High-Pressure Die Casting (HPDC) is one of the major production processes of the automotive industry, widely used to manufacture geometrically complex nonferrous castings. The mechanical strength and microstructure of HPDC-manufactured products change with variation in several process parameters such as injection pressure, molten temperature, 1st and 2nd stage plunger velocities, cooling temperature, etc. Since these process parameters directly a, ect casting quality, their optimum combination is needed to maximize productivity of the process and minimize casting defects such as porosity, pinholes, blowholes, etc. Hence, to tackle this problem, an approach is presented in this paper that minimizes the major casting defect, i. e., porosity, in the HPDC process by optimizing parameters through Design Of Experiments (DOE) in combination with Taguchi analysis. The obtained results showed that cooling time, injection pressure, and 2nd stage plunger velocity had a major in uence on the response factor (density of the cast part). It was further concluded that by using a 178-bar injection pressure, 665, C molten temperature, 5 seconds of cooling time, 210 C mold temperature, 0. 20 m. s-1 1st stage plunger velocity, and 6. 0 m. s-1 2nd stage plunger velocity, the rejection rate of the selected part due to porosity was reduced by 61%.

The electrochemical method of recovering tungstic acid uses nitric acid as the electrolyte. At the anode, carbide material is oxidized, yielding insoluble tungstic acid (H2WO4) and cobalt ions in the solution. Tungstic acid is then used to make tungsten oxide (WO3), a valuable industrial material. Initially, experiments in this study were prepared and carried out using experimental design approaches and grey relational analysis (GRA), which was based on the Taguchi method and carried out using Minitab17 software. Datafit (Versions 9.1) software was used to create regression models for predicting weight loss and energy usage. The goal function of the tests was anode weight loss/hour and electrochemical cell power consumption, whereas the impacting variables were current density, electrolyte concentration, cell temperature, and cathode electrode type. The optimal electrochemical cell has a current density of 4000 A/m2, 1.8 M electrolyte concentration and 70 °C cell temperature, and an aluminum cathode.

In this paper, the optimization of electromechanical devices by continuous sensitivity analysis and its comparison with Taguchi method is investigated. The present research can be useful for researchers in one of the important and practical issues that is the optimization of different systems. In practice, it will be observed that the continuous sensitivity analysis method, in addition to achieving significant results, also increases the convergence rate significantly compared with the Taguchi method. In addition to the above, this dissertation also tries to improve the method of continuous sensitivity analysis, which has been done using the help of interpolation such as Spline and Bizar. One of the advantages of the continuous sensitivity analysis method using Spline interpolation in comparison with the Taguchi method is the absence of sharp angles at the optimized border and ease of construction. This specification is of great importance in electromagnetic devices. The main purpose of this article is to compile a complete and understandable reference for use in today's industry and further studies.

in this research, the dry sliding wear behaviour of the Mg-TiO2 nanocomposite is analyzed by conducting a wear test using a pin-on-disc wear testing machine under normal atmospheric conditions. The process parameters considered during the test are the weight fraction of TiO2 nanoparticles, normal load, and sliding speed. The sliding distance and wear track diameter are maintained constant at 1500 m and 90 mm respectively during the test. The performance measures are cumulative wear and coefficient of friction. Taguchi-based Grey relational analysis is employed in this study to optimize the performance of the wear behaviour of the nanocomposite. The design of experiments considered in this study is L9 orthogonal array with each process parameter for three levels. Grey relational grade (GRG) is computed for each experiment and it was found that the maximum GRG of 0. 825 is obtained for the process parameter combination A3B2C1 which corresponds to 5wt% TiO2, 1 kg normal load and 1. 5 m/s sliding speed respectively. The initial GRG estimated is compared with the predicted and experimental values for the optimum process parameters and it was found that there is an improvement in GRG by 2. 2% and 0. 77% respectively. ANOVA (analysis of variance) is carried out to estimate the process parameter that influences the wear behaviour of the nanocomposite significantly and later concluded that the process parameter normal load is the most significant factor other than any other factors.

Thermoplastic elastomer nanocomposites based on polypropylene (PP) and ethylene-propylene diene monomer (EPDM) and Cloisite 15A were prepared via direct melt mixing in a co-rotating twin-screw extruder. The formulation for preparation of nanocomposites was fixed with the ratio of 75/20/5 for PP/EPDM/ organoclay©15A, expressed in mass fraction. The objective of the present study was to investigate the effects of processing conditions on the formation of TPE (PP/EPDM/nanoclay) nanocomposites. The parameters under study included the feeding rate, screw speed and barrel temperature, which were varied independently, from 0.2 to 1.0 kg/h and from 50 to 150 rpm and 180 to 200°C, in the order given. Design of experiments was carried out by Expert Design software (Taguchi analysis Method) on the basis of three different levels of the above processing parameters. The state of dispersion was quantified by X-ray diffraction, transmission electron microscopy and rheological measurements. X-Ray diffraction results show that the nanocomposites obtained in different conditions have an intercalated structure and the proportion of exfoliation, estimated by rheological measurements, depend on the operating conditions. The exfoliated layers increase when the feed rate and barrel temperature decrease and the screw speed increases. The study of linear viscoelastic properties also shows that the storage modulus, G’, is very sensitive to the microstructure of the nanocomposite. A Carreau-Yasuda model with a yield stress is proposed to describe the rheological behaviour of these materials. The yield stress of nanocomposites increases when the barrel temperature and feed rate are reduced and the screw speed is increased.