Modeling and determining the optimal conditions for the jet electrochemical machining (Jet-ECM) process is critical. In this study, a hybrid approach combining numerical and design of experiments (DOE) methods have been applied to model and determine the optimal conditions for Jet-ECM. The voltage (V), inner tool diameter (I), initial machining gap (G), and electrolyte conductivity (C) are considered input variables. Additionally, dimensional accuracy (E) and machining depth (D) are response variables. Twenty-seven numerical simulations have been performed using the Box–Behnken design to implement the response surface methodology (RSM). Consequently, two mathematical models have been obtained for these response variables. The effects of the input variables on the response variables are investigated using statistical techniques such as variance analysis. Furthermore, the desirability function approach has been applied to determine the optimal conditions for dimensional accuracy and depth of machining. The results show that the optimal values for achieving maximum depth of machining while maintaining a dimensional accuracy of 0.05 mm are as follows: electrolyte conductivity of 8 S/m, voltage of 36.9 V, initial machining gap of 200 μm, and inner tool diameter of 0.4 mm.
Mehrvar, A., Motamedi, M., & Jamalpour, A. (2023). Modeling of Jet Electrochemical Machining Using Numerical and Design of Experiments Methods. Scientia Iranica, (), -. doi: 10.24200/sci.2023.60185.6650
MLA
Ali Mehrvar; Mohsen Motamedi; Abouzar Jamalpour. "Modeling of Jet Electrochemical Machining Using Numerical and Design of Experiments Methods". Scientia Iranica, , , 2023, -. doi: 10.24200/sci.2023.60185.6650
HARVARD
Mehrvar, A., Motamedi, M., Jamalpour, A. (2023). 'Modeling of Jet Electrochemical Machining Using Numerical and Design of Experiments Methods', Scientia Iranica, (), pp. -. doi: 10.24200/sci.2023.60185.6650
VANCOUVER
Mehrvar, A., Motamedi, M., Jamalpour, A. Modeling of Jet Electrochemical Machining Using Numerical and Design of Experiments Methods. Scientia Iranica, 2023; (): -. doi: 10.24200/sci.2023.60185.6650