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Data-driven modeling of mechanical properties of cast iron using fuzzy logic
Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).ORCID iD: 0000-0003-1303-9791
Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).ORCID iD: 0000-0001-6671-6157
Jönköping University, School of Engineering, JTH, Materials and Manufacturing.ORCID iD: 0000-0001-5609-5430
Jönköping University, School of Engineering, JTH, Materials and Manufacturing.ORCID iD: 0000-0002-3024-9005
2020 (English)In: Fuzzy Systems and Data Mining VI: Proceedings of FSDM 2020 / [ed] Antonio J. Tallón-Ballesteros, Amsterdam: IOS Press, 2020, p. 656-662Conference paper, Published paper (Refereed)
Abstract [en]

For many industries, an understanding of the fatigue behavior of cast iron is important but this topic is still under extensive research in materials science. This paper offers fuzzy logic as a data-driven approach to address the challenge of predicting casting performance. However, data scarcity is an issue when applying a data-driven approach in this field; the presented study tackled this problem. Four fuzzy logic systems were constructed and compared in the study, two based solely upon experimental data and the others combining the same experimental data with data drawn from relevant literature. The study showed that the latter demonstrated a higher accuracy for the prediction of the ultimate tensile strength for cast iron.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2020. p. 656-662
Series
Frontiers in Artificial Intelligence and Applications, ISSN 0922-6389, E-ISSN 1879-8314 ; 331
Keywords [en]
Fuzzy logic system, Data scarcity, Fatigue related properties prediction, Cast iron components
National Category
Materials Engineering Computer Engineering
Identifiers
URN: urn:nbn:se:hj:diva-51085DOI: 10.3233/FAIA200743ISI: 000661247100064Scopus ID: 2-s2.0-85101524360ISBN: 978-1-64368-134-4 (print)ISBN: 978-1-64368-135-1 (electronic)OAI: oai:DiVA.org:hj-51085DiVA, id: diva2:1505318
Conference
6th International Conference on Fuzzy Systems and Data Mining (FSDM 2020), 13-16 November 2020, Xiamen, China
Note

The conference was originally due to be held from 13-16 November 2020 in Xiamen, China, but was changed to an online conference held on the same dates due to ongoing restrictions connected with the COVID-19 pandemic.

Available from: 2020-11-30 Created: 2020-11-30 Last updated: 2023-10-02Bibliographically approved

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Tan, HeTarasov, VladimirFourlakidis, VasileiosDiószegi, Attila

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