International Journal of Advanced Manufacturing Technology最新文献

The dual-drive feed system can significantly reduce the effects of nonlinear friction. However, due to the numerous heat sources in its system, the thermal responsive mechanism is still unclear. The reason restricts the realization of high-precision micro-feed. Moreover, the existing thermal simulated model of the machine tool oversimplifies the calculation process of thermal contact resistance (TCR), resulting in a significant error in simulation. Therefore, a full-state TCR calculation model is proposed, and based on the model, a high-precision thermal behavior model of the dual-drive feed system is established. Firstly, the entire deformation process of the asperities is characterized by using fractal theory, and the TCR between the joint parts of the feed system is calculated by considering the thermal resistance of air or grease. A thermal simulated model of the dual-drive feed system is developed based on the solved heat generation and the heat transfer coefficients. Then, the temperature rise characteristics of the dual-drive feed system and the responsive mechanism of thermal deformation under different working conditions are analyzed. The influence of TCR on temperature field distribution and deformation field is discussed. Finally, the experiments on temperature rise and thermal deformation are conducted on the dual-drive feed system. The results of the simulated analysis and experiments show that the accuracy of the simulation can be significantly improved by using the full-state TCR model. The error of the thermal model based on the full-state TCR is much smaller than that of the general TCR model and the without TCR. The accurate description of the TCR has an essential impact on the accuracy of the simulated model, and the obstruction of the heat flow by air or grease cannot be neglected.

Abstract

Peen forming is a method for deforming metal sheets by introducing plastic strain near the peened surface through shot impacts. The resulting shape after peen forming is affected by peening conditions (such as shot velocity, shot diameter, and nozzle trajectory) and the specimen size. This study aimed to clarify the mechanism of the spherical to cylindrical deformation shift in peen forming, through experiments and numerical simulations using the finite element method by varying the specimen geometry, nozzle trajectory, and air pressure. The deformation of sheets, 200 mm × 200 mm × 2 mm (length, width, thickness), shifted from spherical to cylindrical at an approximate curvature of 0.4 m⁻¹. These shifts occurred at smaller curvatures in wider specimens. Numerical simulation using a three-step finite element method was used to calculate the spherical to cylindrical deformation shift. The simple spherical bending model showed that the deformation shifted from spherical to cylindrical, when the strain in the center of the thickness at the edge of the sheet was compressive. This result was consistent with the experimental and numerical simulation results.

This study reports a methodology for predicting surface roughness using data-driven models with grinding force as the input data. Prior to the model training process, the critical grinding parameters for brass material were selected and optimized using the Taguchi method. The experimental grinding force data were then collected and preprocessed into three features: the raw feature as the baseline feature, the statistical feature, and the fast Fourier transform (FFT) feature. The data were imported into a linear regression model as the baseline model and a deep neural network (DNN) model as the proposed strategy. The widely used surface roughness (Ra) of the ground workpiece was experimentally measured and served as the performance index. The model’s performance was evaluated based on the mean absolute percentage error (MAPE) between the predicted and measured Ra values. The validation of the Ra prediction revealed that, among all test combinations, the DNN model with four hidden layers and the FFT feature as the input had the best performance of surface roughness prediction, with a MAPE of 3.17%. The independent testing and evaluation of the DNN model with the FFT feature yielded a MAPE of 6.96%, indicating that the proposed strategy effectively predicted the surface roughness of the workpiece. This work also proposes an automatic regrinding strategy in which the grinding system automatically regrinds the workpiece if the predicted Ra of the workpiece in the previous grinding process exceeds the threshold. Experimental results confirmed that among 24 ground areas, two areas have roughness exceeding the threshold and need to be regrind, and the proposed strategy can correctly identify and regrind these two areas (100% success rate). After automatic regrinding, the workpiece exhibited a roughness lower than the set threshold.

The joining of aluminum alloy AA5052 and carbon-fiber-reinforced polyether ether ketone (CF/PEEK) by friction lap welding was investigated under different conditions of surface texturing and process temperatures. The joint quality was evaluated by measurement of the tensile shear force and examination of the joint morphology. The aluminum alloy underwent two different types of surface texturing—mechanical engraving and sandblasting. The welding experiments were then conducted under different tool rotational speeds for each. The temperatures across the weld line were measured during the welding process using thermocouples mounted at specific locations. The temperature distribution at the interface was determined by an inverse heat conduction method. It was found that the temperatures at the interface exceeded the melting temperature of PEEK for all testing conditions but was always below PEEK thermal degradation temperature. It was also found that joint performance of mechanically engraved samples increased with the increase of interface temperatures. This was attributed to the increased mechanical interlocking due to the flow of melted PEEK into the engraved sample’s surface features. The joint strength of sandblasted samples did not change considerably with interface temperatures.

This article focuses on enhancing the range of motion (ROM) of the Tetra II joint, a spherical compliant joint consisting of three internally interconnected tetrahedron-shaped elements that achieve motion through elastic deformation. Despite its excellent precision, this specific design is constrained in terms of ROM due to internal contacts among the tetrahedral elements. To overcome this limitation, this study utilizes a computer-aided engineering (CAE) framework to optimize the configuration of the Tetra II joint and enhance its ROM. The resultant optimized joint, referred to as Tetra III, is subsequently compared to Tetra II in terms of both ROM and center shift. Finite element models (FEM) are employed to validate the optimization results and examine how various tetrahedron-shaped geometries impact the joint’s performance. The newly optimized joint exhibits a significantly higher ROM compared to the previous version, while maintaining excellent precision and overall smaller dimensions. Finally, to demonstrate its manufacturability, the Tetra III joint is produced using selective laser sintering (SLS) technology, with Duraform PA serving as the construction material. The successful fabrication serves as a demonstrative example of the improved design of the Tetra III joint.

The objective of this experimental study is to utilize rotary friction welding (FW) for assembling similar polyamide materials. The application of the SVM approach enables the development of a predictive model for estimating mechanical properties in RFW processes. Furthermore, the optimization of RFW parameters through GA proves pivotal in selecting optimal welding conditions, providing a variety of choices. The welding parameters considered in this study included rotation speed at five levels and traverse speed at three levels. The strength of the welded samples was characterized by a tensile test. Additionally, temperature measurements were taken to determine the maximum temperature in the joint area. The results demonstrated the dependence of tensile strength and maximum temperature on the rotation speed. Maximum tensile strength is achieved at an optimal rotation speed. Moreover, analysis of variance (ANOVA) indicates that rotation speed is the parameter most influenced by tensile strength.

High-entropy alloys (HEAs) are special type of alloy suitably developed for use in petroleum exploration, energy storage devices, medical implants, etc. This is because they possess excellent corrosion, thermal, and mechanical properties. Corrosion characteristic of HEAs prepared via spark plasma sintering is a top notch as the technique generates corrosion resistant phases and homogenous microstructure. This study was aimed at reviewing recent publications on corrosion characteristics of HEAs processed by SPS in order to develop ways of improving their anti-corrosion properties. The resource materials were obtained from Scopus-indexed journals and Google Scholar websites of peer-reviewed articles published within the last 5 years. From the study, it was revealed that incorporation of some elements (Al, Cr, Ti) into HEAs can improve their corrosion resistance, while addition of some others can reduce their brittleness and enhance their stability and formability. It was recommended that optimization of SPS parameters was one of the strategies of generating better corrosion characteristics in HEAs.

Failure of resistance spot welds in computer-aided engineering models is based upon criteria that incorporate test data obtained in various loading conditions including different proportions of tensile, shear, and moment loads. The decomposition of the critical load into its respective shear, tensile, and bending moment components is influenced by the rigid body motion during their corresponding mechanical tests. Continuous tracking of the weld orientation and the deformed coupons is required for accurate determination of the load components at the onset of failure. A comprehensive experimental investigation was performed to characterize the critical failure load components in combined loading using various orientations of KS-II tests and a range of coach peel coupon geometries. Mechanical testing was coupled with digital image correlation (DIC) to systematically evaluate empirical force-based failure models for resistance spot welds of two third generation advanced high strength steels with optimal and suboptimal fusion zone diameters. New analysis methodologies using DIC were developed to account for rotation and deformation of the joint in the determination of the shear, normal, and bending moments acting on the spot-welded joints. The coach peel test results for both steels revealed a non-convex experimental fracture locus in bending-tension loading cases. The conventional assumption of a convex failure locus overestimated the critical bending moment strength between 7 and 66%. Results indicated that changes in the operative failure mechanism from pullout/partial-pullout to interfacial can expand the fracture loci within the shear-tensile loading mixities. Improved alternative functional forms for the weld failure models were proposed and contrasted with conventional models that assume convexity.

This research delves into the numerical predictions of fill-level and residence time distribution (RTD) in starve-fed single-screw extrusion systems. Starve-feeding, predominantly used in ceramic extrusion, introduces challenges which this study seeks to address. Based on a physical industrial system, a comprehensive 3D computational fluid dynamics (CFD) model was developed using a porous media representation of the complex multi-hole plate die. Validations performed using real sensor data, accounting for partial wear on auger screw flights, show an ~11% discrepancy without accounting for screw wear and ~6% when considering it. A 2D convection-diffusion model was introduced as a dimensionality reduced order model (ROM) with the intention of bridging the gap between comprehensive CFD simulations and real-time applications. Central to this model’s prediction ability was both the velocity field transfer from the CFD model and calibration of the ROM diffusion coefficient such that a precise agreement of residence time distribution (RTD) curves could be obtained. Some discrepancies between the CFD and the ROM were observed, attributed to the loss of physical information of the system when transitioning from a higher fidelity CFD model to a semi-mechanistic ROM and the inherent complexities of the starved flow in the compression zone of the extruder. This research offers a comprehensive methodology and insights into reduced order modeling of starve-fed extrusion systems, presenting opportunities for real-time optimization and enhanced process understanding.

The demand for 3D-printed high-performance polymers (HPPs) is on the rise across sectors such as the defense, aerospace, and automotive industries. Polyethyleneimine (PEI) exhibits exceptional mechanical performance, thermal stability, and wear resistance. Herein, six generic and device-independent control parameters, that is, the infill percentage, deposition angle, layer height, travel speed, nozzle temperature, and bed temperature, were quantitatively evaluated for their impact on multiple response metrics related to energy consumption and mechanical strength. The balance between energy consumption and mechanical strength was investigated for the first time, contributing to the sustainability of the PEI material in 3D printing. This is critical considering that HPPs require high temperatures to be built using the 3D printing method. PEI filaments were fabricated and utilized in material extrusion 3D printing of 125 specimens for 25 different experimental runs (five replicates per run). The divergent impacts of the control parameters on the response metrics throughout the experimental course have been reported. The real weight of the samples varies from 1.06 to 1.82 g (71%), the real printing time from 214 to 2841 s (~ 1300%), the ultimate tensile strength from 15.17 up to 80.73 MPa (530%), and the consumed energy from 0.094 to 1.44 MJ (1500%). The regression and reduced quadratic equations were validated through confirmation runs (10 additional specimens). These outcomes have excessive engineering and industrial merit in determining the optimum control parameters, ensuring the sustainability of the process, and the desired functionality of the products.

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