MULTI-RESPONSE OPTIMIZATION OF ELECTRICAL DISCHARGE MACHINING OF 17-4 PH SS USING TAGUCHI-BASED GREY RELATIONAL ANALYSIS

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GERÇEKCİOĞLU E., Albaşkara M.

Archives of Metallurgy and Materials, cilt.68, sa.3, ss.861-868, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 68 Sayı: 3
  • Basım Tarihi: 2023
  • Doi Numarası: 10.24425/amm.2023.145448
  • Dergi Adı: Archives of Metallurgy and Materials
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, Aerospace Database, Communication Abstracts, Compendex, Metadex, Directory of Open Access Journals, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.861-868
  • Anahtar Kelimeler: 17-4 PH SS, ANOVA, EDM, Surface Characterization, Taguchi-based Grey Relational Analysis
  • Erciyes Üniversitesi Adresli: Evet

Özet

Multiple response optimization of the machining of 17-4 PH stainless steel material, which is difficult to process with traditional methods, with EDM was made by Taguchi-based grey relational analysis method. Surface roughness (Ra), material removal rate (MRR), and electrode wear rate (EWR) were the responses, while current, pulse-on time, pulse-off time, and voltage were chosen as process parameters. According to the multi-response optimization, the experiment level that gave the best result was A1B2C2D2. Optimum machining outputs were found as A1B3C1D1 using the Taguchi method. As a result of the Taguchi analysis and ANOVA, it was determined that the significant parameters according to multiple performance characteristics were current (56.22%) and voltage (22.40%). The surfaces of the best GRG and optimal sample were examined with XRD, SEM and EDX analysis and the effects on the surfaces were compared.