François Pérès

Sustainable management of end-of-life systems

In a sustainable development context, the stakes of the last stage of system life cycle, the end-of-life stage, have increased over recent years. End-of-life systems have to be de-manufactured in order to be valued so as to respond to environmental concerns. The aim of a disassembly strategy consists in issuing a solution to the whole decision problem raised during the end-of-life stage of systems. Indeed, decision makers have to select valuable components according to technical, economical and environmental criteria and then design and optimise a disassembly support system that will generate these products. The solution obtained is what we refer to in this article as a disassembly trajectory. The work presented in this article is about planning these trajectories on different horizons integrating several arrivals of end-of-life systems. The proposed approach, with Bayesian networks and influence diagrams as the underlying mathematical tools, enables dynamically defined uncertainties to be taken into account.

OMTDR using BER estimation for ambiguities cancellation in ramified networks diagnosis

Nowadays, increasing demands for on-line wire diagnosis using reflectometry have imposed serious challenges on signals processing, bandwidth control and interference mitigation. On-line diagnosis aims at detecting and locating faults accurately while the target system is running. In this work, a new reflectometry method, named “Orthogonal Multi-Tone Time Domain Reflectometry” (OMTDR), is proposed. OMTDR, based on Orthogonal Frequency Division Multiplexing (OFDM), is a suitable candidate for on-line diagnosis as it permits interference avoidance, bandwidth control and data rate increase thanks to the use of orthogonal tones and guard intervals. Over the diagnosis function, OMTDR adds communication between sensors to more accurately determine faults position in a multi-branch network using a distributed strategy. OMTDR was tested on a branched network consisting of three cables with different lengths, with sensors at each cable end. Here, the sensors signals are carefully constructed using a resource allocation scheme to use frequencies below and above the prohibited bandwidth, used by the target system, for communication and diagnosis. Simulation results show that the proposed method performs well in a branched wiring network as it permits to detect and locate faults accurately even when the target system is operating.

A bipolar consensus approach for group decision making problems

Adaptive consensus seeking in group decision making.Mutual influence modeling.Taking into account human attitude.Multi-criteria problem using bipolarity concept.Consensus processes with or not individual changes. This paper addresses the collaborative group decision making problems considering a consensus processes to achieve a common legitimate solution. The proposed resolution model is based on individual bipolar assessment. Each decision maker evaluates alternatives through selectability and rejectability measures which respectively represent the positive and negative aspects of alternatives considering objectives achievement. The impact of human behavior (influence, individualism, fear, caution, etc.) on decisional capacity has been taken into account. The influence degrees exerted mutually by decision makers are modeled through concordance and discordance measures. The individualistic nature of decision makers has been taken into account from the individualism degree. In order to achieve a common solution(s), models of consensus building are proposed based on the satisficing game theory formalism for collective decision problems. An application example is given to illustrate the proposed concepts.

Diagnosis sensor fusion for wire fault location in CAN bus systems

This paper proposes a new method for distributed wire diagnosis using reflectometry. It not only uses the reflected part of the test signal to extract information about the fault position, but it also investigates the transmitted part to enable sensors communication. The major novelty is to inject a signal carrying additional information about the fault position as a test signal using Orthogonal Multi-Tone Time Domain Reflectometry (OMTDR) method. While the reflected signal permits to determine the fault position at time t, the transmitted one sends the fault position at time (i-1) to the master sensor. Finally, the latter takes the location decision based on the information gathered from its slaves. This removing location ambiguities in branched networks. Time Division Multiple Access (TDMA) is used to avoid noise interference.

Initial spare parts supply of an orbital system

This article presents a method of management of the initial spare parts supply. This generic problem is of particular interest in certain systems in which the difficulty of accessibility or the life cycle duration constitute risks tied to the possible depletion of the spare parts stock. In this paper we consider the spatial context. After having commented on the particularities of the management of the spare parts supply of a space station, we propose a method based on the minimization of the risk of postponement of a maintenance operation. Finally, an application to the Columbus laboratory of the International Space Station is presented.

Design methods applied to the selection of a rapid prototyping resource

The article first introduces the problem in question and discusses the interest in implementing a concurrent engineering approach. It focuses on the relevant rapid prototyping techniques likely to be used in order to make the design and production processes more reliable. Next, the article describes in generic terms the advantages of using the QFD method as a decision making tool. The practical case study chosen is related to the selection of a prototyping resource. After identifying the functions to be fulfilled by the rapid prototyping resource, a technology deployment matrix is built and the principles leading to the results are commented upon.

BOCR Framework for Decision Analysis

This paper considers establishing a framework for modellig decision analysis problems where the analyst must cope with uncertainty, multiple objectives, multiple attributes and multiple actors. These probems rise when considering large scale and complex decision problems encountered in real world applications in domains such as risk assessment and managment, infrastrucutres planning, complex process monitoring, supply chain planning, etc. To tackle this modelling chalenges, we propose to use BOCR (benefit, opportunity, cost, and risk) paradigm to identify attributes that must characterize an alternative with regard to a given objective. Then Bayesian network and/or AHP (analytic hierrarchy process) analysis can be used to assess the values of these later attributes. Finally an aggregation method based on satisficing game is developed that permit to evaluate each alternative by two measures: selectability degree constructed using “positive” attributes (benefit and opportunity) and the rejectability degree built on “negative” attributes (cost and risk).

Anticipating aging failure using feedback data and expert judgment

This paper presents a methodology for anticipating failures in a component up to the end of its life cycle. Often, feedback data is not sufficient and must be complemented by the analysis of expert judgment. The methodology developed aims at anticipating the degradation mechanisms responsible for aging, and evaluating their relevance and related uncertainties. This is necessary information for risk analysis related to the operating of a component up to the end of its life cycle. Lastly, the methodology is applied to a nuclear component.

Distributed sensor fusion for wire fault location using sensor clustering strategy

From reflectometry methods, this work aims at locating accurately electrical faults in complex wiring networks. Increasing demand for online diagnosis has imposed serious challenges on interference mitigation. In particular, diagnosis has to be carried out while the target system is operating. The interference becomes more even critical in the case of complex networks where distributed sensors inject their signals simultaneously. The objective of this paper is to develop a new embedded diagnosis strategy in complex wired networks that would resolve interference problems and eliminate ambiguities related to fault location. To do so, OMTDR (Orthogonal Multi-tone Time Domain Reflectometry) method is used. For better coverage of the network, communication between sensors is integrated using the transmitted part of the OMTDR signal. It enables data control and transmission for fusion to facilitate fault location. In order to overcome degradation of diagnosis reliability and communication quality, we propose a new sensor clustering strategy based on network topology in terms of distance and number of junctions. Based on CAN bus network, we prove that data fusion using sensor clustering strategy permits to improve the diagnosis performance.

A Distributed Diagnosis Strategy using Bayesian Network for Complex Wiring Networks

Abstract In this paper, a distributed diagnosis strategy using reflectometry is proposed. It consists in making reflectometry measurements at different spots of a highly complex wiring network simultaneously in order to reduce ambiguities caused by multipath signals propagation. Although the problem of sensors number optimization is greatly studied in the literature, it is not well investigated in complex wiring networks diagnosis. The proposed approach is based on two principles which are sensors number and location optimisation using Bayesian Networks and measure uncertainty estimation. It consists in four steps: (1) sensors implementation in a deterministic case, (2) influential parameters on diagnosis measure identification, (3) diagnosis measure modelling using Bayesian Networks, (4) sensor number and location optimization. Here, the main objective is to minimize both sensors number and diagnosis measure uncertainty.