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Application of ANOVA in interval type-2 fuzzy logic systems for modeling the process of ceramic coating preparation in the foundry industry

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Abstract

The preparation of ceramic coatings is a complex process, impacted by the variability and uncertainty inherent in its operational parameters. This coating, applied to sand cores in the iron casting production of monoblocs, serves primarily to shield them from physical and chemical reactions with molten metal that could lead to penetration. This study tackles such complexity by employing a type-2 interval fuzzy logic system (IT2 FLS), notably integrating analysis of variance (ANOVA) for statistical inference within the model. This methodology facilitates a detailed and quantitative analysis of the operational variables’ influence, enhancing both the understanding and the accuracy of the IT2 FLS model. The IT2 FLS implementation exhibited \(96\%\) effectiveness in explaining the process variability, identifying the paint tank’s density as the most influential variable, unlike ambient temperature, which had a lesser impact. Furthermore, the IT2 FLS model not only displayed superior fit (\({R}^{2}=0.96\)) compared to type-1 fuzzy logic systems (\({R}^{2}=0.80\)) and linear regression models (\({R}^{2}=0.49\)), but also revealed, through cross-validation, a significant predictive capacity (\({R}_{prediction}^{2}=0.86\)). These results validate the robustness of the IT2 FLS against conventional methods and highlight the novelty of integrating ANOVA to deepen the statistical analysis of the IT2 FLS model. Such an approach provides an effective tool for understanding and enhancing complex manufacturing processes, offering value to industries aiming to optimize efficiency and quality.

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References

  1. Busarac N, Adamovic D, Grujovic N, Zivic F (2022) Lightweight materials for automobiles. IOP Conf Ser Mater Sci Eng 1271:. https://doi.org/10.1088/1757-899x/1271/1/012010

  2. Zhang W, Xu J (2022) Advanced lightweight materials for automobiles: a review. Mater Des 221. https://doi.org/10.1016/j.matdes.2022.110994

  3. Nwaogu UC, Tiedje NS (2011) Foundry coating technology: a review. Mater Sci Appl 02: https://doi.org/10.4236/msa.2011.28155

  4. Nwaogu UC, Poulsen T, Stage RK et al (2011) New sol-gel refractory coatings on chemically-bonded sand cores for foundry applications to improve casting surface quality. Surf Coat Technol 205:. https://doi.org/10.1016/j.surfcoat.2011.02.042

  5. Cadavid-Iglesias EH, Vargas-Galvis F, López-Gómez ME et al (2018) Manufacture of oxy-acetylene thermally sprayed coatings on refractory substrates from unconventional feedstock material. DYNA (Colombia) 85:. https://doi.org/10.15446/dyna.v85n205.65539

  6. (2000) Foseco Ferrous Foundryman’s Handbook

  7. Arinez JF, Chang Q, Gao RX et al (2020) Artificial intelligence in advanced manufacturing: current status and future outlook. Journal of Manufacturing Science and Engineering, Transactions of the ASME 142:. https://doi.org/10.1115/1.4047855

  8. Pervez M, Kamal T (2020) Comparative study of modern control techniques for optimal dynamic nonlinear process control. In: Proceedings - 2020 23rd IEEE International Multi-Topic Conference, INMIC 2020. https://doi.org/10.1109/INMIC50486.2020.9318161

  9. Liu KW, Kuo CC (2022) Application of the fuzzy-based Taguchi method for servo stamping curve. Int J Adv Manuf Technol 121:. https://doi.org/10.1007/s00170-022-09820-x

  10. Sathish Kumar A, Naveen S, Vijayakumar R et al (2023) An intelligent fuzzy-particle swarm optimization supervisory-based control of robot manipulator for industrial welding applications. Sci Rep 13:. https://doi.org/10.1038/s41598-023-35189-2

  11. Ivančan J, Lisjak D (2021) New FMEA risks ranking approach utilizing four fuzzy logic systems. Machines 9:. https://doi.org/10.3390/machines9110292

  12. Mendel JM (2017) Uncertain Rule-Based Fuzzy Systems: Introduction and New Directions. Springer, Cham. https://doi.org/10.1007/978-3-319-51370-6

  13. Erdem P, Akyuz E (2021) An interval type-2 fuzzy SLIM approach to predict human error in maritime transportation. Ocean Eng 232:. https://doi.org/10.1016/j.oceaneng.2021.109161

  14. Patel G C M, Shettigar AK, Parappagoudar MB (2018) A systematic approach to model and optimize wear behaviour of castings produced by squeeze casting process. J Manuf Process 32:. https://doi.org/10.1016/j.jmapro.2018.02.004

  15. AbouOmar MS, Su Y, Zhang H et al (2022) Observer-based interval type-2 fuzzy PID controller for PEMFC air feeding system using novel hybrid neural network algorithm-differential evolution optimizer. Alex Eng J 61:. https://doi.org/10.1016/j.aej.2021.12.072

  16. Hannan MA, Ghani ZA, Hoque MM et al (2019) Fuzzy logic inverter controller in photovoltaic applications: issues and recommendations. IEEE Access 7:. https://doi.org/10.1109/ACCESS.2019.2899610

  17. Méndez GM, Montes Dorantes PN, Mexicano Santoyo A (2019) Interval type-2 fuzzy logic systems optimized by central composite design to create a simplified fuzzy rule base in image processing for quality control application. Int J Adv Manuf Technol 102:. https://doi.org/10.1007/s00170-019-03354-5

  18. Şahin İ, Ulu C (2022) Altitude control of a quadcopter using interval type-2 fuzzy controller with dynamic footprint of uncertainty. ISA Trans. https://doi.org/10.1016/j.isatra.2022.08.020

    Article  Google Scholar 

  19. Kayisli K (2023) Super twisting sliding mode-type 2 fuzzy MPPT control of solar PV system with parameter optimization under variable irradiance conditions. Ain Shams Eng J 14:. https://doi.org/10.1016/j.asej.2022.101950

  20. Chen Y, Li C, Yang J (2023) Design and application of Nagar-Bardini structure-based interval type-2 fuzzy logic systems optimized with the combination of backpropagation algorithms and recursive least square algorithms. Expert Syst Appl 211:. https://doi.org/10.1016/j.eswa.2022.118596

  21. Ontiveros-Robles E, Melin P, Castillo O (2018) Comparative analysis of noise robustness of type 2 fuzzy logic controllers. Kybernetika 54. https://doi.org/10.14736/kyb-2018-1-0175

  22. Jianzhong S, Shaohua L, Yong Y, Rong L (2019) An improved general type-2 fuzzy sets type reduction and its application in general type-2 fuzzy controller design. Soft Comput 23:. https://doi.org/10.1007/s00500-019-03889-5

  23. Karnik NN, Mendel JM (1998) Introduction to type-2 fuzzy logic systems. In: 1998 IEEE International Conference on Fuzzy Systems Proceedings - IEEE World Congress on Computational Intelligence. https://doi.org/10.14736/kyb-2018-1-0175

  24. N. Karnik N, M. Mendel J (2001) Operations on type-2 fuzzy sets. Fuzzy Sets Syst 122:. https://doi.org/10.1016/S0165-0114(00)00079-8

  25. Wang YC, Chen T, Yeh YL (2019) Advanced 3D printing technologies for the aircraft industry: a fuzzy systematic approach for assessing the critical factors. Int J Adv Manuf Technol 105:. https://doi.org/10.1007/s00170-018-1927-8

  26. Zhou H, Zhang C, Tan S et al (2021) Design of the footprints of uncertainty for a class of typical interval type-2 fuzzy PI and PD controllers. ISA Trans 108:. https://doi.org/10.1016/j.isatra.2020.08.009

  27. Praharaj M, Sain D, Mohan BM (2022) Development, experimental validation, and comparison of interval type-2 Mamdani fuzzy PID controllers with different footprints of uncertainty. Inf Sci (N Y) 601:. https://doi.org/10.1016/j.ins.2022.03.095

  28. Lu TC (2015) Genetic-algorithm-based type reduction algorithm for interval type-2 fuzzy logic controllers. Eng Appl Artif Intell 42:. https://doi.org/10.1016/j.engappai.2015.02.012

  29. Tayyebi S, Soltanali S (2017) A new approach of GA-based type reduction of interval type-2 fuzzy model for nonlinear MIMO system: application in methane oxidation process. Chemometr Intell Lab Syst 167:. https://doi.org/10.1016/j.chemolab.2017.06.004

  30. Barbur VA, Montgomery DC, Peck EA (1994) Introduction to linear regression analysis. Statistician 43:. https://doi.org/10.2307/2348362

  31. Aisbett J, Rickard JT, Morgenthaler DG (2010) Type-2 fuzzy sets as functions on spaces. IEEE Trans Fuzzy Syst 18:. https://doi.org/10.1109/TFUZZ.2010.2046176

  32. Khanesar MA, Mendel JM (2016) Maclaurin series expansion complexity-reduced center of sets type-reduction + defuzzification for interval type-2 fuzzy systems. In: 2016 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE 2016

  33. Höhle U (2003) Metamathematics of fuzzy logic. Fuzzy Sets Syst 133:. https://doi.org/10.1016/s0165-0114(02)00356-1

  34. Wu D, Mendel JM (2009) Enhanced Karnik-Mendel algorithms. IEEE Trans Fuzzy Syst 17:. https://doi.org/10.1109/TFUZZ.2008.924329

  35. Montgomery DC, Peck EA, Vinning GG, Ryan AG (2013) Solutions manual to accompay: introduction to linear regression analysis. Wiley, Hoboken

    Google Scholar 

  36. Li J, Gao F, Lin S et al (2023) Quantum k-fold cross-validation for nearest neighbor classification algorithm. Phys A Stat Mech Appl 611:. https://doi.org/10.1016/j.physa.2022.128435

  37. Shi Y sheng, Zhang J liang, Wen S feng et al (2021) Additive manufacturing and foundry innovation. China Foundry 18

  38. Barnes HA (1996) Rheology: principles, measurements and applications. Powder Technol 86:. https://doi.org/10.1016/s0032-5910(96)90008-x

  39. Joyce M, Rebros M, Ramrattan S (2008) Adapting more progressive refractory coating measurement controls. Int J Met 2:. https://doi.org/10.1007/BF03355434

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Authors and Affiliations

  1. Corporación Mexicana de Investigación en Materiales (COMIMSA), Calle Ciencia y Tecnología #790, C.P. 25290, Saltillo, Coahuila, Mexico

    Gerardo Daniel Olvera-Romero

  2. Facultad de Ingeniería, Universidad Autónoma de Coahuila, Ciudad Universitaria, Carretera a México Km. 13, Arteaga, Coahuila, Mexico

    Gerardo Daniel Olvera-Romero & Jesús Salvador Luna-Álvarez

  3. Facultad de Sistemas, Universidad Autónoma de Coahuila, Ciudad Universitaria, Carretera a México Km. 13, Arteaga, Coahuila, Mexico

    Rolando Praga-Alejo, David González-González & Homero de León-Delgado

  4. Instituto Tecnológico de Saltillo, Tecnológico Nacional de México, V. Carranza #2400, Col. Tecnológico, C.P. 25280, Saltillo, Coahuila, Mexico

    Mario Rodríguez-Reyes, Dagoberto Vázquez-Obregón & José Flores-Cárdenas

  5. Casting Solutions, SAPI DE CV, Topacio #524, C.P. 25204, Saltillo, Coahuila, Mexico

    Héctor Mancha-Molinar

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  1. Gerardo Daniel Olvera-Romero
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  2. Rolando Praga-Alejo
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All authors contributed to the study conception and design.

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Correspondence to Rolando Praga-Alejo.

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Olvera-Romero, G.D., Praga-Alejo, R., Rodríguez-Reyes, M. et al. Application of ANOVA in interval type-2 fuzzy logic systems for modeling the process of ceramic coating preparation in the foundry industry. Int J Adv Manuf Technol (2024). https://doi.org/10.1007/s00170-024-13563-2

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