ENBIS-17 in Naples

9 – 14 September 2017; Naples (Italy) Abstract submission: 21 November 2016 – 10 May 2017

VAM, an R Package to Take into Account the Effect of Maintenance and Ageing

12 September 2017, 09:00 – 09:20

Abstract

Submitted by
Doyen Laurent
Authors
Doyen Laurent (Univ. Grenoble Alpes)
Abstract
Recurrent events data arise in many application fields such as epidemiology (e.g. relapse times of a disease), industry (e.g. repair times of a system), ... To analyze such data, we must be able to take into account events effects on successive occurrence times. The presentation is focalized on maintenance efficiency in reliability context, but it can equivalently be applied to intervention and treatment efficiency in epidemiology context. The basic assumptions are known as perfect maintenance or As Good As New (the system is renewed) and minimal maintenance or As Bad As Old (maintenance has no effect on future occurrence times). Obviously, reality falls between these two extreme cases. An intermediate effect can be described thanks to imperfect maintenance models. We will present with practical examples an introductory tutorial to our VAM software. VAM, for Virtual Age Models, is an R open source package that implements the principal imperfect maintenance models. VAM usage is based on a formula which specify the characteristic of the data set to analyze and the model used for that. Thanks to this formula description the package becomes adaptive. In fact, the formula is defined by the user and characterizes the behavior of the new unmaintained system, the types, effects and number of different preventive and corrective maintenances, and how preventive maintenance times are planned. Then, the package functionalities enable to simulate new data sets, to estimate with maximum likelihood method the parameters of the model, to calculate and plot different indicators. These functions can be in particular used to implement Monte Carlo and bootstrap methods. A weakness of classical R codes is that such computation can becomes quite long because R is an interpreted and not compiled language. But this is not the case for the VAM package since it is mainly implemented in C++ thanks to the Rcpp package.

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