Condition Assessment and Fault Prognostics of Microelectromechanical Systems.

International audienceMicroelectromechanical systems (MEMS) are used in different applications such as automotive, biomedical, aerospace and communication technologies. They create new functionalities and contribute to miniaturize the systems and reduce their costs. However, the reliability of MEMS is one of their major concerns. They suffer from different failure mechanisms which impact their performance, reduce their lifetime and their availability. It is then necessary to monitor their behavior and assess their health state to take appropriate decision such as control reconfiguration and maintenance. These tasks can be done by using Prognostic and Health Management (PHM) approaches. This paper addresses a condition assessment and fault prognostic method for MEMS. The paper starts with a short review about MEMS and presents some challenges identified and which need to be raised to implement PHM methods. The purpose is to highlight the intrinsic constraints of MEMS from PHM point of view. The proposed method is based on a global model combining both nominal behavior model and degradation model to assess the health state of MEMS and predict their remaining useful life. The method is applied on a microgripper, with different degradation models, to show its effectiveness

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

Optimal Design for Accelerated-Stress Acceptance Test Based on Wiener Process

[[notice]]補正完

The State of the Art in Fuel Cell Condition Monitoring and Maintenance

Fuel cell vehicles are considered to be a viable solution to problems such as carbon emissions and fuel shortages for road transport. Proton Exchange Membrane (PEM) Fuel Cells are mainly used in this purpose because they can run at low temperatures and have a simple structure. Yet to make this technology commercially viable, there are still many hurdles to overcome. Apart from the high cost of fuel cell systems, high maintenance costs and short lifecycle are two main issues need to be addressed. The main purpose of this paper is to review the issues affecting the reliability and lifespan of fuel cells and present the state of the art in fuel cell condition monitoring and maintenance. The Structure of PEM fuel cell is introduced and examples of its application in a variety of applications are presented. The fault modes including membrane flooding/drying, fuel/gas starvation, physical defects of membrane, and catalyst poisoning are listed and assessed for their impact. Then the relationship between causes, faults, symptoms and long term implications of fault conditions are summarized. Finally the state of the art in PEM fuel cell condition monitoring and maintenance is reviewed and conclusions are drawn regarding suggested maintenance strategies and the optimal structure for an integrated, cost effective condition monitoring and maintenance management system

Prognostics and health management for maintenance practitioners - Review, implementation and tools evaluation.

In literature, prognostics and health management (PHM) systems have been studied by many researchers from many different engineering fields to increase system reliability, availability, safety and to reduce the maintenance cost of engineering assets. Many works conducted in PHM research concentrate on designing robust and accurate models to assess the health state of components for particular applications to support decision making. Models which involve mathematical interpretations, assumptions and approximations make PHM hard to understand and implement in real world applications, especially by maintenance practitioners in industry. Prior knowledge to implement PHM in complex systems is crucial to building highly reliable systems. To fill this gap and motivate industry practitioners, this paper attempts to provide a comprehensive review on PHM domain and discusses important issues on uncertainty quantification, implementation aspects next to prognostics feature and tool evaluation. In this paper, PHM implementation steps consists of; (1) critical component analysis, (2) appropriate sensor selection for condition monitoring (CM), (3) prognostics feature evaluation under data analysis and (4) prognostics methodology and tool evaluation matrices derived from PHM literature. Besides PHM implementation aspects, this paper also reviews previous and on-going research in high-speed train bogies to highlight problems faced in train industry and emphasize the significance of PHM for further investigations