Bayesian parameter estimation with prior weighting in ALT model

This paper provides an overview of the application of Bayesian inference to accelerated life testing (ALT) models for the concrete case of estimation by Maximum of Aposteriori (MAP) method in the case of constant stress levels. It studies the Bayesian inference over the accelerated life model as presented in [1]. It suites, integrates and generalizes the particular cases presented in [2] and [3]. Towards the end, weighting of the prior information according to data is integrated. The paper also illustrates an experimental example

Bayesian method approach for fatigue life distribution estimation of rubber components

The constantly increasing market requirements of high-quality vehicles compel automotive manufacturers to perform lifetime testing to verify the reliability levels of new products. A common problem is that only a small number of samples of a system\u27s component can be tested. In automotive applications, mechanical components subjected to cyclic loading have to be designed against fatigue. In this paper, the Bayesian estimation of lognormal distribution parameters (usually used to define the fatigue lifetime of rubber components) is studied to improve the accuracy of estimation while incorporating the available knowledge on the product. In particular, the finite element results and experts\u27 opinions are considered prior knowledge. For lifetime prediction by Finite Element Method (FEM), a model based on the Brown-Miller law was developed for the rubberlike boot seal material

Adiabatic Evolution for Systems with Infinitely many Eigenvalue Crossings

We formulate an adiabatic theorem adapted to models that present an instantaneous eigenvalue experiencing an infinite number of crossings with the rest of the spectrum. We give an upper bound on the leading correction terms with respect to the adiabatic limit. The result requires only differentiability of the considered spectral projector, and some geometric hypothesis on the local behaviour of the eigenvalues at the crossings

L'étalon-or des évaluations randomisées : du discours de la méthode à l'économie politique

La dernière décennie a vu l'émergence d'un nouveau champ de recherche en économie du développement : les méthodes expérimentales d'évaluation d'impacts par assignation aléatoire. Cet article explore le contraste entre d’une part les limites (nombreuses) et la circonscription (très étroite) du champ réel d'application de ces méthodes et d’autre part leur succès, attesté à la fois par leur nombre et leur forte médiatisation. L’analyse suggère que ce contraste est le fruit d’une conjonction économique et politique particulière, émanant de stratégies novatrices de la part des chercheurs de cette nouvelle école, et d’intérêts et de préférences spécifiques provenant à la fois du monde académique et de la communauté des donateurs

What are the effects of the reliability model uncertainties in the maintenance decisions?

Most of the works proposed for the design of reliability test plans  are  devoted  to  the  guaranty  of  the  reliability performance  of  a  product  but  scarce  of  them  tackles maintenance  issues.  On  the  other  hand,  classical maintenance  optimization  criteria  rarely  take  into  account the variability of the failure parameters due to lack of data, especially when the data collection in the operating phase is expensive.  The  objective  of  this  paper  is  to  highlight through a numerical experiment the impact of the test plan design  defined  here  by  the  number  of  the  products  to  be tested and the test duration on the performance of a classical condition-based maintenance (CBM) policy

La RSE est - elle applicable dans les établissements publics comme dans n'importe quelle autre organisation ? Un exemple : les Universités

De responsabilité sociétale des entreprises à responsabilité sociétale des organisations, une évolution mais pour quelle mise en application ? Le service public peut-il s\u27adapter ? Pourquoi ? Avec qui ? A quelles conditions ? Dispose-t-il des outils nécessaires ? Réflexions sur ce thème

Optimal accelerated test plan: optimization procedure using Genetic Algorithm

This paper describes an optimization procedure using Genetic Algorithm to define an optimal accelerated test plan considering an economic approach. We introduce a general framework to obtain plans of optimal accelerate tests with a specific objective, such as cost. The objective is to minimize the costs involved in testing without reducing the quality of the data obtained. The optimal test plans are defined by considering prior knowledge of reliability, including the reliability function and its scale and shape parameters, and the appropriate model to characterize the accelerated life. This information is used in Bayesian inference to optimize the test plan. To perform optimization, a specific genetic algorithm is decribed and applied to obtain the best test plan. This procedure is then illustrated on a numerical example