A modified approach on modeling-design-optimization procedure for cutting of pure titanium using wire electric discharge machining (WEDM)


Baytok Y., Aydin L., DEVECİ H. A., GÜLTÜRK E.

PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART E-JOURNAL OF PROCESS MECHANICAL ENGINEERING, cilt.238, sa.5, ss.2305-2319, 2024 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 238 Sayı: 5
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1177/09544089231166654
  • Dergi Adı: PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART E-JOURNAL OF PROCESS MECHANICAL ENGINEERING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.2305-2319
  • Anahtar Kelimeler: multiple nonlinear regression analysis, stability, Stochastic optimization, wire EDM
  • Kocaeli Üniversitesi Adresli: Evet

Özet

The main goal of this study is to introduce a modified approach to the modeling-design-optimization triple procedure for cutting pure titanium. The manufacturing process is selected as wire electric discharge machining. To achieve a smooth cutting operation of the pure titanium plate (grade 2), the independent cutting parameters, peak current, pulse off time, pulse on time, spark gap voltage, wire feed, and wire tension are taken into consideration. Their effects on machining rate, surface roughness, dimensional deviation, and wire wear ratio are also examined. The mathematical model of the process is determined with the multiple nonlinear neuroregression approach. Stability study that measures the ability to realize the cutting parameters was conducted during the modeling phase. This type of step has not been used as a criterion for model determination before in modeling studies. Comparisons were accomplished with the traditional and nontraditional models, and it is shown that the nontraditional models' accuracy was more reasonable. Besides, this study contains the design optimization of the manufacturing process parameters using modified version of different stochastic and derivative-free optimization methods: differential evaluation, random search, simulated annealing, and Nelder-Mead algorithm, (MDE, MRS, MSA and MNM) simultaneously.