Michel Aldanondo

Bio: Michel Aldanondo is an academic researcher from University of Toulouse. The author has contributed to research in topics: Constraint satisfaction problem & Constraint (information theory). The author has an hindex of 14, co-authored 101 publications receiving 840 citations. Previous affiliations of Michel Aldanondo include École nationale d'ingénieurs de Tarbes & École Normale Supérieure.

Configuration for mass customization: how to extend product configuration towards requirements and process configuration

Abstract: In order to develop mass customization, many companies use configuration software to customize their products. Although many studies already exist about Product Configuration, Requirements and Process Configuration have not been studied in detail. As all these three aspects must be considered for mass customization, the aim of this paper is to show how Product Configuration, when considered as a constraint satisfaction problem, can be extended upstream towards Requirements Configuration and downstream towards Process Configuration. Product Configuration basics are first reviewed thanks to a constraint based approach, and an analysis of industrial configuration situations is done in order to clarify mass customization needs in terms of configuration. Then upstream Requirements Configuration and downstream Process Configuration are defined and generic models are proposed. It is shown that the proposed elements allow a global and consistent flow of configuration activities. A detailed example illustrates the different configuration problems and a discussion terminates the paper.

Mass customization and configuration: Requirement analysis and constraint based modeling propositions

Abstract: The purpose of this paper is, on the one hand, to identify to define and classify customization requirements and, on the other hand, to evaluate how generic modeling and configuration assistance within the Constraint Satisfaction Problem (CSP) framework can fulfil the requirements. The aim is to provide commercial configurator knowledge base designers with constraint based generic modeling elements for customizable industrial product. A first part recalls the main trends of the configuration problem. In a second part divided in four sections corresponding with different requirement set; each section proposes a definition of the requirement set, some CSP based modeling elements and a discussion about adequacy of relevant configuration assistance techniques.

Expert configurator for concurrent engineering: Cameleon software and model

Abstract: 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.

Design Prototypes: A Knowledge Representation Schema for Design

Abstract: A prevalent and pervasive view of designing is that it can be modeled using variables and decisions made about what values should be taken by these variables. The activity of designing is carried out with the expectation that the designed artifact will operate in the natural world and the social world. These worlds impose constraints on the variables and their values; so, design could be described as a goal-oriented, constrained, decision- making activity. However, design distinguish- es itself from other similarly described activities not only by its domain but also by additional necessary features. Designing involves exploration, exploring what variables might be appropriate. The process of explo- ration involves both goal variables and deci- sion variables. In addition, designing involves learning: Part of the exploration activity is learning about emerging features as a design proceeds. Finally, design activity occurs within two contexts: the context within which the designer operates and the context produced by the developing design itself. The designer’s perception of what the context is affects the implication of the context on the design. The context shifts as the designer’s perceptions change. Design activity can be now characterized as a goal-oriented, con- strained, decision-making, exploration, and learning activity that operates within a con- text that depends on the designer’s percep- tion of the context.

A review of methods for capacity identification in Choquet integral based multi-attribute utility theory: Applications of the Kappalab R package

Abstract: The application of multi-attribute utility theory whose aggregation process is based on the Choquet integral requires the prior identification of a capacity. The main approaches to capacity identification proposed in the literature are reviewed and their advantages and inconveniences are discussed. All the reviewed methods have been implemented within the Kappalab R package. Their application is illustrated on a detailed example.