An eco-knowledge tool to support eco-design implementation inside design departments

In last years, an increasing attention on environmental matters is registered. Companies face environmental matters to increase the environmental performances of their products, forced by numerous legislations, normative and protocols and induced to the growing attention of consumers toward environmentally friendly products. However, observing the industrial context, it emerges there are several barriers for implementation of eco-design strategies inside design departments. The paper presents a tool which aims at both providing a basic guide on environmental sustainability issues and favouring the knowledge sharing among the different actors of the product design process. The core of the tool is a repository in which company materials, organized and collected in different forms, are collected. The repository contains several parts: training, guidelines, knowledge and milestone, accordingly to the type, structure and form of materials stored. The eco-design tool functions, structure, and workflow are presented and then preliminary test cases are described

Computational narrative mapping for the acquisition and representation of lessons learned knowledge

Lessons learned knowledge is traditionally gained from trial and error or narratives describing past experiences. Learning from narratives is the preferred option to transfer lessons learned knowledge. However, learners with insufficient prior knowledge often experience difficulties in grasping the right information from narratives. This paper introduces an approach that uses narrative maps to represent lessons learned knowledge to help learners understand narratives. Since narrative mapping is a time-consuming, labor-intensive and knowledge-intensive process, the proposed approach is supported by a computational narrative mapping (CNM) method to automate the process. CNM incorporates advanced technologies, such as computational linguistics and artificial intelligence (AI), to identify and extract critical narrative elements from an unstructured, text-based narrative and organize them into a structured narrative map representation. This research uses a case study conducted in the construction industry to evaluate CNM performance in comparison with existing paragraph and concept mapping approaches. Among the results, over 90% of respondents asserted that CNM enhanced their understanding of the lessons learned. CNM’s performance in identifying and extracting narrative elements was evaluated through an experiment using real-life narratives from a reminiscence study. The experiment recorded a precision and recall rate of over 75%

Rule mining in maintenance: analysing large knowledge bases

Association rule mining is a very powerful tool for extracting knowledge from records contained in industrial databases. A difficulty is that the mining process may result in a huge set of rules that may be difficult to analyse. This problem is often addressed by an a priori filtering of the candidate rules, that does not allow the user to have access to all the potentially interesting knowledge. Another popular solution is visual mining, where visualization techniques allow to browse through the rules. We suggest in this article a different approach: generating a large number of rules as a first step, then drill-down the produced rule base using alternatively semantic analysis (based on a priori knowledge) and objective analysis (based on numerical characteristics of the rules). It will be shown on real industrial examples in the maintenance domain that UML Class Diagrams may provide an efficient support for subjective analysis, the practical management of the rules (display, sorting and filtering) being insured by a classical Spreadsheet

Approches organisationnelles pour la conception de systèmes multi-agents dédiés à la gestion des connaissances; Application aux projets d'ingénierie et d'innovation Composition du jury

Approches organisationnelles pour la conception de systèmes multi-agents dédiés à la gestion des connaissances; Application aux projets d’ingénierie et d’innovatio

Enhancing experience reuse and learning

International audienceno abstrac