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Interval Type-3 Fuzzy Decision Making in Material Surface Quality Control

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Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics

Part of the book series: Studies in Computational Intelligence ((SCI,volume 1096))

Abstract

Recently, we have witnessed that type-2 fuzzy has surpass the performance of type-1 in real-world scenarios. For this reason, it is interesting to investigate the area of type-3 fuzzy theory, and in this work, we are dealing with the application side of this theory. We illustrate the impact of type-3 in surface quality control. The method uses interval type-3 fuzzy to automate quality control. Surface roughness and porosity of the materials are utilized to estimate the quality of the material with a type-3 fuzzy approach. Material manufacturing needs accurate quality control and a type-3 approach is able to show superiority over type-2 and type-1 in this case.

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Authors and Affiliations

  1. Tijuana Institute of Technology, TecNM, Tijuana, Mexico

    Oscar Castillo & Patricia Melin

Authors
  1. Oscar Castillo
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  2. Patricia Melin
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Correspondence to Oscar Castillo .

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Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, BC, CP, Baja California, Mexico

    Oscar Castillo

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, BC, CP, Baja California, Mexico

    Patricia Melin

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Castillo, O., Melin, P. (2023). Interval Type-3 Fuzzy Decision Making in Material Surface Quality Control. In: Castillo, O., Melin, P. (eds) Hybrid Intelligent Systems Based on Extensions of Fuzzy Logic, Neural Networks and Metaheuristics. Studies in Computational Intelligence, vol 1096. Springer, Cham. https://doi.org/10.1007/978-3-031-28999-6_29

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