To achieve enhanced surface characteristics in wire electrical discharge machining (WEDM), the present work reports the use of an artificial neural network (ANN) combined with a genetic algorithm (GA) for the correlation and optimization of WEDM process parameters. The parameters considered are the discharge current, voltage, pulse-on time, and pulse-off time, while the response is fractal dimension. The usefulness of fractal dimension to characterize a machined surface lies in the fact that it is independent of the resolution of the instrument or length scales. Experiments were carried out based on a rotatable central composite design. A feed-forward ANN architecture trained using the Levenberg-Marquardt (L-M) back-propagation algorithm has been used to model the complex relationship between WEDM process parameters and fractal dimension. After several trials, 4-3-3-1 neural network architecture has been found to predict the fractal dimension with reasonable accuracy, having an overall R-value of 0.97. Furthermore, the genetic algorithm (GA) has been used to predict the optimal combination of machining parameters to achieve a higher fractal dimension. The predicted optimal condition is seen to be in close agreement with experimental results. Scanning electron micrography of the machined surface reveals that the combined ANN-GA method can significantly improve the surface texture produced from WEDM by reducing the formation of re-solidified globules.

Ni–B alloys deposited by the electroless method are considered to be hard variants of the electroless nickel family. Inclusion of Mo or W to form ternary alloys improves the thermal stability of electroless nickel coatings. Therefore, in the present work, Ni–B, Ni–B–Mo, and Ni–B–W coatings are deposited; and their tribological behavior at room and high temperatures are investigated. Electroless Ni–B, Ni–B–Mo, and Ni–B–W coatings are deposited on AISI 1040 steel substrates. The coatings are heat treated to improve their mechanical properties and crystallinity. Tribological behavior of the coatings is determined on a pin-on-disc type tribological test setup using various applied normal loads (10–50 N) and sliding speeds (0.25–0.42 m/s) to measure wear and coefficient of friction at different operating temperatures (25 °C–500 °C). Ni–B–W coatings are observed to have higher wear resistance than Ni–B or Ni–B–Mo coatings throughout the temperature range considered. Although for coefficient of friction, no such trend is observed. The worn surface of the coatings at 500 °C is characterized by lubricious oxide glazes, which lead to enhanced tribological behavior compared with that at 100 °C. A study of the coating characteristics such as composition, phase transformations, surface morphology, and microhardness is also carried out prior to tribological tests.

The objective of the present study is to find out the optimum combination of process parameters in EDM process so that surface roughness reaches a minimum value and the metal removal rate (MRR) reaches a maximum value. In this study, five roughness parameters (viz. center line average roughness, root mean square roughness, mean line peak spacing, skewness and kurtosis) along with MRR have been considered. To optimize the multi-response problems, Taguchi method alone is unable to solve the problem. Thus, the multi-response characteristics must be converted to a single performance index. In this study weighted principal components analysis (WPCA) method is used for this conversion. For the experimentation, Taguchi L27 orthogonal design with four process parameters, viz., pulse on time, pulse off time, discharge current and voltage at three different levels is used. The optimum combination of process parameters has been found out and verified through the confirmation test. The result of the confirmation test shows a good agreement with the predicted value. This indicates the utility of the WPCA technique as multi-objective optimizer in the field of EDM. In addition, the surface morphology is studied with the help of scanning electron microscopy (SEM) analysis.

The tribological properties of acrylonitrile-butadiene-styrene (ABS) polymer filled with micron-sized calcium carbonate (CaCO3) are studied in this paper. Filler content, normal load and sliding speed are considered as design parameters and coefficient of friction (COF) and specific wear rate are considered as the responses. The experiments are conducted on multi-tribotester (block-on-roller configuration) based on L27 orthogonal array (OA). The optimum design parameter combination for minimum coefficient of friction and specific wear rate are found using grey relational analysis. The optimum parameter combination is found to be 5% of filler content, 35N of load and 120rpm of speed. Analysis of variance (ANOVA) is also used to find out the most influential factor which affects the tribological properties. The most influential factor is normal load followed by sliding speed and filler content. Further, a confirmation test is carried out to validate the result and it is seen that the grey relational grade is increased about 72.56% from the initial to the optimum condition. Finally, surface morphology is studied using scanning electron microscopy (SEM)

The Ni–B binary alloy deposited by autocatalytic chemical deposition technique has tremendous potential of wear/friction reduction and wide industrial usage. A significant improvement in mechanical properties, higher hardness, and wear resistance can be achieved in electroless nickel coatings by deposition of poly-alloy coatings rather than the binary variant. The present work therefore investigates the outcome of co-deposition of both tungsten and molybdenum in binary Ni–B coatings on the morphology, structure, and tribological behavior. Ni–B–W–Mo poly-alloy coatings were deposited by chemical reduction on AISI 1040 steel. Ni–B–W and Ni–B–Mo ternary coatings were also deposited along with Ni–B for effective comparison. Tribo-tests in the as-deposited and heat-treated condition (400°C for 1 h) revealed that the anti-wear properties of Ni–B–W and anti-friction properties of Ni–B–Mo could be realized in Ni–B–W–Mo coatings. Also, Ni–B–W–Mo coatings were observed to have high W content and a compact defect-free surface morphology with dense nodules. Backscattered electron images of the worn surface of the Ni–B–W–Mo coating in the as-deposited and heat-treated condition revealed low deformation of the coating with mild abrasion and an excellent overall tribo-performance.

The influence of machining parameters, viz., spindle speed, depth of cut and feed rate on fractal dimension of surface profile produced in CNC end milling is investigated. Experiments are conducted for three different workpiece materials to see the effect of material variation in this respect. The second order mathematical models, in terms of the machining parameters, have been developed for fractal dimension prediction using Response Surface Methodology (RSM). It is found that the response surface model for fractal dimension is specific to workpiece materials. Optimum cutting conditions with respect to fractal dimension are also obtained using the response optimisation technique.