Metal-based microelectromechanical systems are widely used in applications such as micro-energy harvesters, micro-heat exchangers and micro-electromagnetic that require high strength and flexibility. In the fabrication of such systems, micro wire electrical discharge machining (MicroWEDM) is majorly used. This paper studies the effect of the MicroWEDM process parameters on the dimensional deviation of machined MEMS structures including microcantilevers and micro-beams using the Taguchi method. Using optimal levels of the parameters including pulse duration (0. 8 μ s), cutting speed (8. 4 mm/min), voltage (17 V) and wire tension (0. 5 kg), the dimensional deviation is reduced about 8. 65 times compared with the average of experiments results. The order of effect importance of the process parameters on the dimensional deviation of microstructures obtained by the ANOVA analysis of S/N ratios is as follows: pulse duration, wire tension, process voltage and cutting speed. Dimensional deviation of the micro-features was reduced to 1 μ m using the optimal levels of the process parameters.

Manufacturing of blades in air turbine motors according to complicated shape and critical working conditions needs a high technology. The root of blade under applied forces should have high surface quality and dimensional accuracy in comparison with the other blade components. In this study, the surface quality due to different types of available wire-cut machines for machining of compressor blade root has been investigated. To this end some samples has been machined by different wire-cut machines. Afterwards the different components of surface integrity (such as surface roughness, surface topography, hardness, thickness of affected surface layers, microcrackes and pits, residual stresses) has been studied. Finally, the machining of the root of compressor blade with this process has been discussed and concluded.

Surface roughness is one of the most important parameters that plays very critical role in determining the quality of engineering components. A good surface quality resulting in improve of fatigue strength, corrosion and wear resistance of the workpiece. On the other hand, increasing cutting speed and decreasing time of machining are desirable for manufacturers in order to reduce costs and increase rate of production. According to importance of above subjects, having high surface with low cost is required to have proper understanding of cutting parameters of WEDM. In this study, the effect of parameters such as Power, Time-off pulse, Open circuit voltage and Servo voltage on Tungsten carbide is investigated.

Abstract: Wire Electrical Discharge Machining (WEDM) is a non-traditional thermal machining process used to manufacture irregularly profiled parts. Machining of ductile cast iron (ASTM A536) under several machining factors, which affect the WEDM process, is presented. The considered machining factors are pulse on time (Ton), pulse off (Toff), peak current (Ip), voltage (V), and wire speed (S). To optimize the machining factors, their setting is performed via an experimental design using the Taguchi method. The optimization objective is to achieve maximum Material Removal Rate (MRR) and minimum Surface Roughness (SR). Additionally, the analysis of variance (ANOVA) is used to identify the most significant factor. Also, a regression analysis is carried out to forecast the MRR and SR dependent on defined machining factors. Depending on consequences, the best regulation factors for reaching the maximum MRR are Ton = 32 μs, Toff = 8 μs, Ip = 4 A, S = 40 mm/min. and V = 70 volt. Whereas, the optimal control factors that achieve the minimum SR is Ton = 8 μs, Toff = 8 μs, Ip = 2 A, S = 20 mm/min, and V= 30 volt. It is hypothesized that the perfect combination of control factors that achieves minimum SR and maximum MRR is Ton = 8 μs, Toff = 8 μs, Ip=5 A, S=50 mm/min. The microstructure of the machined surface in the optimal machining conditions shows a very narrow recast layer at the top of the machined surface.

Wire electric discharge machining is one of the newest, most popular and most accurate non-traditional machining processes, which is being studied. The advantages of this process include precision machining of parts with different hardness or complex shapes. Due to the increasing applications of this type of machining and since increasing the cutting speed and reducing the dimensional deviation in this process are very important, the selection of optimal cutting parameters has an important role to achieve high cutting speed and low dimensional deviation. Improper selection of parameters leads to limitations in output parameters and ultimately reduces productivity; Therefore, in this study, using Sobol statistical sensitivity analysis method, which has the advantage of high accuracy over other methods and extracting a small amount of parameter effect, to investigate the effect of various input parameters, including pulse-on time, pulse-off time, servo gap voltage, peak current and wire tension on the two output parameters of cutting speed and dimensional deviation are discussed. The results obtained from the sensitivity analysis of the expression are that the parameters of the pulse off time and pulse on time are the most effective parameters on the cutting speed with 39% and 37%, respectively, and the servo gap voltage parameters and the pulse on time are the most effective parameters on the dimensional deviation with 59% and 31%, respectively.

Wire erosion discharge machining (WEDM) is a modification of electro discharge machining (EDM) and has been widely used for a long time for cutting punches and dies, shaped pockets and other machine parts on conductive work materials. The surface finish of the machined surface mainly depends on the pulse duration, open voltage, wire speed and dielectric flushing pressure. In the present work, two of the techniques, namely factorial design and neural network (NN) were used for modeling and predicting the surface roughness of AISI 4340 steel. Surface roughness was taken as a response variable measured after WEDM and pulse duration, open voltage, wire speed and dielectric flushing pressure were taken as input parameters. Relationships between surface roughness and WEDM cutting parameters have been investigated. The level of importance of the WEDM cutting parameters on the surface roughness was determined by using the analysis of variance method (ANOVA). The mathematical relation between the work piece surface roughness and WEDM cutting parameters were established by regression analysis method. This mathematical model may be used in estimating the surface roughness without performing any experiments. Finally, predicted values of surface roughness by techniques, NN and regression analysis, were compared with the experimental values and their closeness with the experimental values determined. Results show that, NN is a good alternative to empirical modeling based on full factorial design.