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Abstract In recent years, the use of cutting fluids has become crucial in hard metal machining. Traditional non-biodegradable cutting fluids have long dominated various industries for machining. This research presents an innovative approach by suggesting a sustainable alternative: a cutting fluid made from a blend of glycerol (GOL) and distilled water (DW). We conducted a thorough investigation, creating 11 different GOL and DW mixtures in 10% weight increments. These mixtures were rigorously tested through 176 experiments with varying loads and rotational speeds. Using Design-Expert software (DES), we identified the optimal composition to be 70% GOL and 30% DW, with the lowest coefficient of friction (CFN). Building on this promising fluid, we explored further improvements by adding three nanoscale additives: Nano-graphite (GHT), zinc oxide (ZnO), and reduced graphene oxide (RGRO) at different weight percentages (0.06%, 0.08%, 0.1%, and 0.3%).

Abstract Super duplex stainless steel (SDSS) is a type of stainless steel made of chromium (Cr), nickel (Ni), and iron (Fe). In the present work, a 1.6 mm wide thin sheet of SDSS is joined using gas tungsten arc welding (GTAW). The ideal parameter for a bead-on-plate trial is found, and 0.216 kJ/mm of heat input is used for welding. As an outcome of the welding heating cycle and subsequent cooling, a microstructural study revealed coarse microstructure in the heat-affected zone and weld zone. The corrosion rate for welded joints is 9.3% higher than the base metal rate. Following the corrosion test, scanning electron microscope (SEM) analysis revealed that the welded joint’s oxide development generated a larger corrosive attack on the weld surface than the base metal surface. The percentages of chromium (12.5%) and molybdenum (24%) in the welded joints are less than those in the base metal of SDSS, as per energy dispersive X-ray (EDX) analysis.

Abstract The use of appropriate loads and regulations is of great importance in weld fatigue assessment of rail on-track maintenance equipment and similar vehicles for optimized design. The regulations and available loads, however, are often generalized for several categories, which proves to be overly conservative for some specific categories of machines. EN (European Norm) and AAR (Association of American Railroads) regulations play a pivotal role in determining the applicable loads and acceptance criteria within this study. The availability of track-induced fatigue load data for the cumulative damage approach in track maintenance machines is often limited. Consequently, the FEA-based validation of rail track maintenance equipment often resorts to the infinite life approach rather than cumulative damage approach for track-induced travel loads, resulting in overly conservative designs.

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 Single point incremental forming (SPIF) is a robust and new technique. In the recent research scenario, materials properties such as microstructure, micro-texture analysis, and crystal structure can be accessed through characterization non-destructive techniques, e.g., scanning electron microscope (SEM), electron backscattered diffraction (EBSD), and X-ray diffraction (XRD). XRD is a non-destructive method for analyzing the fine structure of materials. This study explores how process variables such as wall angle, step size, feed rate, and forming speed affect the parts of large-, medium-, and small-sized truncated cones of aluminum alloy AA3003-O sheet. Several cone parts of truncated cones are used in this investigation to implement Scherrer’s method. The two primary determining factors peak height and crystallite size are assessed for additional analysis in the present research.

Abstract Due to the limitations of current battery manufacturing processes, integration technology, and operating conditions, the large-scale application of lithium-ion batteries in the fields of energy storage and electric vehicles has led to an increasing number of fire accidents. When a lithium-ion battery undergoes thermal runaway, it undergoes complex and violent reactions, which can lead to combustion and explosion, accompanied by the production of a large amount of flammable and toxic gases. These flammable gases continue to undergo chemical reactions at high temperatures, producing complex secondary combustion products. This article systematically summarizes the gas generation characteristics of different types and states of batteries under different thermal runaway triggering conditions. And based on this, proposes the key research directions for the gas generation characteristics of lithium-ion batteries.

Abstract This study investigated the influence of high-strength low-alloy steel on the fatigue life of a load-bearing member with a non-load-bearing transverse welded attachment (T-joint). It compared high cycle fatigue data to two fatigue design codes, namely BS 7608 and Eurocode EN 1993-1-9. Different base and filler material combinations of varying material strengths were investigated, resulting in a total of three different specimen configurations. Two material combinations had a high-strength steel (Strenx® 700 MC D) for the base material, with one combination having a matched filler material and the other having an undermatched filler material. The third material combination had a lower-strength steel (S 355 JR AR) for the base material, with a matched filler material. Tensile tests were performed to confirm the base material mechanical properties and weld quality of the manufactured specimens.

Abstract Nylon polymer with an optimal blend of Kevlar, fiberglass, and high-speed, high temperature (HSHT) Fiberglass offers improved characteristics such as flexural strength, wear resistance, electrical insulation, shock absorption, and a low friction coefficient. For this reason, the polymer composite manufactured by combining HSHT, Kevlar, and fiberglass with nylon as base material will expand the uses of nylon in the aerospace, automotive, and other industrial applications related to ergonomic tools, assembly trays, and so forth. The proposed work was carried out to investigate the continuous fiber reinforcement (CFR) in nylon polymer using a dual extrusion system. Twenty experimental runs were designed using a face-centered central composite design (FCCD) approach to analyze the influence of significant factors such as reinforcement material, infill pattern, and fiber angle on the fabricated specimen as per American Society for Testing Materials (ASTM) standards.

Abstract New Editor-in-Chief: Dr. Mark Barkey

Abstract Milling is a prevalent machining technique employed in various industries for the production of metallic and non-metallic components. This article focuses on the optimization of cutting parameters for polyamide (PA6) using carbide tools, utilizing a recently developed multi-objective, nature-inspired metaheuristic algorithm known as the Multi-Objective Grasshopper Optimization Algorithm (MOGOA). This optimization process’s primary objectives are minimizing surface roughness and maximizing the material removal rate. By employing the MOGOA algorithm, the study demonstrates its efficacy in successfully optimizing the cutting parameters. This research’s findings highlight the MOGOA algorithm’s capability to effectively fine-tune cutting parameters during PA6 machining, leading to improved outcomes in terms of surface roughness reduction and enhanced material removal rate.

Abstract TOC

Abstract The present investigation has been conducted to study the tribological and adhesion properties of X10CrNi18-8 austenitic stainless steel (ASTM 301) coatings deposited on aluminum alloys such as AU4G by using the arc-spraying process. These coatings were made with and without a bond-coat layer, which is constituted by NiAl. The structure of the phases that are present in coatings was characterized by X-ray diffraction (XRD) and scanning electron microscopy (SEM). The measurements of microhardness and tribological behavior at different loads were also performed on the surface of the coatings. Adherence test was also carried out using four-point bending tests. The SEM showed that the dense microstructures of coatings have a homogeneous lamellar morphology with the presence of porosities and unmelted particles. The main phase of coating corresponds to a solid solution as a face-centered cubic (fcc).

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 With the introduction of advanced lightweight materials with complex microstructures and behaviors, more focus is put on the accurate determination of their forming limits, and that can only be possible through experiments as the conventional theoretical models for the forming limit curve (FLC) prediction fail to perform. Despite that, CAE engineers, designers, and toolmakers still rely heavily on theoretical models due to the steep costs associated with formability testing, including mechanical setup, a large number of tests, and the cost of a stereo digital image correlation (DIC) system. The international standard ISO 12004-2:2021 recommends using a stereo DIC system for formability testing since two-dimensional (2D) DIC systems are considered incapable of producing reliable strains due to errors associated with out-of-plane motion and deformation.

Abstract Point cloud objects have gained popularity in three-dimensional (3D) printing recently due to advancements in reverse engineering technology. Fabricating an object with a fused deposition modeling (FDM) printer requires converting the object to layered contours, which involves a slicing process. The slicing process of a point cloud object usually requires reconstructing a 3D object from a point cloud, which requires users’ deep understanding of 3D modeling software and a laborious work process. To avoid these problems, the direct slicing of point cloud objects is gaining more popularity. This research work proposes an adaptive slicing approach from point cloud objects directly without surface reconstruction. The adaptive slicing maintains the global geometry error while requiring a smaller number of fabrication layers and printing time. A new error profile used in the adaptive slicing approach is introduced.

Abstract The joining of dissimilar AISI 1020/AISI 1018 steel and AISI 431/AISI 1018 steel carries significant importance in automotive applications to lower the cost of manufacturing and obtain the mechanical properties of different materials. However, the joining of these materials by fusion welding is difficult particularly for a rod-to-plate joint configuration such as solidification cracking, wider heat affected zone (HAZ), HAZ softening, high residual stresses, and distortion of joint configuration. So, to overcome the issues in fusion welding of AISI 1020/AISI 1018 steel and AISI 431/AISI 1018 steel, rotary friction welding (RFW) was employed to develop the rod-to-plate joints. The parametric empirical relationships (PERs) were developed using regression equations incorporating RFW parameters to predict tensile strength (TS) and weld interface hardness (WIH) of rod-to-plate joints.

Abstract The purpose of this research is to fabricate a multipurpose drone with different lightweight materials that are used for water irrigation as well as pesticide spraying in agricultural fields. Components are collected and the drone is fabricated based on the parameters required for payload, weight, and design calculations. After the completion of fabrication, the drone is tested using different masses of payload for better endurance. The drone arms are made of balsa wood and stands are fabricated with polyvinyl chloride (PVC) and carbon fiber. The obtained results proved that a full payload is able to fly for 7 min; at the same time if we reduce the payload to 50%, the endurance will be increased double the time. In this study, the same drone and pumping configuration is used to perform the water and pesticide irrigation over various areas on agricultural land, which is achieved by changing the tank quantity.

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 In the current research, an aluminum alloy AA8090 is welded using the friction stir welding (FSW) technique. The main objective is to eliminate the chances of defects in the weld joint, which were observed in the conventional joining process. Experiments were planned according to the one factor at a time (OFAT) approach. The input process parameters involved during the present work are welding speed (WS), rotational speed (RS), tilt angle (TA), and dwell time (DT). However, the response variables investigated at different input parametric combinations are tensile strength (TS), percentage elongation (EL), microhardness (MH), and macroscopic structure. Due to the combination of both attributes of optimization (the higher the better in TS and the lower the better in EL), the multi-performance quality characteristics optimization approach, i.e., grey relational analysis (GRA), is implemented.

Abstract Gear transmission error (TE) is one of the internal excitation on transmission system vibration and noise. The vibration analytical model of transmission system was constructed by considering the dynamical characteristics of a gear box, which were verified by comparing the modal frequency and mode shapes between simulation results and experiment data. The vibration and radiated noise of transmission was analyzed by the transmission NVH test data. The mechanism of load conditions, TE, and system resonance influence on transmission system vibration and noise are investigated in details. Based on the vibration analysis model, the effects of pitch error, helix tilt deviation, and radial runout error on gear pair meshing characteristics and system vibration response are studied individual.