Atik, F.Sarucan, A.2023-11-112023-11-11202397830313977382367-3370https://doi.org/10.1007/978-3-031-39774-5_52https://hdl.handle.net/20.500.13091/4767Intelligent and Fuzzy Systems - Intelligence and Sustainable Future Proceedings of the INFUS 2023 Conference -- 22 August 2023 through 24 August 2023 -- -- 299549In order to effectively prevent corrosion and ensure a long service life, the galvanizing (alkaline zinc plating) process is a frequently used process in the industrial field. The galvanizing process, which has a wide range of applications, especially in the automotive industry, the construction sector and the white goods industry, offers various benefits, especially the production of corrosion-resistant and long-lasting products to reduce costs. As a process with a large number of parameters, Galvanized coating can be made more efficient for industrial enterprises. In order to optimize the process, Taguchi method and fuzzy logic were used in the study. 8 factors and 4 performance characteristics that are effective in the process were tried to be improved with 27 experiments determined according to the Taguchi method. In order to find the optimal levels of the parameters, the signal-to-noise (S/N) ratio was determined and the best combination of factors was determined. In order to test the effectiveness and efficiency of this approach, verification experiments were conducted and the results were presented. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.eninfo:eu-repo/semantics/closedAccessAlkaline zinc coatingFuzzy LogicTaguchiAutomotive industryComputer circuitsConstruction industryCorrosion resistanceCorrosion resistant coatingsTaguchi methodsZinc coatingsAlkaline zinc coatingAlkalinesFuzzy-LogicGalvanisingLong service lifeModel-based OPCOptimisationsPlating processTaguchiTaguchi's methodsFuzzy logicOptimization of Alkaline Zinc Plating Process in a Company Using Taguchi Model Based on Fuzzy LogicConference Object10.1007/978-3-031-39774-5_522-s2.0-85171977815