Aide à la décision multicritère

L'aide à la décision multicritère constitue une branche d'étude majeure de la recherche opérationnelle impliquant plusieurs écoles de pensée, principalement américaine avec les travaux de Thomas L. Saaty et européenne avec ceux de Bernard Roy et du LAMSADE (Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision). Il s'agit de méthodes et de calculs permettant de choisir la meilleure solution ou la solution optimale parmi tout un ensemble de solutions, l'alternative de type OUI-NON n'étant qu'un cas particulier du cas général. Un abus de langage courant consiste à la confondre avec l'informatique décisionnelle (en anglais "business intelligence") et l'aide à la décision multicritère. L'informatique décisionnelle est dédiée à l'exploitation de données (query/reporting et data mining, principalement) destinée à l'élaboration de synthèses multi-niveaux. Outils d'aide à la décision (OAD) Les outils d'aide à la décision permettent d'apporter des réponses

Quantum-based approach for laboratory risk assessment and decision-making

Ruoxing Liao

With the rising focus on academic safety, there has been an effort to improve the academic safety climate and develop lab-specific risk assessment tools. Despite the progress made in recent years, there is still a deficit of reliable data statistics on safety events and risk assessment in academia, making it difficult to perform full-scale analysis. Moreover, the rapid turnover of personnel and the highly dynamic research tasks in a laboratory environment impede the implementation of classical and well-established risk management strategies, which are usually time-consuming and resource-intensive. Laboratory safety management is always challenging due to lack of data and effective methods. The end of safety management is usually the selection of risk mitigation measures. In the laboratory risk management process, decisions are often made through discussion and compromise. In this regard, it would be beneficial to provide a tool that can support in resource allocation and prioritization of actions. The goal of this project is to develop a decision support tool to assist in the selection of optimal and appropriate preventive or corrective measures in the lab safety management process. The use of decision tools such as Multi-Criteria Decision Making (MCDM) can effectively abstract complex laboratory management problems into a decision framework. This study focuses on the ranking process of competitive corrective measures. Combining the results of interviews and questionnaires, five evaluation criteria were proposed for the normative process of multi-criteria decision making. They are: Residual Risk, Risk reduction, Personnel reliability, Technical reliability, and Cost. classical methods TOPSIS and WSM have been evaluated during the study, and emerging quantum decision making methods have been explored. All three methods are used to simulate the laboratory safety decision making process, and they all present good consistency. Different weighting methods have also been applied to the model and two case studies have been conducted. The first case study is designed to construct the model and verify its feasibility, and the second model is used to investigate the process of group decision making. By applying different MCDM methods, the obtained results are discussed and compared to verify the stability and accuracy of the model. The approach proposed in this research is a promising tool. It offers the possibility to be compatible with different MCDM methods and risk assessment methods, and the proposed decision model could be used as a decision support system to help lab managers make better decisions, or it can provide a neutral point of view as an aid. Future work may include fine-tuning the model. In the following stage, decision criteria should be precisely defined, and corresponding quantitative formulas should be proposed to serve the flexible and dynamic laboratory environment.

2022

Evaluation de stratégies pour la gestion du risque sismique du bâtiment

Vincent Pellissier

This document presents the results of a research on seismic risk management. It echoes the worldwide trend of increasing awareness of the importance of this risk and represents a contribution to the effort of research. In order to manage risk in a rational way, it is necessary to quantify it. The first part of this research consists in evaluating the seismic risk of a portfolio of buildings. The selected portfolio is the city of Aigle located in the center of the Swiss Alps. The evaluation was based on a seismic inventory of the city, enabling, through a global approach, to consider the behavior of the buildings. Different losses (life, building, furniture) could be estimated for several scenarii of seismic hazards intensities. Knowing the probability of occurency of these intensities, as well as the uncertainties of the constitutive parameters, it was then possible to quantify the risk affecting the selected portfolio of buildings. The maximum potential loss for the studied area was also estimated. As a result, a reproducible risk estimation model was developed with its constitutive parameters. The obtained results provide information on potential losses, on the level of insurance premium as well as on elements of reinsurance. Seismic risk management, because of its complexity and the extent of the consequences ensuing from major events, requires a different approach from other natural risks. In the second part of this research, management tools are therefore developed in order for decision makers to face these particularities. A comprehensive management framework is elaborated. This framework makes it possible to deal with the complexity of seismic risk, which not only stems from its inherent specificities but also from the multiplicity of decision criteria as well as the variety of actors within the system. The definition of protection objectives receives special attention in this research. Construction codes usually fix safety levels for new constructions. For existing buildings on the other hand, there are no such provisions. The present research proposes a method for fixing this protection level. This method also considers the often contradictory principles of precaution and proportionality. An innovative catalogue of mitigation measures are then proposed, classified according to their influence on the components of risk. These measures can be focused on prevention, protection or intervention. They have an impact on the hazard, the vulnerability or on the exposed value at the considered risk. Consequently, different strategies are built to be later evaluated and compared. For this work, a strategy is considered to be a panel of measures that have an impact on the constitutive elements of risk. The decision-making process is regarded as a systemic approach considering the multiplicity of decision criteria and actors. A multicriteria analysis method based on an outranking philosophy is adopted for the comparison. Criteria are proposed for individual buildings as well for a portfolio of buildings. Applications of the decision-making process on pilot projects illustrate the methodology and provide practical recommendations. The pilot project of the city of Aigle was the guideline for the presented research, which aimed to deal with the complexity of seismic risk management in the most comprehensive way possible.

EPFL2004

Machine Tool Use Phase

Ioan Oliver Avram

This thesis is motivated from the fundamental decision problem in today's manufacturing industry which could be summarized as one simple question: how is it possible to achieve economic growth by taking advantage of the latest technologies while protecting the environment? The machine tool has undergone a remarkable change in recent years and the classical concept of an independent, manually operated machine tool, specially dedicated to a particular machining process no longer belongs to the production environment. The increasing usage of computer control and measuring equipment as well as workpiece and tool handling devices has transformed the machine tool into a sophisticated hybrid production system having a lower demand for human supervision of the process. All these efforts are gathered together in order to achieve a high productivity system able to machine different parts respecting quality requirements at the lowest cost. In addition, increasing attention to the environmental and health impacts by governmental regulations and by growing awareness in society is forcing manufacturers to find environmentally friendly designs and machining strategies. The objective of this research is to propose a multicriteria decision aid methodology (MCDA) for evaluation of the use phase of a machine tool system by jointly considering economical, technical and environmental criteria which allows the decision maker to be in a better position to make sustainable decisions. The evaluation is carried out at two levels by addressing the process level with its local cutting area effects and the main activities of the machine tool system by giving full consideration to reduction/elimination of the cutting fluid and reduction of the overall energy consumption. After carefully reviewing previous research, a consistent hierarchical evaluation criteria structure and an entity relationship diagram characterizing the organizational scheme of a database, which stores the data to be used in the evaluation process, is proposed for each level. As a second step, this thesis proposes a model for estimation of the mechanical energy requirements of the cutting subsystem of a machine tool based on the cutter location data, the cutting parameters and the technical specifications of the spindle and feed axes. The MCDA methodology and the energy consumption model were implemented in a software tool using the VBA (Visual Basic for Applications) language and was validated through various tests consisting in the machining of different milling and drilling features of a prismatic part by employing different cutting parameters and cooling/lubrication alternatives. In addition to the cutting tests, an extensive monitoring of the power share amongst the main subsystems of a modern machining center was carried out and a power data collection framework was proposed. The acquisition, interpretation and storage of the experimental data were supported by a measurement platform developed in the LabVIEW environment.

EPFL2010