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Abstract The paper presents a complete description of the design and manufacturing of a Carbon Fiber/epoxy mold with an embedded Carbon Fiber resistor heater, and the mold performances in terms of its surface temperature distribution and thermal deformations resulting from the heating. The mold was designed for manufacturing aileron skins from Vacuum Bag Only prepreg cured at 135°C. The glass transition temperature of the used resin-hardener system was about 175°C. To ensure homogenous temperature of the mold working surface in the course of curing, the Carbon Fiber heater was embedded in a layer of a highly heat-conductive cristobalite/epoxy composite, forming the core of the mold shell. Because the cristobalite/epoxy composite displayed much higher thermal expansion than CF/epoxy did, thermal stresses could arise due to this discrepancy in the course of heating.

Abstract In this article, Al-Mg-Si-Mn alloy (AA6082) is butt joined by employing friction stir welding (FSW). The mechanical and metallurgical properties of joints are analyzed by conducting tensile and microhardness testing, respectively. To measure the temperature at different locations, eight thermocouples (L-shaped k-type) are placed at equal distance from the centerline. Least square method attempts to calculate the temperature at the centerline of joints. The process parameters are also optimized using Taguchi’s five-level experimental design. The optimum process parameters are determined, employing ultimate tensile strength (UTS) as a response parameter. A statistical test “analysis of variance” is used to check the adequacy of the model. It has been observed that rotational speed and feed rate are the predominant factors for UTS and microhardness.

Abstract Fatigue performance can be a critical attribute for the production of structural parts or components via additive manufacturing (AM). In comparison to the static tensile behavior of AM components, there is a lack of knowledge regarding the fatigue performance. The growing market demand for AM implies the need for more accurate fatigue investigations to account for dynamically loaded applications. A357.0 parts are processed by laser-based powder bed fusion (L-PBF) in order to evaluate the effect of surface finishing on fatigue behavior. The specimens are surface finished by shot peening using ϕ = 0.2 and ϕ = 0.4 mm steel particles and ϕ = 0.21-0.3 mm zirconia-based ceramic particles.

Abstract Prediction of the surface finish of hardened bearing steels was estimated in machining with ceramic uncoated cutting tools under various process parameters using two statistical approaches. A second-order (quadratic) regression model (MQR, multiple quantile regression) for the surface finish was developed and then compared with the artificial neural network (ANN) method based on the coefficient determination (R 2), root mean square error (RMSE), and percentage error (PE). The experimental results exhibited that cutting speed was the dominant parameter, but feed rate and depth of cut were insignificant in terms of the Pareto chart and analysis of variance (ANOVA). The optimum surface finish in machining bearing steel was achieved at 100 m/min speed, 0.1 mm/revolution (rev) feed rate, and 0.6 mm depth of cut.