Maximum entropy model applied to RCM scheme for replaceable systems.

EasyChair Preprint no. 1665

Abstract

Based on methodologies of variational calculus and differential entropy, we propose in this work a non-parametric model that provides a robust estimation of reliability to be used in a RCM scheme. A Weibull analysis is presented first in a case study within the usual RCM schemes. If the sample of data is reduced the weibull analysis loses precision, impacting in the RCM scheme. To solve this limitation, a maximum entropy approach is proposed. Differential entropy has been shown as a solid tool to model the response of a random variable when reduced sample size information is available. We take advantage of the formalism of the variational calculus to express a functional that obeys the Euler-Lagrange equations and supported by the Kolmogorov axioms, we extract a generalized non-parametric probability density. By subjecting this density to appropriate boundary conditions in terms of the first moments of the generalized probability density.

Keyphrases: differential entropy, Euler-Lagrange, RCM, Reliability, Shanon, variational calculus, Weibull, Weibull analysis

@Booklet{EasyChair:1665,
  author = {Marco Fuentes-Huerta and David Salvador González-González and Octavio Perez Gomez Gaona and Rolando Javier Praga-Alejo},
  title = {Maximum entropy  model applied to RCM scheme for replaceable systems.},
  howpublished = {EasyChair Preprint no. 1665},

  year = {EasyChair, 2019}}