In this study, the main cutting parameters of high speed machining (HSM) including cutting speed, feed rate, depth of cut as well as deposition method were optimized using genetic algorithm considering the average surface roughness (Ra) of work piece and flank wear (Vb) of CVD and PVD coated tool criteria in high speed turning of hardened AISI 4140 Steel. Standard L18 orthogonal array has been used for the design of experiment (DOE) applying Taguchi approach. Multiple linear regression model applying Minitab, was used to determine the relationship and interaction between machining parameters and outputs. For genetic algorithm(GA) optimization, the average was applied as a functional output of design of experiments. The results of GA for smaller- the better quality characterization shows the optimum roughness of 1.107 mm and optimum flank wear of 0.461mm. The confirmation tests were carried out in order to validate the response of predicted optimum condition. The results of validation test show a good agreement between obtained optimum condition and the results of genetic algorithm. The analysis of variance was used in order to obtain the contribution of each factor on the output statistically. ANOVA results indicated that the cutting speed and cut depth are the most effective factors on the flank wear by 37.02 and 27.80 percent contribution respectively. The most effective factors on surface roughness were feed rate and cutting speed by 82.49 and 10.50 percent contribution respectively. Stereoscopy and Scanning electron microscopy was used to evaluate the wear mechanism and topography of worn surface. پرونده مقاله

In this paper the fracture toughness of WC-12Co coatings in optimum particle temperature in high velocity oxy fuel (HVOF) process have been studied by means of Vickers indentation. Multiple linear regression model applying Minitab, were used to determine the relationship and interaction between HVOF parameters and particle temperature. For genetic algorithm optimization, the signal to noise ratio was applied as a functional output of design of experiments. The results of validation test show a good agreement between obtained optimum condition and the results of genetic algorithm. The fracture toughness obtained by Vickers indentation shows the direct effect of particle temperature on coating toughness. The maximum amount of signal-to-noise using the genetic algorithm for velocity and temperature is 53.07 and -64.62, which equals 450.2 m/s and 1702ºC respectively. The results show that the Fracture toughness of WC-12Co deposited by LPG fuel in smallest level of temperature is 2.83MPa(m)1/2 compared to 1.32MPa(m)1/2 in highest temperature. The spray watch diagnostic system, micro-hardness test, Vickers indentation, X-Ray diffraction, EDS and scanning electron microscopy have been used for this purpose. پرونده مقاله

Thermally sprayed coatings are intrinsically associated with residual stresses in the deposits. These stresses are varied in nature and magnitude, and have a pronounced effect on the mechanical behavior of the system. In the current study, WC-12Co coatings were deposited using HVOF thermal spraying. The sin2ψ method was used to evaluate the through thickness residual stress by means of XRD after mechanical layer removal process. A nonlinear explicit-implicit finite element model was developed to study the peening and thermal stress during the high velocity impact of WC-12Co particle and cooling the splat and coating layers. The average of through thickness residual stress using X-Ray diffraction and numerical model was -157.1 MPa and -133.4 MPa respectively. The results showed that the residual stress was compressive and had a good agreement with the experimental results in literature. پرونده مقاله