Electrochemical machining is a modern machining technique that plays an important role in the applications of aerospace, die and electronic industries. Electrochemical machining is used to machine difficult-to-machine materials and complex shapes. Machining of alloy steels especially 20MnCr5 is very important for its wide variety of applications such as piston bolts, spindles, camshafts, gears, shafts and other mechanical controlling parts. Machining of the above components with conventional machine tools is a burdensome task. Hence, in this work, an investigation was made to study the electrochemical machining characteristics of 20MnCr5 alloy steel. Two electrolytes, namely, aqueous sodium chloride (NaCl) and potassium dichromate (K₂Cr₂O₇) mixed aqueous NaCl, were used to investigate the machining performance. K₂Cr₂O₇ was selected for its oxidizing characteristics and was included in small proportions in aqueous NaCl bath. The influence of predominant electrochemical machining process parameters such as applied voltage (V), inter electrode gap and electrolyte concentration was studied on the material removal rate and surface roughness (R_a). Scanning electron microscope photography of surface of the 20MnCr5 specimen machined with electrochemical machining was studied to understand the effect of electrolytes during the machining. The contour plots were generated to study the effect of process parameters as well as their interactions. It was noted in the study that the presence of K₂Cr₂O₇ in aqueous NaCl electrolyte increases the material removal rate significantly. The process parameters are optimized through genetic algorithm-desirability function. Optimized operating conditions were found to be quite close with experimental results.

Electrochemical machining (ECM) is a preferred advanced machining process for machining Monel 400 alloys. During the machining, the toxic nickel hydroxides in the sludge are formed. Therefore, it becomes necessary to determine the optimum ECM process parameters that minimize the nickel presence (NP) emission in the sludge while maximizing the material removal rate (MRR). In this investigation, the predominant ECM process parameters, such as the applied voltage, flow rate, and electrolyte concentration, were controlled to study their effect on the performance measures (i.e., MRR and NP). A meta-heuristic algorithm, the grey wolf optimizer (GWO), was used for the multi-objective optimization of the process parameters for ECM, and its results were compared with the moth-flame optimization (MFO) and particle swarm optimization (PSO) algorithms. It was observed from the surface, main, and interaction plots of this experimentation that all the process variables influenced the objectives significantly. The TOPSIS algorithm was employed to convert multiple objectives into a single objective used in meta-heuristic algorithms. In the convergence plot for the MRR model, the PSO algorithm converged very quickly in 10 iterations, while GWO and MFO took 14 and 64 iterations, respectively. In the case of the NP model, the PSO tool took only 6 iterations to converge, whereas MFO and GWO took 48 and 88 iterations, respectively. However, both MFO and GWO obtained the same solutions of EC = 132.014 g/L, V = 2406 V, and FR = 2.8455 L/min with the best conflicting performances (i.e., MRR = 0.242 g/min and NP = 57.7202 PPM). Hence, it is confirmed that these metaheuristic algorithms of MFO and GWO are more suitable for finding the optimum process parameters for machining Monel 400 alloys with ECM. This work explores a greater scope for the ECM process with better machining performance.

It is essential to determine the most suitable machining method for magnesite-reinforced Aluminium 6061 composites, which possess excellent mechanical properties, especially notable tensile strength and hardness. The composites were produced using a stir-casting technique, incorporating reinforcements of lightly-calcined magnesite, dead burnt magnesite, and waste magnesite in weight fractions of 2.5%, 5%, and 7.5% within an aluminium 6061 matrix. Wire electrical discharge machining was employed to investigate the machining characteristics of these composites, using controllable process parameters such as cutting speed, pulse-on and pulse-off times, and the weight fraction of magnesites. Two performance indicators such as surface roughness and material removal rate were tested for various parameter combinations by central composite design. To comprehend the impact of the study parameters, contour charts were drawn. MRR increases at a high cutting speed of 2 mm/min when the pulse-on time changes from 120 μs to 125 μs. SR increases when the pulse-on times above 120 μs at all cutting speeds. High cutting speeds make high MRR irrespective of the weight fractions of reinforcement. High pulse-on times make the material melt more, which increases the material removal rate. Because specimen surface material erodes quickly and forms microcracks, high pulse-on time also results in high surface roughness. To optimize the WEDM machining conditions for each composite, hybrid SSO-DF and DFO-DF optimizers were developed by combining the desirability function with Salp-swarm optimization and Dragonfly optimization algorithms. The cutting speed of 2 mm/min and the pulse-on time of 114 μs produce the best performances on the composites.

During the sintering process in the shaft kiln of refractory factories, a considerable quantity of materials is separated and dumped as Waste Magnesite (WM). The other superior grades, Lightly-Calcined Magnesite (LCM) and Dead-Burned Magnesite (DBM), are separated at different temperatures from the shaft kiln. The WM materials still have 8% of magnesium with some sand and dust particles in huge ranges. These materials are primarily used in the applications of medicine and fertilizers and animal feed processing and additives. This work investigates the potential of WM particles as reinforcement materials in the Al 6061 alloy matrix. In order to compare the characteristics of WM-based composite, LCM and DBM powders were also considered as reinforcement particles. The WM, LCM, and DBM particles were mixed with a 15% weight ratio to Al 6061 alloy, and composites were fabricated using the Stir Casting method. The surface morphology investigations through Scanning Electron Microscopy (SEM) revealed that these particles were well distributed and dispersed within the alloy matrix and with good interfacial adhesion. It is noted that Al 6061/15% wt. LCM composite possesses a better tensile strength than Al 6061/15% wt. WM and Al 6061/15% wt.DBM composites. The impact value produced by the WM-based composite is better than the LCM and DBM composites. The Wear Rate and Coefficient of Friction (COF) were examined through a Pin-on-Disc apparatus. Al 6061/15% wt. WM composite tested a low wear rate (9.74 × 10⁻⁶ mm³ m)⁻¹. The results show that Al 6061/15% wt. LCM composite achieved the least COF value of 0.681 at an applied load of 0.5 Kg and a sliding distance of 2826 m. The results prove that the wastage magnesite is good enough and the most robust reinforcement material for Aluminum 6061 alloy-based composite.