Optimization of Processing Parameters in ECM of Die Tool Steel Using Nanofluid by Multiobjective Genetic Algorithm

Area of Science:

• Materials Science
• Manufacturing Engineering
• Surface Engineering

Background:

• Electrochemical machining (ECM) of die tool steel using plain sodium nitrate electrolyte faces challenges with spike formation, hindering optimal material removal rate (MRR) and surface finish.
• Spikes impede the achievement of desired surface quality and efficiency in the electrochemical machining process for tool steels.

Purpose of the Study:

• To minimize spike formation during the electrochemical machining of high-carbon, high-chromium (HCHCr) die tool steel.
• To optimize the material removal rate (MRR) and surface roughness (Ra) by utilizing a nanofluid electrolyte.
• To identify the optimal process parameters for enhanced ECM performance.

Main Methods:

• Investigated the use of copper nanoparticles suspended in a sodium nitrate aqueous electrolyte (nanofluid) for ECM.
• Employed Design Expert 7.0 software to design 36 experiments based on applied voltage, electrolyte discharge rate, and tool feed rate.
• Utilized a multiobjective genetic algorithm (MOGA) for process optimization and prediction of optimal parameters.

Main Results:

• Identified optimal parameters for ECM of HCHCr die tool steel as 18 V applied voltage, 0.54 mm/min tool feed rate, and 12 lit/min nanofluid discharge rate.
• Predicted maximum MRR of 375.78 mm³/min and surface roughness Ra of 2.34 μm at specific optimal conditions.
• Confirmatory tests validated the model predictions with less than 4% deviation, confirming the effectiveness of the developed models.

Conclusions:

• The use of copper nanoparticle-based nanofluid significantly minimizes spike formation in ECM of HCHCr die tool steel.
• The optimized process parameters and developed models provide a reliable method for achieving superior MRR and surface finish.
• This research offers a pathway to enhance the efficiency and quality of electrochemical machining for critical tooling applications.