International Journal of Advanced Manufacturing Technology最新文献

In this study, mahogany seed oil was sourced and prepared, and the performances were compared with mineral oils. The extracted oil was characterized to recognize properties related to pyto-chemical, physio-chemical lubricity and thereafter used along with mineral oil for the formulation of cutting fluid using emulsifying agent, anti-corrosive agent, biocides, and anti-foam agent as additives. These additives were added to oil and water by using 2⁴ full factorial design to achieve the optimal combination. In addition, central composite design (CCD) was adopted for the experimental design, and the performance of the mahogany oil-based cutting fluid (MBCF) was investigated in terms of surface finish, cutting temperature, material removal rate, machine sound level, and chips formation and, thereafter, compared with conventional mineral oil (CBCF) in turning of AISI 304 steel under flood cooling technique. Experimental data were analyzed using analysis of variance (ANOVA) and grey relational analysis (GRA). The experimental findings showed that optimal multi-response performance of the MBCF can be achieved using spindle speed, feed rate and depth of cut of 1100 rev/min, 0.27 mm/rev, and 0.23 mm, respectively, while optimal multi-response performance of CBCF can be achieved with spindle speed, feed rate, and depth of cut of 900 rev/min, 0.62 mm/rev, and 0.23 mm, respectively.

The concepts of digital twins (DTs) have been widely studied to predict system performance, shorten design cycles, and implement preventive maintenance, but mainly, in large-scale enterprises. It is extremely beneficial to the whole manufacturing sector, since DTs can be readily implemented in small and medium-sized enterprises (SMEs) with basic computer aided engineering (CAE) tools; over 95% enterprises are SMEs. This paper aims to prove the feasibility of using commercial CAE tools, such as SolidWorks Simulation, to design air-quenching processes for SMEs. SMEs can benefit to explore new business opportunities, reduce system design cycle, and improve existing air-quenching processes. To our knowledge, it will be the first work of adopting DTs in conceptual design of an air-quenching process in sense that (1) the need of simulating an air-quenching process before physical implementation is discussed thoroughly; (2) heat transfer processes are classified, governing mathematical models for various heat transfer behaviors are introduced to present an evaluation model of a heat transfer process; (3) main process variables of air-quenching are identified; (4) a DT of an air-quenching process is developed and simulated to verify the capabilities of commercial SolidWorks Simulation; (5) case studies are developed to show how a CAE tool can be used in DTs. The findings from the reported work are summarized with a debrief of our future work.

Compacted graphite iron (CGI) is increasingly used in industrial production due to its excellent mechanical property, especially in the field of high-performance automotive engine manufacturing, and has become a substitute for gray cast iron (GCI). However, the hard-to-machine problem caused by its excellent physical properties was the main issue affecting the surface quality of the CGI workpiece. As a new type of tool, the wiper insert could effectively improve the surface quality. In order to develop a long lifespan and high-stability wiper insert tool for CGI milling, this study conducted a series of experiments, including tool design and simulation, coating preparation and testing, and tool cutting performance testing. In the optimization of simulation analysis of tool geometric parameters, it was found that the numerical value of curved cutting-edge radius had a more significant impact on the cutting performance of wiper insert. In the coating test, AlCrN-coated wiper insert C with a coating thickness of 2.84 µm had the best load bearing and fracture toughness performance in the coating mechanic test and had the best coating bonding performance in the scratch test. In the milling experiment with a cutting speed of 125.7 mm/min, a feed rate of 0.15 mm/r, and a cutting depth of 0.5 mm, the coated wiper insert C had the longest tool life and the best machined surface quality of the workpiece. Compared to other coated tools, the tool life was extended by at least 15.7%, and the effective cutting area was increased by 20%, which means it was the most suitable tool for machining CGI.

In order to improve the accuracy of the thermal error model of the electric spindle, a thermal error modeling method based on the optimized Elman neural network using the cuckoo algorithm is proposed. To analyze the thermal behavior of the electric spindle, an ANSYS analysis approach is utilized to create a temperature map. Based on the simulation analysis outcomes, an experimental platform is established to gather temperature data and thermal displacement data. The electric spindle temperature is optimized through the utilization of fuzzy cluster analysis and the Spearman rank correlation coefficient method in combination. The comparison between the established model and the Elman model and the GA-Elman model proves that the CS-Elman model has good prediction accuracy and stability.

Ball-end milling cutters are commonly used for precision processing of complex curved parts in CNC systems. However, the milling process often experiences chatter, leading to final surface damage. To solve the problem, the method of automatically adjusting the tool posture was proposed to avoid chatter problems during the milling process. Frequency response function varies along the processing path. The frequency domain control equation for ball-end milling cutter machining under different operating conditions was established in the feed coordinate system, and the stability of the system at the cutting point can be quickly determined by Nyquist. In order to accurately solve the control equation, a method for solving the Cutter Workpiece Engagement (CWE) boundary under different tool postures was designed. The feasible region for the tool axis was searched based on geometric and stability constraints at each original tool path position. In the feasible domain, the tool axis path was optimized and the tool position file was updated with the constraint of machine tool rotation axis smoothness. Milling experiments were conducted on AL7050-T745 workpiece. From the simulation and experimental results, it can be concluded that milling width and tilt angle have significant impact on the milling process. The method proposed in this article has been experimentally validated in a five-axis ball-end milling experiment.

The manufacturing technique known as investment casting has found extensive application in producing metal components featuring intricate geometries. The production efficiency of the wax patterns is an essential issue in the investment casting industry, especially for the mass production of wax patterns. A conformal cooling channel (CCC) performs the rapid uniform cooling process for injection molding. However, the significant pressure drop along the cooling channels is a distinct disadvantage of CCC. In this study, an innovative waterfall cooling channel (WCC) was proposed and implemented. The WCC cools the injected products by surface contact, replacing the conventional line contact to cool the injected products. The WCC was optimized using Moldex3D simulation software. Rapid tools with two kinds of cooling channels were designed and implemented. The cooling time of the molded part was investigated using a low-pressure wax injection molding machine. Considering a water cup characterized by a mouth diameter of 70 mm, a height of 60 mm, and a thickness of 2 mm, the experimental results confirmed that the use of WCC can save the cooling time of the product by about 265 s compared with the CCC. This result shows that the WCC can increase cooling efficiency by approximately 17.47% compared with conventional CCC.

The use of fused deposition modeling (FDM) in printing polymers for various applications has been ever increasing. However, its utilization in printing polymers for high-strength and superior surface finish applications is still a challenge, primarily due to process intrinsic defects, i.e., voids between the layers and the rough exterior arising from unrestrained deposition of molten polymer. This research hypothesizes that application of ultrasonic vibration (USV) post-fabrication could minimize these shortcomings. For this investigation, ASTM D638 Type IV samples were FDM-printed using poly(lactic) acid (PLA). Through screening experiments, an optimized set of ultrasonic parameters was determined. Then, the effect of both-sided ultrasonic application was characterized. Subsequently, the impact of USV on the samples’ physical, tensile, and morphological properties was examined by varying the layer height, infill patterns, and % infill density. Up to 70% roughness reduction was observed as a result of post-FDM ultrasonic application. Additionally, the tensile strength of the samples increased by up to 15.31%. Moreover, for some lower % infill samples, post-ultrasonic tensile strengths were higher than 100% infill control samples. Analysis of scanning electron microscopy (SEM) and X-ray computed tomography (CT) imagery indicated enhanced layer consolidation and reduced void presence in samples treated with ultrasonic. The combination of ultrasonic-generated heat and downward pressure promoted a synergistic squeeze flow and intermolecular diffusion across consecutive layers of polymers. As a result, increased tensile strength and surface finish were achieved while dimensional change was marginal.

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.