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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 2, 2022.
Abstract: Currently, the industrial and economic environment is highly competitive, forcing companies to keep up with technological progress and to be efficient in terms of quality and responsiveness, not only to survive, but also to dominate the market. So, to achieve this goal, companies are always looking to master their production processes, as well as to enlarge their range of products, either by developing new products or by improving old ones. This confronts companies to many problems, including the identification of adequate and optimal production parameters for the development of their products. In this context, a decision making system based on digital twins (DT), case-based reasoning (CBR) and Ontologies is proposed. The originality of this work lies in the fact that it combines three emerging artificial intelligence tools for modeling, reasoning and decision making. Thus, this work proposes a new flexible and automated system that ensures an optimal selection of production parameters for a given complex product. An industrial case of study is developed to illustrate the effectiveness of the proposed approach.
ABADI Mohammed, ABADI Chaimae, ABADI Asmae and BEN-AZZA Hussain, “A Smart Decision Making System for the Selection of Production Parameters using Digital Twin and Ontologies” International Journal of Advanced Computer Science and Applications(IJACSA), 13(2), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130248
@article{Mohammed2022,
title = {A Smart Decision Making System for the Selection of Production Parameters using Digital Twin and Ontologies},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130248},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130248},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {2},
author = {ABADI Mohammed and ABADI Chaimae and ABADI Asmae and BEN-AZZA Hussain}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.