Fabrice Guerin

Application of a neural network for optimum clearance prediction in sheet metal blanking processes

The blanking process and the structure of the blanked surface are influenced by both the tooling (clearance and the tool geometry) and the properties of the workpiece material (blank thickness, mechanical properties, microstructure, etc.). Therefore, for a given material, the clearance and tool geometry are the most important parameters.The objective of the present work is to develop a methodology to obtain the optimum punch-die clearance for a given sheet material by the simulation of the blanking process. A damage model of type Lemaitre is used in order to describe crack initiation and propagation into the sheet. The proposed approach combines predictive finite element and neural network modeling of the leading blanking parameters. The numerical results obtained by finite element computation including damage and fracture modeling were utilized to train the developed simulation environment based on back propagation neural network modeling.The comparative study between the numerical results and the experimental ones, shows the good agreement.

Numerical pressure prediction algorithm of superplastic forming processes using 2D and 3D models

The paper describes a finite element model allowing for the prediction in a rapid way the optimum pressure cycle law, the deformed shapes, the distributions of the strain rate and the evolution of the thickness during superplastic forming processes. During the calculation, a pressure-cycle control algorithm is used in the analysis which keeps track of the maximum strain rate sensitivity index m, and adapts the pressure law applied in order to approach as nearly as possible the optimal pressure time history law. The purpose is not to follow the target exactly but obtain a practical pressure time history in a low computation cost time. To compare the performance of 2D and 3D approaches, two analyses have been performed using 2D and 3D finite element modeling. The numerical results are compared with the experimental ones to verify the validity of the pressure algorithm control.

Bayesian estimation in accelerated life testing

A common problem of high-reliability computing is, on the one hand, the magnitude of total testing time required, particularly in the case of high-reliability components; and, on the other hand, the number of devices under testing. In both cases, the objective is to minimise the costs involved in testing without reducing the quality of the data obtained. One solution is based on Accelerated Life Testing (ALT) techniques which permit decreasing the testing time. Another solution is to incorporate prior beliefs, engineering experience, or previous data into the testing framework. It is in this spirit that the use of a Bayesian approach can, in many cases, significantly reduce the number of devices required. This paper presents a study of the Arrhenius-Exponential model by an evaluation of parameters using Maximum Likelihood (ML) and Bayesian methods. A Monte Carlo simulation is performed to examine the asymptotic behaviour of these different estimators.

Reliability estimation by Bayesian method: definition of prior distribution using dependability study

Abstract In this article, we present an evaluation method of the system reliability using Bayesian statistics and data feedback. In particular, we deal with the problem of the prior definition. A method is proposed to build the prior distribution from the dependability study (risk evaluation study).

Reliability analysis of mechatronic systems using censored data and petri nets: application on an antilock brake system (abs)

Reliability estimation is becoming established as an important issue of the design process of mechatronic systems (i.e. systems involving in their implementation more basic technologies, such as mechanics, electronics and software). We propose to estimate the mechatronic system reliability using stochastic Petri Nets. The failure times are simulated in the Petri Nets model integrating the reliability of the components of the mechatronic system. The reliability is estimated from simulated failure times by using the Maximum Likelihood method. The paper is illustrated by an application example on ABS system. This paper presents the results of a co-operational work, getting together mechanical, electronic, and software engineers. The proposed method allows reliability evaluating both for n mechatronic systems and for their different sub-systems. An application to a vehicle Antilock Brake System (ABS) illustrates this method. We model the mechanical, electronic and embedded software sub-systems, to design, to check and to estimate the reliability of the ABS. Reliability evaluation of mechatronic systems requires the modeling of failure behavior of different components. We propose to evaluate mechatronic systems reliability using censored data. By using the failure times of the system, we compute the values of the parameters for all the components by maximum likelihood estimator with censored times

Determining the shape parameter of a Weibull distribution from mechanical damage models

The aim of this paper is to show that it is possible to determine the shape factor of the Weibull distribution relating to a mechanical damage model. In particular, we define the shape parameter linked to damage by limited fatigue. Also, the parameters of distribution of cycles number to failure is characterized using the limited fatigue approach by the Basquin model. After, the Weibull parameters (/spl beta/ and /spl eta/) are estimated by the method of moments. This work is currently used for other modes in order subsequently to obtain more precise conclusions when one analyses a Weibull sheet.

Functional and dysfunctional analysis of a mechatronic system

A study of system reliability is generally preceded by a functional analysis, which consists of defining the material limits, the various functions and operations realized by the system and the various configurations. This stage does not give information about the modes of failure and their effects. It is necessary to complete it by a second one taking into account the dysfunctions in order to model suitably a complex system with Petri networks. In this paper, we propose to employ SADT, FMEA, SEEA and Petri networks methods to study a mechatronic system.

Reliability analysis for complex industrial real-time systems: application on an antilock brake system

The reliability analysis of industrial systems is a very important engineering issue, in order to guarantee their functional behavior. Most of the critical failures are generated by the interactions between the sub-systems, implemented in different technologies, e.g. mechanics, electronics, and software. Therefore the analysis of the system as a whole is not enough and it is necessary to study all the interactions in order to estimate the system reliability.

Bayesian Estimation of Degradation Model Defined by a Wiener Process

The constantly increasing market request of high quality vehicles ask the automotive manufacturers to perform lifetime testing in order to verify the reliability levels of new products. In this paper, we deal with two difficulties in reliability assessment for mechanical parts. On one hand, there is the small number of parts available for testing. On the other hand, there is the problem of wear. In the automotive applications, mechanical components subjected to relative motion of parts have to be designed against wear. In this paper, the Bayesian estimation of Wiener process parameters (usually used to define the degradation process) is studied to improve the estimation accuracy in incorporating the available knowledge on the product. In particular, the finite element results and expert knowledge are considered as “a priori”. For wear prediction by FEM, a model based on Archard law was developed for the brake disc wear.

Comparative study of accelerated testing models, applications in mechanics

Accelerated tests are becoming more and more popular in industry due to the need for obtaining life-data and to get more failures quickly. The article presents a comparative and critical analysis of some methods of accelerated testing (parametric, semi-parametric) in the case of mechanics. A simulation of a mechanical-damage model (fatigue) illustrates our analysis. The results obtained reveal the limitations and possible applications of these methods in mechanics.