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Publications significatives

  • Handling soft constraints in hoist scheduling problems: the fuzzy approach

    Références :
    Hélène Fargier et Jacques Lamothe. « Handling soft constraints in hoist scheduling problems: the fuzzy approach ». In : Engineering Applications of Artificial Intelligence 14.3 (juin 2001). P. 387--399. ISSN : 0952-1976. DOI : 10.1016/S0952-1976(01)00008-2.
    The Hoist Scheduling Problem (HSP) deals with the scheduling of hoists that move products between tanks in electroplating facilities that perform chemical surface treatments. In HSP, the gradual effect of soaking times (operation duration in tanks) on the quality of treatment can be represented by means of fuzzy sets: the satisfaction degree in a fuzzy interval models a quality evaluation of the chemical treatment. When temporal bounds are required, an implicit relaxation of these flexible constraints can thus be performed so as to meet the due-date. When the objective is rather a minimization of the makespan, a bi-criteria decision problem has to be dealt with that involves both the quality and the line throughput optimization. Rather than an aggregation of the two evaluations under the form of a single criterion, we propose a decision-support approach that quickly converges to a good trade-off between the two criteria. (C) 2001 Elsevier Science Ltd. All rights reserved.
    Keywords: due-dates, fuzzy constraints, fuzzy logic, Heuristics, Hoist scheduling, line, search algorithms, systems
  • Expert configurator for concurrent engineering: Cameleon software and model

    Références :
    Michel Aldanondo, Sylvie Rougé et Mathieu Véron. « Expert configurator for concurrent engineering: Cameleon software and model ». In : Journal of Intelligent Manufacturing 11.2 (avr. 2000). P. 127--134. ISSN : 0956-5515. DOI : 10.1023/A:1008982531278.
    This paper, dealing with discrete production systems, has two goals. The first one is to identify cases in which the use of expert configurator software is a significant improvement for concurrent engineering achievement. Since the industrial implementation of these configurators is often tricky, the second issue of this paper is to present a model that allows to specify the industrial problem before implementation. This paper is divided into three sections. We first quickly recall the main trends of concurrent engineering and the related expert configurator interests. Then, the basic behavior and solutions for expert configurators are presented and the modeling requirements are pointed out. The third part is dedicated to the presentation, illustrated with an example, of our model and our method.
    Keywords: configuration, information system, product diversity, product modeling
  • A framework for a knowledge-based system for risk management in concurrent engineering

    Références :
    Emmanuel Caillaud, Didier Gourc, Luis Antonio Garcia, Rose Crossland et Chris McMahon. « A framework for a knowledge-based system for risk management in concurrent engineering ». In : Concurrent Engineering-Research and Applications 7.3 (sept. 1999). P. 257--267. ISSN : 1063-293X. DOI : 10.1177/1063293X9900700307.
    Knowledge is a requirement for concurrent engineering, and therefore an approach to capture and organise the different knowledge to be taken into account in concurrent engineering is proposed. This approach, known as the "MEthodology for Knowledge Engineering for Concurrent Engineering" (MEKECE) is a dedicated application of knowledge engineering methodologies to concurrent engineering that involves a combination of case based reasoning and expert systems approaches aimed at managing risk. To manage concurrent engineering specific risks, the knowledge of the different tasks constituting product development must be captured and organised, and information on the causes of risks that have a threshold effect on time and on cost must be available in a convenient form for the participants in the process. The framework of this knowledge based system for risk management in concurrent engineering is presented.
    Keywords: concurrent engineering, Design, knowledge, knowledge based system, manufacturing, Risk management