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Abstract

In the present work, the performance of multilayer coated carbide tool was investigated considering the effect of cutting parameters during turning of 34CrMo4 Low alloy steel. It has high strength and creep strength, and good impact tenacity at low temperature. It can work at –110°C to 500°C. And EN 10083-1 34CrMo4 owns high static strength, impact tenacity, fatigue resistance, and hardenability; without overheating tendencies. The objective functions were selected in relation to the parameters of the cutting process: surface roughness criteria. The correlations between the cutting parameters and performance measures, like surface roughness, were established by multiple linear regression models. Highly significant parameters were determined by performing an Analysis of variance (ANOVA). During the experiments flank wear, cutting force and surface roughness value were measured throughout the tool life. The results have been compared with dry and wet-cooled turning. Analysis of variance factors of design and their interactions were studied for their significance. Finally, a model using multiple regression analysis between cutting speed, fee rate and depth of cut with the tool life was established.
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Abstract

Any industrial process needs to work with the optimal operating conditions and thus the evaluation of their robustness is a critical issue. A modeling of a laboratoryscale wire-to-plane two stages electrostatic precipitator for guiding the identification of the set point, is presented this in paper. The procedure consists of formulating recommendations regarding the choice of optimal values for electrostatic precipitation. A twostages laboratory precipitator was used to carry out the experiments, with samples of wood particles of average granulometric size 10 μm. The parameters considered in the present study are the negative applied high voltage of the ionization stage, the positive voltage of the collection stage and the air speed. First, three “one-factor-at-a-time” experiments were performed followed by a factorial composite design experiments, based on a two-step strategy: 1) identify the domain of variation of the variables; 2) set point identification and optimization of the process.
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Abstract

The paper described properties of electro-spark deposited coatings under influence of the laser treatment process. The properties were assessed by analyzing the coating microstructure, X-ray radiation, microhardness, bonding strength, corrosion resistance, porosity and wear tests. The tests were conducted for Mo and Cu coatings (the anode) which were electro-spark deposited over the C45 steel substrate (the cathode) and melted with a laser beam. The coatings were deposited by means of an ELFA-541. The laser processing was performed with an Nd:YAG laser. The coatings after laser processing are still distinguished by very good performance properties, which make them suitable for use in sliding friction pairs.
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Abstract

Chemical bonded resin sand mould system has high dimensional accuracy, surface finish and sand mould properties compared to green sand mould system. The mould cavity prepared under chemical bonded sand mould system must produce sufficient permeability and hardness to withstand sand drop while pouring molten metal through ladle. The demand for improved values of permeability and mould hardness depends on systematic study and analysis of influencing variables namely grain fineness number, setting time, percent of resin and hardener. Try-error experiment methods and analysis were considered impractical in actual foundry practice due to the associated cost. Experimental matrices of central composite design allow conducting minimum experiments that provide complete insight of the process. Statistical significance of influencing variables and their interaction were determined to control the process. Analysis of variance (ANOVA) test was conducted to validate the model statistically. Mathematical equation was derived separately for mould hardness and permeability, which are expressed as a non-linear function of input variables based on the collected experimental input-output data. The developed model prediction accuracy for practical usefulness was tested with 10 random experimental conditions. The decision variables for higher mould hardness and permeability were determined using desirability function approach. The prediction results were found to be consistent with experimental values.
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