Advanced Electrochemical Discharge Machining and Process Optimization for Hybrid Metal Matrix Composites

Abstract Composite and non-conductive materials are machined using an advanced technology known as electrochemical discharge machining (ECDM). This paper investigates the machinability of an aluminum 6061 alloy reinforced with boron carbide (B4C) and silicon carbide (SiC) HMMCs. It investigates how voltage, electrolyte concentration, and pulse-on and pulse-off periods affect the Material Removal Rate (MRR). An ANOVA (analysis of variance) revealed that the most significant factor was voltage (F-value = 36.61, P-value = 0.004), followed by pulse-on time (Pon), with electrolyte concentration and pulse-off time (Poff) having little impact. Regression analysis (adjusted R² = 74.18%) demonstrated model dependability. Increasing the voltage and pulse-on time enhances MRR, machining efficiency, and stability. This paper presents a statistically proven optimization strategy for aerospace and automotive applications.

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Publication Details

Journal
Management Systems in Production Engineering
Published
2026-02-16
DOI
https://doi.org/10.2478/mspe-2026-0012
Primary Topic
Advanced Machining and Optimization Techniques
Type
article
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article

Advanced Electrochemical Discharge Machining and Process Optimization for Hybrid Metal Matrix Composites

Safa Lafta, Abbas Fadhil Ibrahim
Management Systems in Production Engineering
Advanced Machining and Optimization Techniques
article

Advanced Electrochemical Discharge Machining and Process Optimization for Hybrid Metal Matrix Composites

Safa Lafta, Abbas Fadhil Ibrahim
article en

Abstract

Abstract Composite and non-conductive materials are machined using an advanced technology known as electrochemical discharge machining (ECDM). This paper investigates the machinability of an aluminum 6061 alloy reinforced with boron carbide (B4C) and silicon carbide (SiC) HMMCs. It investigates how voltage, electrolyte concentration, and pulse-on and pulse-off periods affect the Material Removal Rate (MRR). An ANOVA (analysis of variance) revealed that the most significant factor was voltage (F-value = 36.61, P-value = 0.004), followed by pulse-on time (Pon), with electrolyte concentration and pulse-off time (Poff) having little impact. Regression analysis (adjusted R² = 74.18%) demonstrated model dependability. Increasing the voltage and pulse-on time enhances MRR, machining efficiency, and stability. This paper presents a statistically proven optimization strategy for aerospace and automotive applications.

Management Systems in Production EngineeringVol. 34(1)
University of Baghdad (IQ), University of Technology - Iraq (IQ)
Openalex Percentile: Top 54%
Advanced Machining and Optimization Techniques
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