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Abstract Equal-channel angular pressing (ECAP) is among the most applicable severe plastic deformation processes used to fabricate ultrafine-grained materials with superior mechanical properties. In this work, a commercial purity aluminum has been processed via ECAP process up to four passes. The influence of ECAP routes (A and Bc) on the mechanical properties of the material and its grain size was investigated. Microstructural observations of the as-annealed and the rods processed via ECAP were undertaken using optical microscopy. Hardness profiles and contour maps of sections cut perpendicularly and parallel to the load direction were assessed to investigate the effect of ECAP processing on the hardness distribution across the deformed rods. Compressive properties of the rods were also examined. In addition, digital images correlation was used to display the stress distribution along the longitudinal section of the processed sample during the compression test.

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Abstract In the present study, the mechanical performances of plain carbon steel were explored based on the grain growth behavior. In the first step, the samples were normalized at different temperatures ranging from 900°C to 1100°C for 30, 60, 100, 150, and 200 min, respectively. In order to measure the grain size, the planimetric technique of Jeffries was used based on the optical micrographs taken for each sample. The mechanical properties of each grain such as hardness, elongation, yield, and tensile strength were studied, depending on the conventional methods. Experimental results showed that the increase in both heating temperature and holding time enhances grain growth, while the growth rate decreases with increasing time. The initial grain size and proportionality constant were calculated at 950°C, where K = 2.26 μm2/min and D 0 = 25.09 μm. Moreover, a significant increase in strength and hardness was observed with a decrease in grain size.

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 Sound ductile iron (DI) welded joints were performed using developed coated electrode and optimized welding parameters including post weld heat treatment (PWHT).Weldments consisting of weld metal, partially melted zone (PMZ), heat affected zone (HAZ) and base metal were austenitized at 900 °C for 2 hour and austempered at 300 °C and 350 °C for three different holding time (1.5 hour, 2 hour and 2.5 hour). In as-weld condition, microstructures of weld metal and PMZ show ledeburitic carbide and alloyed pearlite, but differ with their amount. Whereas microstructure of HAZ shows pearlite with some ledeburitic carbide and base metal shows only ferrite.

Abstract In this work, the complex relationship between deformation history and residual stresses in a magnesium-to-aluminum self-pierce riveted (SPR) joint is elucidated using numerical and experimental approaches. Non-linear finite element (FE) simulations incorporating strain rate and temperature effects were performed to model the deformation in the SPR process. In order to accurately capture the deformation, a stress triaxiality-based damage material model was employed to capture the sheet piercing from the rivet. Strong visual comparison between the physical cross-section of the SPR joint and the simulation was achieved. To aid in understanding of the role of deformation in the riveting process and to validate the modeling approach, several experimental measurements were conducted. To quantify the plastic deformation from the piercing of the rivet, micro hardness mapping was performed on a cross-section of the SPR joint.

Abstract In this study, active-passive filling friction stir repairing (A-PFFSR) process was employed to repair the volume defects in friction stir welding (FSW) joints of Al-Cu alloy. The volume defects with varied geometries were first machined into taper holes, which are similar to keyhole defect by a rotational tool with a threaded pin. Then, the keyhole defect was effectively filled with the materials around the keyhole and an additional filler using a number of nonconsumable pinless tools with the shoulders having six spiral flutes. The macro/microstructures, microhardness, and tensile properties of the repaired joints were investigated. The influences of plunge speed on macro/microstructures and mechanical properties of the repaired joints have been analyzed too. It was noticed that decreasing plunge speed was effective to improve the frictional heat and material flow, which increased joint surface integrity avoiding interfacial drawbacks.

Abstract Compared with traditional plastics, glass fiber-reinforced plastic (GFRP) has more outstanding performance advantages, which is more and more widely used. To improve the quality of the products manufactured by the GFRP injection molding, the injection parameters are optimized in two stages. In the first stage, the range of optimization parameters including the glass fiber content and six molding parameters is selected by the Moldflow recommendation. The warpage and shrinkage of each orthogonal experiment are obtained by the Moldflow simulation. Then, a comprehensive evaluation method called GRA-TOPSIS and the range analysis method are utilized to identify the optimal level values of all optimization parameters. According to the order of influence of each parameter, the range of these parameters is adjusted for the second stage.

Abstract As the advancement of metal additive manufacturing (AM) technology persists, so will the expansion of its capabilities and applications. In particular, the automotive industry can benefit from the advantages provided by AM, such as flexibility in design and customized products. In this avenue, one potential application of AM is in internal combustion engines (ICEs). As a first step, this effort explores the feasibility of using AM to produce working ICE components for an air-cooled engine. The cylinder head and crankcase of an 11 cm3 displacement volume Saito FG-11 engine were the components identified for metal AM. They were manufactured through Laser Powder Bed Fusion (LBPF) and post machined to achieve the necessary tolerances. Engine testing encompassed both propeller and dynamometer setups with corresponding data collection to measure and compare engine performance.

Abstract Aluminum boron carbide (Al-B4C) composites have been a popular choice among scientists and designers for high-performance strength-to-weight ratio engineering applications. Requirements for such applications are met due to enhanced microstructure, mechanical properties, and ease of processing conditions. The performance and application of these composites are mostly dependent on certain parameters, like composition ratios of reinforcing particles, their sizes and wettability, the presence of additional phases, etc. Prominently, efforts are also being made to synthesize Al-B4C as functionally graded materials (FGMs) that have the potential to cater to the needs of advanced engineering applications and can facilitate new dimensions in the field of aluminum matrix composites (AMCs).

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.

Abstract Fiber-reinforced composites are widely used in injection molding processes because of their high strength and high elastic modulus. However, the addition of reinforcing agents such as glass fibers has a significant impact on their injection molding quality. The difference in shrinkage and hardness between the plastic and the reinforcement will bring about warpage and deformation in the injection molding of the product. At the same time, the glass fibers will be oriented in the flow direction during the injection molding process. This will enhance the mechanical properties in the flow direction and increase the shrinkage in the vertical direction, reducing the molding quality of the product. In this study, a test program was developed based on the Box-Behnken test design in the Design-Expert software, using a plastic part as an example.

Abstract Selective inhibition sintering (SIS) results in easy, flexible, fast, and cost-efficient fabrication of functional parts by using powder material for various applications. The functional part is important for operational examination by fabricating the part unswervingly from computer-aided design (CAD) data. However, poor surface quality is the major disadvantage in the SIS procedure. The selection procedure of optimal operating parameters plays a major role in the fabrication of end products. The present study discusses the effect of key contributing operating parameters on the surface quality of the polyamide parts fabricated by the SIS process. Parameters like heater power (HP), layer thickness (LT), heater feed rate (HFR), machine feed rate (MFR), and bed temperature (BT) were considered in this study.

Abstract Joining titanium (Ti) alloys with conventional processes is difficult due to their complex structural properties and ability of phase transformation. Concerning all the difficulties, diffusion bonding is considered as an appropriate process for joining Ti alloys. Ti6Al4V, which is an α+β alloy widely used for aero engine component manufacturing, is diffusion bonded in this investigation. The diffusion bonding process parameters such as bonding temperature, bonding pressure, and holding time were optimized to achieve desired bonding characteristics such as shear strength, bonding strength, bonding ratio, and thickness ratio using response surface methodology (RSM). Empirical relationships were developed for the prediction of the bond characteristics, and sensitivity analysis was performed to determine the increment and decrement tendency of the shear strength with respect to the bonding parameters.

Abstract In the process of injection molding, the vacuum pump rear housing is prone to warping deformation and volume shrinkage, which affects its sealing performance. The main reason is the improper control of the injection process and the large flat structure of the vacuum pump rear housing, which does not meet its production and assembly requirements (the warpage deformation should be controlled within 1.1 mm and the volume shrinkage within 10%). To address this issue, this study initially utilized orthogonal experiments to obtain training samples and conducted a preliminary analysis using gray relational analysis. Subsequently, a predictive model was established based on a one-dimensional convolutional neural network (1D CNN).

Abstract Halogen detector is an important halogen gas leakage detection instrument. In order to ensure that the upper and lower shells have the same quality, it is necessary to use one mold and two pieces in production. Compared with the conventional one-mold two-cavity process, it is easier to produce warpage and volume shrinkage. To solve this problem, a multi-objective injection molding process optimization method based on deep neural network (DNN) model based on stochastic weight average (SWA) method and multi-objective evolutionary algorithm based on decomposition (MOEA/D) was proposed. Melt temperature, mold temperature, injection pressure, holding pressure, holding time, and cooling time are the six parameters and important structure parameters (gate diameter) as design variables, warpage, and volume shrinkage rate as the optimization goal. The neural network model between variable and goal was established, and the MOEA/D algorithm was used for global optimization.

Abstract Raceway Brinell damage is one major cause of wheel bearing (hub unit) noise during driving. Original Equipment Manufacturer (OEM) customers have asked continuously for its improvement to the wheel bearing supply base. Generally, raceway Brinelling in a wheel hub unit is a consequence of metallic yielding from high external loading in a severe environment usually involving a side impact to the wheel and tire. Thus, increasing the yielding strength of steel can lead to higher resistance to Brinell damage. Both the outer ring and hub based on Generation 3 (Gen. 3) wheel unit are typically manufactured using by AISI 1055 bearing quality steel (BQS); these components undergo controlled cooling to establish the core properties then case hardening via induction hardening (IH). This paper presents a modified grade of steel and its IH design that targets longer life and improves Brinell resistance developed by ILJIN AMRC (Advanced Materials Research Center).

Abstract The objective of this investigation is to study the cyclic deformation behavior of SA333 Gr-6 C-Mn steel at 300°C. Low cycle fatigue tests were carried out at total strain amplitude between ±0.35 and ±1.25% at a constant strain rate of 1 × 10−3 s−1. Ratcheting tests were conducted at a various combination of mean stress and stress amplitude at a constant stress rate of 115 MPa s−1. The material SA333 Gr-6 steel exhibits cyclic hardening throughout its fatigue life. The material shows non-Masing behavior and deviation (δσo ) from Masing behavior increase with an increase of strain amplitude. Ratcheting strain accumulation increases, whereas ratcheting life decreases with an increase in mean stress or stress amplitude. With an increase in mean stress and stress amplitude, ratcheting rate also increases. The material shows hardening characteristic due to dynamic strain aging (DSA) phenomena.

Lightweighting in the automotive industry has been primarily motivated by fuel economy and greenhouse gas emission targets. The target greenhouse gas emissions and, therefore, the fuel economy for the average vehicle in both the United States and European Union are required to achieve significant annual improvements through 2026. Weight reduction, or lightweighting of an automobile, provides improvements not only in the fuel economy of engine-powered vehicles but also provides for improvements in the driving range of electric vehicles. As an industry example, the 2017 Chrysler Pacifica minivan utilizes a blend of high-strength steels, aluminum, and magnesium to reduce vehicle weight by over 100 kg, helping achieve a nearly 10% reduction in greenhouse gas emissions in a larger vehicle footprint with increasing industry safety demands [1].