicos y heurísticos aplicando SOA

Auxiliar de InvestigaciónEn el proyecto se realiza el diseño y desarrollo de 4 servicios web implementando los modelos de toma de decisión (AHP, AHP FUZZY, ELECTRE y PROMETHEE), encargados de procesar datos obtenidos en campo en la primera fase del proyecto que se realizó a través de encuestas, formatos de entrevistas, talleres y metodologías de análisis. Los datos se procesaran de acuerdo al modelo de toma de decisión seleccionado, generando como resultado final un indicador de vulnerabilidad territorial.PregradoIngeniero de Sistema

Printed in U.S.A. OPTIMAL REPLACEMENT UNDER PARTIAL OBSERVATIONS

In this paper, we present a framework for the condition-based maintenance optimization. A technical system which can be in one of N operational states or in a failure state is considered. The system state is not observable, except the failure state. The information that is stochastically related to the system state is obtained through condition monitoring at equidistant inspection times. The system can be replaced at any time; a preventive replacement is less costly than failure replacement. The objective is to find a replacement policy minimizing the long run expected average cost per unit time. The replacement problem is formulated as an optimal stopping problem with partial information and transformed to a problem with complete information by applying the projection theorem to a smooth semimartingale process in the objective function. The dynamic equation is derived and analyzed in the piecewise deterministic Markov process stopping framework. The contraction property is shown and an algorithm for the calculation of the value function is presented, illustrated by an example. 1. Introduction. We consider a technical system which can be in one of N operational states �1 � 2�����N�, or in the failure state N ′ ≡ N +1. We assume that if i ≤ j, state i is not worse than state j; 1 denotes the state of a new system. The system state is not observable

A case comparison of a proportional hazards model and a stochastic filter for condition-based maintenance applications using oil-based condition monitoring information

The ability to predict the expected time remaining before a component fails is crucial when scheduling maintenance activities and component replacements. The current paper presents a comparison of the proportional hazards model and a probabilistic filtering approach when applied to the estimation of a components residual life using stochastically related oil-based wear information. The condition information is collected at irregular monitoring points from aircraft engines and consists of the concentrations of various contaminating metallic particles in an oil sample. Issues regarding the use of multiple information parameters are also addressed