Development of an Expert System to Support the Decision-Making Process on the Shop Floor
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-23844-4_14
Reference19 articles.
1. Tavana, M., & Hajipour, V. (2019). A practical review and taxonomy of fuzzy expert systems: methods and applications. Benchmarking: An International Journal.
2. Ng, S., Tai, V. C., Tan, Y. C., Abd Rahman, N. F. (2021). SFlex-WMS: A novel multi-expert system for flexible logistics and warehouse operation in the context of Industry 4.0. SHS Web of Conferences, 124, 10002. https://doi.org/10.1051/shsconf/202112410002
3. Ramezani, J., Jassbi, J. (2017). A hybrid expert decision support system based on artificial neural networks in process control of plaster production—An industry 4.0 perspective. In L. Camarinha-Matos, M. Parreira-Rocha, J. Ramezani (Eds.) Technological innovation for smart systems. DoCEIS 2017. IFIP Advances in information and communication technology (vol. 499). Springer. https://doi.org/10.1007/978-3-319-56077-9_5
4. Cobos-Guzman, S., Verdú, E., Herrera-Viedma, E., et al. (2020). Fuzzy logic expert system for selecting robotic hands using kinematic parameters. J Ambient Intelligence and Humanized Computing, 11, 1553–1564. https://doi.org/10.1007/s12652-019-01229-x
5. de Moura, R. L., Franqueira, V. N. L., Pessin, G. (2021). Towards safer industrial serial networks: an expert system framework for anomaly detection. In: IEEE 33rd international conference on tools with artificial intelligence (ICTAI 2021) (pp. 1197–1205). https://doi.org/10.1109/ICTAI52525.2021.00189.
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