In this paper, the authors describe the development of a Decision Support System (DSS) in the spunlace nonwoven production industry. The suggested DSS utilizes domain ontology and a collaborative platform that allows operators to share and exchange experiences in the industrial diagnosis in order to have new ideas and useful information for collaborative decision-making. One of the main aspects addressed in the decision-making process was the knowledge management of the most frequently breakdowns of machines as the card, aquajet etc. This paper introduces the architecture of the system, including several modules such as, Reasoning engine and Similarity module, etc. The decision-making is reinforced by a case-based reasoning to recommend solutions where previously solved cases (problem) are compared to recently encountered ones using the same ontology to define similarity between cases. Some experiments have been conducted in INOTIS enterprise to indicate the efficiency of the proposed system.
-In spunlace nonwovens industry, the maintenance task is very complex, it requires experts and operators collaboration. In this paper, we propose a new approach integrating an agentbased modelling with case-based reasoning that utilizes similarity measures and preferences module. The main purpose of our study is to compare and evaluate the most suitable similarity measure for our case. Furthermore, operators that are usually geographically dispersed, have to collaborate and negotiate to achieve mutual agreements, especially when their proposals (diagnosis) lead to a conflicting situation. The experimentation shows that the suggested agent-based approach is very interesting and efficient for operators and experts who collaborate in INOTIS enterprise.
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