Optimization of machining parameters for EDM operations based on central composite design and desirability approach

A novel aluminium metal matrix composite reinforced with SiC particles were prepared by liquid metallurgy route. Recent developments in composites are not only focused on the improvement of mechanical properties, but also on machinability for difficult-to-machine shapes. Electrical discharge machining (EDM) was employed to machine MMC with copper electrode. using EDM. Experiments were conducted using pulse current, gap voltage, pulse on time and pulse off time as typical process parameters. The experiment plan adopts face centered central composite design of response surface methodology. Analysis of variance was applied to investigate the influence of process parameters and their interactions viz., pulse current, gap voltage, pulse on time and pulse off time on material removal rate (MRR), electrode wear ratio (EWR) and surface roughness (SR). The objective was to identify the significant process parameters that affect the output characteristics. Further a mathematical model has been formulated by applying response surface method in order to estimate the machining characteristics such as MRR, EWR and SR.     

Application of Desirability-Based Multiobjective Optimization Techniques to Study the Wear of Al Self-Lubricating Hybrid Nanocomposites

In this study, novel Al6061–SiC nanocomposites and Al6061–SiC–Gr hybrid nanocomposites were fabricated by ultrasonic cavitation method by adding silicon carbide (SiC) of 0.8 and 1.6% and graphite (Gr) of 0.5 and 1.0% by weight basis for each casting. A Three-level Box–Behnken design of experiment was developed using response surface methodology. Dry sliding wear tests were performed as per the experimental design using a pin-on disc set-up at room temperature. Analysis of variance (ANOVA) was applied to investigate the influence of process parameters viz., load, sliding distance, wt% reinforcement and their interactions on specific wear rate and coefficient of friction. Further, a mathematical model was formulated by applying response surface method in order to estimate the tribology characteristics such as wear and COF of the hybrid nanocomposites. The specific wear rate and coefficient of friction were significantly influenced by % of SiC followed by % of Gr, load and sliding distance. The wear test parameters were optimized for minimizing specific wear rate and COF using desirability function approach. A set of optimum parameter of combination for AMMNC was identified as: SiC 1.36wt%; Gr 0.63 wt%; load 35.65 N and sliding distance 2848 m with specific wear rate of 0.517 g/N-m; coefficient of friction 0.181. The AFM image of Al6061–1.36SiC–0.63Gr hybrid nanocomposite at optimized condition confirmed the improvement in the wear surface smoothness of the hybrid nanocomposite compared to Al6061–SiC nanocomposites.     

Application of response surface method on machining of Al–SiC nano-composites

The newly fabricated metal matrix nano-composite (MMNC) of Al 7075 reinforced with 1.5 wt% SiC nano-particles was prepared by a novel ultrasonic cavitation method. The high resolution scanning electron micrograph (SEM) and field emission scanning electron micrograph (FESEM) shows uniform distribution and good dispersion of the SiC nanoparticles within the aluminum metal matrix. Electrical discharge machining (EDM) was employed to machine MMNC with copper electrode by adopting face centered central composite design of response surface methodology. Analysis of variance was applied to investigate the influence of process parameters and their interactions. Further a mathematical model has been formulated in order to estimate the machining characteristics. It has been observed that pulse current was found to be the most important factor affecting all the three output parameters such as material removal rate (MRR), electrode wear rate (EWR) and surface roughness (SR). The optimum parameter of combination setting has been identified for the MMNC are voltage 50.00 V, pulse current 8.00 A, Pulse on time 8.00 μs and pulse off time 9.00 μs. Finally the parameters were optimized for maximizing MRR, minimizing EWR and SR using desirability function approach.     

Mechanical Properties and Tribological Behavior of Al6061–SiC–Gr Self-Lubricating Hybrid Nanocomposites

In the present investigation, a newly fabricated Al6061 reinforced with various quantity (0.4–1.6 wt%) of nano SiC in steps of 0.4 and fixed quantity (0.5 wt%) of micro graphite particle’s hybrid nanocomposites were prepared by ultrasonic assisted stir casting method. The influence of nano SiC and graphite content on the mechanical and tribological properties of Al6061 hybrid nanocomposites were studied. The pin-on-disc equipment was used to carry out experiment at 10–40 N applied load, 0.5 m/s sliding speed and 1000 m sliding distance. The Al/SiC/Gr hybrid nano-composite and matrix alloy wear surfaces were characterized by FESEM equipped with an EDS, 3D profilometer to understand the wear mechanisms. The results of Al/SiC/Gr self-lubricating hybrid nano-composites showed improved wear resistance than the Al6061 matrix alloy. The co-efficient of friction of Al/SiC/Gr hybrid nano-composites were lower than those of the unreinforced alloy at various applied load. Compared to matrix alloy, the surface roughness of Al/SiC/Gr hybrid nano-composites had significantly reduced to 66% at low load and 75% at high load. Self-lubricating Al/SiC/Gr hybrid nanocomposites showed superior surface smoothness compared to matrix alloy.     

Teaching—Learning-Based Optimization Coupled with Response Surface Methodology for Micro Electrochemical Machining of ALUMINIUM NANOCOMPOSITE

Silicon - In this work, Micro Electro Chemical Machining (μECM) of aluminium alloy (AA) 7075 reinforced with nano silicon carbide particles (1.5 wt.%) has been effectively...     

EDM of cast Al/SiC metal matrix nanocomposites by applying response surface method

The newly engineered metal matrix nanocomposite (MMNC) of Al 7075 reinforced with 0.5 wt% SiC nanoparticles was prepared by ultrasonic cavitation method. The high resolution scanning electron micrograph shows uniform distribution and good dispersion of the SiC nanoparticles within the aluminum metal matrix. Electrical discharge machining was employed to machine MMNC with copper electrode by adopting face-centered central composite design of response surface methodology. Analysis of variance was applied to investigate the influence of process parameters and their interactions. Further, a mathematical model has been formulated in order to estimate the machining characteristics.     

Effects of the Nanoclay and Crosslinking Systems on the Mechanical Properties of Ethylene-propylene-diene Monomer/styrene Butadiene Rubber Blends Nanocomposite

Silicon - This paper investigates the effect of nanoclay and crosslinking systems on the cure characteristics, mechanical properties, abrasion resistance, compression set and swelling properties of...     

Mechanical Characterization Studies of Aluminium Alloy 7075 Based Nanocomposites

Silicon - In the present study, addition of nano silicon carbide particulates (nSiCp) in the matrix of aluminium alloy 7075 (AA7075) in different weight proportions (0 %, 0.5 %,...