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This study aims to obtain the lowest surface roughness (Ra) and drill bit adhesion values (AV) depending on the change in control factors (cutting speed-Vc, feed rate-f and drill bit-D) during drilling of the Al 5083 H116 alloy. Low roughness values increase the fatigue strength of the final part and affect tribological properties such as lubrication and friction. In the machining of ductile materials, the AV increases the Ra value and negatively affects the tool life.

Drilling tests were conducted using Taguchi L16 orthogonal array. The experimental measurement findings for Ra and AV were adjusted utilizing the Grey Relational Analysis (GRA), the Response Surface Method (RSM) and Artificial Neural Networks (ANN) to generate prediction values. SEM detected drill-tip adhesions and chip morphology and they were analyzed by EDX.

Ra and AV increased as the f increased. Vc affects AV; 86.04% f on Ra and 54.71% Vc on AV were the most effective control parameters. After optimizing Ra and AV using GRA, the f is the most effective control factor. Vc: 120 m/min, f: 0.025 mm/rev and D2 were optimal. ANN predicted with Ra 99.6% and AV 99.8% accurately. Mathematical models are obtained with RSM. The increase in f increased AV, which had a negative effect on Ra, whereas the increase in Vc decreased the adhesion tendency. With the D1 drill bit with the highest flute length, a relatively lower Ra was measured, as it facilitates chip evacuation. In addition, the high correlations of the mathematical models obtained indicate that the models can be used safely.

The novelty of this study is to determine the optimum drilling parameters with GRA and ANN for drilling the necessary holes for the assembly of ammunition wing propulsion systems, especially those produced with Al 5083 H116 alloy, with rivets and bolts.

Aerospace industry was pioneered in the use of superplastic forming (SPF) process. Weight saving is the most important need in this industry. For this reason, there is special attention paid to this method. Blow forming is a common method for SPF process. Process parameters such as temperature and pressure have significant effects on part accuracy, quality and desired characteristics. The purpose of this paper is to present a numerical and experimental investigation of process parameters in superplastic free bulge forming.

In this paper, superplastic free bulge forming of Al‐5083 has been studied. First, free bulge tests have been done at two different pressures. Bulge height variations were recorded for different pressure and temperature. The forming time was determined according to the forming pressure and temperature. Then, simulation of free bulge process has been carried out using creep behavior model at high temperature. Bulge height and thickness distribution are obtained at two different pressure settings. These results have been compared with experimental results presenting a good agreement. Also the effects of temperatures and pressure on the required process time are compared for a certain bulge height. Finally, thickness distribution profile for different temperatures, pressures and initial thicknesses have been studied.

A numerical and experimental investigation has been presented that can be used to study the process parameters. These findings show the effects of temperatures, pressure and initial thicknesses on sheet forming.

The results of this work show that higher temperature and forming pressure will reduce the required process time for a certain bulge height. Reduction of these parameters can improve thickness distribution. Also, by considering the effects of both pressure and temperature, it is shown that using lower forming pressure at higher temperature is more suitable for forming. The findings of this work can provide more understanding of the process for aircraft part designers and manufacturing process planners.

Friction material in an automotive brake system plays an important role for effective and safe brake performance. A single material has never been sufficient to solve performance related issues. Current research aimed to examine properties of Boron mixed brake pads by comparing them with the commercial brake pads. Friction coefficient of Boron mixed brake pads and commercial brake pads were significantly different and increased with the increase in surface roughness. The abrupt reduction of friction coefficient is more significant in commercial brake pad samples than in Boron mixed brake pad formulations. Fade occurred in commercial brake pad sample at lower temperatures. Boron formulations are more stable than their commercial counterparts.

This paper aims to investigate the corrosion behaviour of heat-treated and cryorolled Al 5052 alloys in different Cl⁻ ion concentrations.

NaCl solutions with concentrations of 0, 0.5, 3.5 and 5.5 per cent were selected. Samples were subjected to pre-heat treatment (annealing at 300 °C and solution treatment at 540 °C) and cryorolling up to 30 per cent reduction before undergoing corrosion tests. The corrosion behaviour of the samples was then investigated by potentiodynamic polarization. The microstructure of the corroded samples was evaluated under an optical microscope, and the percentages of pits on their surfaces were calculated.

The cryorolled samples had a lower corrosion rate than the samples that were not cryorolled. The cryorolled sample that underwent solution treatment showed the highest corrosion resistance among all the samples tested.

The commercial impact of the study is the possibility of using the cryorolled Al alloy in various ion chloride environment.

The obtained results help in understanding the corrosion behaviour of cryorolled samples under different heat treatment conditions.

The main goal of the present study is to investigate the friction and wear behaviors of aluminum matrix composites with an A360 matrix reinforced with SiC, B₄C and SiC/B₄C particles.

Un‐reinforced aluminum casting alloy, Al/SiC, Al/B₄C and Al/SiC/B₄C aluminum composites were prepared for the present study. Friction and wear tests of aluminum and its composites versus AISI316L stainless steel were carried out for dry sliding condition using by a pin‐on‐disc arrangement. Tests were realized at the sliding speed of 0.5, 1.0 and 1.5 ms⁻¹ and under the loads of 10, 20 and 30 N. The microstructures of the present composites were examined by scanning electron microscopy and energy dispersive spectroscopy analysis.

The coefficient of friction of the composites is approximately 25‐30 percent lower than that of the un‐reinforced aluminum. The specific wear rate of the aluminum and its composites decreases with the increase in load and increases with the increment of sliding speed. Un‐reinforced aluminum has specific wear rate value of 1.73×10⁻¹³ which is the highest specific wear rate, while Al+17%SiC has specific wear rate value of 2.25×10⁻¹³ m² N⁻¹ which is the lowest specific wear rate among the tested materials. The average specific wear rates for Al+17%B₄C, Al+17%SiC/B₄C and Al+17%SiC composites are obtained about 49, 79 and 160 percent lower than aluminum wear rate under the same test conditions, respectively.

In the present study, composites were prepared by pressured infiltration technique. The employed composites are important in industry due to their higher wear resistance, light in weight and less thermal distortion comparing to conventional composites. Also, wear behavior of Al/B₄C, Al/SiC/B₄C and Al/SiC composites produced by pressured infiltration technique were not studied very much earlier, therefore more explanation about these composites were proposed.

Engineers and scientists are searching for novel materials with high performance on all aspect points of view for the applications including marine, aero and automobile fields. AA8090 aluminum alloy is one of the materials used in aero industries for aircraft construction because of its weight reduction ability. However, the AA8090 alloy has a drawback such as low wear resistance that affects the life time of material; hence, it should be addressed. The purpose of this investigation is to improve the wear resistance of AA8090 alloy.

In this investigation, AA8090 aluminum alloy metal matrix composite was fabricated using different types of carbide nanoparticles such as vanadium carbide (VC), Cr₃C₂ and Mo₂C by stir casting method and tribological and mechanical behaviors were studied.

Mechanical studies showed that the S1 sample displayed the maximum hardness of 142 HV and maximum tensile strength of 857 MPa because of the inclusion of hard VC particles. Tribological studies revealed that S1 sample showed high performance. A least wear rate of 0.003915 × 10^–3 mm³/m was noted for S1 sample, which is 71% lower than the wear rate of S0 sample. Further, a least mass loss and lower coefficient of friction of 0.00152 g and 0.2, respectively, were observed for S1 sample because of its high hardness and high wear resistance because of the stuffing of high-hardness VC particles. Hence, it is concluded from this study that S1 sample, i.e. AA8090/VC, could be a better candidate for aerospace applications as it showed good tribological and mechanical properties.

To the best of the authors’ knowledge, this work is original and novel in the field of metal matrix composite which deals with the effect of hybridization on the wear performance of the aluminum alloy composites.

The aim of this paper is to develop a suitable artificial neural network (ANN) model that fits best in predicting the experimental flow stress values to the closet proximity for mechanically alloyed Al6063/0.75Al2O3/0.75Y2O3 hybrid nanocomposite.

The ANN model is implemented on neural network toolbox of MATLAB^® using feed‐forward back propagation network and logsig functions. A set of 80 training data and 20 testing data were used in the ANN model. The layout of the network is arranged with three input parameters that include temperature, strain and strain rate, one hidden layer with 22 neurons and one output parameter consisting of flow stress. Flow stress was also predicted using Arrhenius constitutive model.

Based on the comparison of the predicted results using ANN model and Arrhenius constitutive model, it was observed that the ANN model has higher accuracy and could be used to estimate the flow stress values during hot deformation of Al6063/0.75Al2O3/0.75Y2O3 hybrid nanocomposite.

The ANN trained with feed forward back propagation algorithm developed, presents the excellent performance of flow stress prediction of Al6063/0.75Al2O3/0.75Y2O3 hybrid nanocomposite with minimum error rates.

This paper aims that optimization parameters depending on machining processes examine to define for the milling process of AL 6061-T6 aluminum alloy used in the aviation industry.

The Taguchi method was used to study the optimal parameters. Furthermore, the effects of machining parameters on surface roughness were also evaluated by performing variance analysis. Optimum parameter levels were determined by Signal/Noise analysis.

It was determined that the parameter levels that optimize the surface roughness were “4000 rev/min for the rotational speed of the cutting tool, 0.4 mm for the cutting depth and the optimum value for the feedrate 500 mm/min.”

It is limited by the precision of the manufacturing processes, the desired geometry and the exactness of the measurement make the machine productivity valuable in the production of parts.

By improving the optimal production parameters, reducing part production costs and waste amount in aviation has been seen as an important gain.

Improving production methods and optimization parameters in production technologies will ensure the minimization of loss and waste. These developed parameters with optimizing the surface roughness will add value in this context.

It was determined that the parameter levels that optimize the surface roughness of aluminum considering manufacturing processes. Especially as process parameters, optimum feed rate has been developed for effective rotation speed and cutting depth for cutting tools.

Aluminium metal matrix composites are used in automotive and aerospace industries because of their high performance and weight reduction benefits. The current investigation aims to focus on the development of the stir cast aluminium-boron carbide composites with enhanced mechanical and tribological properties.

The aluminium-boron carbide composites are produced by stir casting process. Aluminium alloy A356 is chosen as the matrix material and three sets of composites are produced with different weight fractions of boron carbide particles. Higher particle size (63 µm) of boron carbide is chosen as the reinforcement material. Aluminium-boron carbide composites are tested for mechanical and tribological properties. The effect of process parameters like load, speed and percentage of reinforcement on the wear rate are studied using the pin-on-disc method. The interaction of the process parameters with the wear rate is analysed by DesignExpert software using RSM methodology and desirability analysis. The coded levels for parameters for independent variables used in the experimental design are arranged according to the central composite design. The worn surface of the pin is examined using a scanning electron microscope. The phases and reaction products of the composites are identified by X-ray diffraction (XRD) analysis.

Aluminium-boron carbide composites reveal better mechanical properties compared to monolithic aluminium alloys. Mechanical properties improved with the addition of strontium-based master alloy Al10Sr. The ultimate tensile strength, hardness and compressive strength increase with an increase in the reinforcement content. The wettability of the boron carbide particles in the matrix improved with the addition of potassium flurotitanate to the melt. Uniform dispersion of particles into the alloy during melting is facilitated by the addition of magnesium. Wear resistance is optimal at 8 per cent of boron carbide with a load 20 N and sliding speed of 348 RPM. The wear rate is optimized by the numerical optimization method using desirability analysis. The amount of wear is less in Al-B₄C composites when compared to unreinforced aluminium alloy. The wear rate increases with an increase in load and decreases with the sliding speed. The wear resistance increases with an increase in the weight fraction of the boron carbide particles.

The produced Al-B₄C composites can retain properties at high temperature. It is used in nuclear and automotive products owing its high specific strength and stiffness. The main applications are neutron absorbers, armour plates, high-performance bicycles, brake pads, sand blasting nozzles and pump seals.

Al/B₄C composites have good potential in the development of wear-resistant products.

Robotic friction stir welding (RFSW) is an innovative process which enables solid-state welding of aluminum parts using robots. A major drawback of this process is that the robot joints undergo elastic deformation during the welding, because of the high forces induced by the process. This leads to tool deviation and incorrect orientation. There is currently no computer-aided manufacturing/computer-aided design (CAD) software for generating off-line paths which integrates robot deflections, and the main purpose of this study is to propose an off-line methodology to plan a path for RFSW with the integration of the deflections.

The approach is divided into two steps. The first step consists of extracting position and orientation data from CAD models of the workpieces and adding the deflections calculated with a deflection model to generate a suitable path for performing RFSW. The second step consists of the smooth fitting of the suitable path using Bézier curves.

The method is experimentally validated by welding a curved workpiece using a Kuka KR500-2MT robot. A suitable tool position and orientation were calculated to perform this welding, an experimental procedure was set up, a defect-free weld was performed and a high accuracy was achieved in terms of position and orientation.

This method can help manufacturers to easily perform RFSW for three-dimensional workpieces regardless of the lateral tool deviation, loss of the right orientation and control force stability.

The originality of this method lies in compensating for robot deflections without using expensive sensors, which is the most commonly used method for compensating for robot deflection. This off-line method can lead to a reduction in programming time in comparison with teach programming method and leads to reduced investment costs in comparison with commercial off-line programming packages.