International Journal of Precision Engineering and Manufacturing-Green Technology最新文献

This study compares the electrically assisted pressure joining (EAPJ) performances of two non-ferrous alloys, aluminum (Al) 6061-T6 and copper (Cu) C11000. For joining, two cylindrical specimens with identical geometries are assembled in a longitudinal direction. Electric currents with various electric current densities are applied directly to the specimen assemblies during continuous axial plastic deformation. Microstructural analysis confirms that the joints are successfully fabricated without melting and solidification in both material combinations. While the mechanical properties of the joints are strongly affected by the electric current density, the results also show that both joining temperature and amount of plastic deformation for successful EAPJ of the C11000 alloy are much lower than those of the Al 6061-T6 alloy. In EAPJ, the Cu C11000 even can be joined at a temperature (250 °C) lower than the 0.3–0.7T_m range (T_m: the melting temperature of material), while the Al 6061-T6 requires the joining temperature (450 °C), which is about 0.7T_m for that material. The present study confirms that the process parameters for successful EAPJ can strongly differ depending on the metal alloy.

This review paper aims to outline methods and applications of green chemistry and sustainable engineering in chemical vapor deposition (CVD) for semiconductor mass production termed as green CVD. The method includes: sustainable chemical processes, efficient equipment designs and hibernation operation. Sustainable chemical process involved 40% reduction of diisopropylamino silane (DIPAS) with saturation time optimization, reduction of 20% with divert-less ALD and 60% with hybrid ALD methods. Polysilazane reduction by 29% in DRAM process via new dispense rotation mechanism. Reduction in greenhouse gases of nitrogen trifluoride (NF₃) by 27% and 25% with ramping down method and N₂ additive gas incorporation respectively. Nitrous oxide reduction of 67% ca. 23.6 kt CO₂ from year 2020 to 2022 with recipe modification. Efficient equipment design methods via systematic and safe precursor retrieval with solvent development with improved abatement and waste gas treatment. Hibernation operation system is forecasted to save up to 15% in cost due to electrical and chemical consumption reduction in collaboration with major semiconductor equipment companies.

Abstract

Polishing is one of the most crucial finishing processes and usually consumes a sufficient slurry to achieve an ultra-fine surface. However, excess slurry consumption is environmentally costly, as it generates a large amount of wastewater. Given the growing environmental concerns, it is essential to improve the process efficiency and minimize the environmental burdens. Considering this, a novel polishing system, herein referred to as center-injected polishing, is proposed by injecting slurry into the center of the polishing pad. Here, it is aimed to utilize the centrifugal force of the rotating pad, with the aim of efficient slurry utilization. The slurry is directly introduced between the pad and the workpiece, then dispersed across the pad by centrifugal force. A simple experiment was conducted with computational analysis using the specially designed polishing tool to prove the concept; slurry was distributed more uniformly in center-injected polishing when compared to the conventional process. The polishing system was then constructed to evaluate polishing performances. Based on sets of experiments in the polishing of silicon carbide (SiC), slurry efficiencies and productivity were analyzed with respect to different rotational speeds and slurry supply rates. The material removal rate (MRR) was more than twice the rate achieved by conventional polishing at the same processing conditions; whereas the slurry consumption was approximately 60% less at the same MRR. The extended Preston equation was used to predict the MRR of the new process. It is expected that efficient slurry utilization will reduce the environmental footprint of abrasive processes.

Gas emissions pose significant environmental and health concerns in thermal processes involving thermoplastic polymers. This issue also extends to material extrusion (MEX) additive manufacturing (AM), which is a thermal process. Therefore, it is crucial to examine gas emissions during MEX AM. This study focused on super engineering plastics (SEPs) such as polyetheretherketone, polysulfone, and polyetherimide. A portable emission-measuring device was employed to analyze total volatile organic compounds (TVOCs) and formaldehyde (HCHO) emitted during MEX AM at various nozzle temperatures. Additionally, the anisotropy of tensile strengths in the SEP specimens fabricated in the longitudinal and transverse deposition directions was evaluated. Overall, the SEPs emitted TVOCs and HCHO within the range from not detected (N/D) to 0.595 mg/m³ and from N/D to 0.139 mg/m³, respectively, based on the nozzle temperature during MEX AM. Moreover, the tensile strengths varied from 59.0 to 83.4 MPa in the longitudinal deposition direction and from 19.2 to 55.7 MPa in the transverse deposition direction. Lower nozzle temperatures not only resulted in reduced gas emissions but also led to lower tensile strength in all the SEPs. However, the strategic use of longitudinal deposition can mitigate the reduction in tensile strength. To demonstrate this, a case study involving the fabrication of a Warren truss bridge was presented. This study provides guidelines for the deposition strategy in MEX using SEPs under AM conditions, aiming to minimize gas emissions while maintaining a tensile strength ranging from 81.1% to 88.7% of the bulk specimen strength.

Draping simulation of complex egg-box structure is conducted using non-orthogonal constitutive VUMAT code and composite lay-up model. Laminated shell is modelled considering tension, in-plane shear, bending properties, and the influence of laminate thickness on the draping process to improved the finite element model, for high simulation accuracy. To determine the effect of draping angle and structure size on drapability, four draping angles (0°, 15°, 30°, 45°) and three structure sizes (small, medium, large) are considered in the simulation. The results are compared with experimental results. Shear deformation pattern, including wrinkle generation, is investigated in terms of structure size and draping angle by using a unit cell with two major axes (side-wall and saddle).

DC53 tool steel has potential applications in mold product manufacturing because of its excellent toughness properties. However, it suffers from poor wear resistance, which limits its wide range of applications. A micron-size fish-scale film structure was designed on the DC53 steel surface and fabricated using crossover laser surface remelting processing to improve its tribological properties. Three kinds of DC53 surfaces, including the as-received, quenched, and fish-scale film structure, were used to evaluate the tribological properties. Specifically, tribological performance was evaluated using a reciprocating sliding tester. The unidirectional ball-on-disc method was employed to assess the wear of the mating surfaces under low-, medium-, and high-load conditions in terms of friction and wear tests. The friction coefficient and the wear rate were recorded to investigate the formation mechanism of tribo-layers. Experimental results demonstrated that the structure combined with microbulges on the DC53 surface had excellent load-bearing capabilities and wear resistance. Energy dispersive spectroscopy following wear tests showed pronounced material transfer from the structured surfaces, with SiO₂ particles filling up some groove voids. The reinforcing layer in the form of nanoscale SiO₂ particles exhibited enhanced performance at higher tribological loads. The synergistic effects of microbulges and SiO₂ films significantly improved the tribological properties of DC53 materials. In addition, the precipitation of SiO₂ contributed to the anti-wear performance of the tool steel surface, which is consistent with the self-lubricating wear mechanism of the worn surface. The laser surface remelting technique enables the fabrication of a micro fish-scale film structure, which has great potential for enhancing the wear resistance and applications of DC53 materials in various fields.

The zero-emission zone (ZEZ) is a recent environmental regulation that restricts the entry of internal combustion engine vehicles. In a ZEZ, hybrid electric vehicles (HEVs) are allowed but must operate in full-electric mode. Therefore, it is important for HEVs entering a ZEZ to have a sufficiently charged battery. This study presents a stochastic dynamic programming-based power management strategy for optimizing HEV charging in preparation for ZEZ drives. Stochastic dynamic programming models the driver's intentions as a Markov chain and designs optimal controllers by incorporating future probabilistic information up to an infinite time horizon. Furthermore, the proposed controller takes into account the remaining distance to the zero-emission zone, enabling efficient charging. Compared to stochastic dynamic programming strategies that do not consider the remaining distance, the proposed power management strategy improves the equivalent fuel efficiency by up to about 21%.

This paper presents the results of research on the impact of the use of different tools and the shape of the additional rivet, on the geometric quality of the joint, the energy consumption of the forming process, the distortion of the steel samples, and the load capacity of the joints. The tests were carried out for DX51D steel sheets with a thickness of 1.5 [mm] joined by using three different sets of tools. A steel rivet with a hardness of 400HV1 and various shapes was used for the tests. In addition to the full rivet, two types of rivet were used, the first with a through hole and the second with a depth of hole of 3 [mm]. The holes in the rivet had different diameters: 1.0, 1.5, 2.0 and 2.5 [mm]. The influence of changing the shape of the rivet (hole and its diameter) on the change in forming force and energy consumption of the joining process was analyzed. The lowest forming force was achieved for a rivet with a through hole and a hole diameter of 2.5 [mm]. The lowest joint forming force was obtained for the die with movable segments. For joints made with three tool arrangements and a series with a modified rivet, the amount of sheet metal deviation was analyzed. Of the three cases of arrangement of tools used to form the joint, the largest deviation of the sheets occurred at the clinch joint formed with a solid round die. In the case of a series of clinch-rivet joints with a modified rivet, the greatest deviation of the sheets occurred for the rivet with a hole of 1.5 [mm]. Changes in the geometric structure of the joint were also studied, and changes in the surface of the sheets in the joint area were observed. The highest value of the interlock in the joint was obtained when a solid rivet was used in the clinch-riveting technology. The strength of the joints was also identified in the lap shear test and the energy consumption at failure was determined. The use of a rivet increased the maximum load capacity to almost twice that of the clinch joint.

Graphical abstract

With the growing demand from the diabetic population and the advancement of lower limb biomechanics, the need for customized insoles for diabetic foot care and lower limb biomechanics correction is rapidly increasing. This has led to a digital transformation in the insole manufacturing process to achieve mass customization. This includes subtractive manufacturing and additive manufacturing. However, the environmental and social impacts of these processes have not been thoroughly assessed. Therefore, this study aims to analyze the ESG (Environmental, Social, and Governance) performance of existing digital processes compared to TP (traditional processes) and identify factors conducive to achieving both mass customization and sustainability. The results indicate that while NC (Numerical Control process) and 3DP (3D printing processes) benefit from digitization by reducing processing time (NC: 69%, 3DP: 38% of the labor hour needed for TP as 100%) and increasing the reliability of process, but NC is limited by energy consumption (TP: 0.39, NC: 0.9, 3DP: 0.32kWh) and manual grinding techniques. In the other hand, traditional process generates the most waste (Waste Weight Percentage: TP: 94.36%, CNC: 87.15%, 3DP) and requires the most processing space. The FFF (fused filament fabrication) type 3DP drastically shortens labor hour and technical barriers, providing an opportunity to change the service model of customized insoles from at least two visits to potentially just one. This makes the 3DP has the best chance to achieve the need of mass customization and the goal of ESG during the digital transformation. Not only the ESG goals but also the metamaterial ability to bring a better function to the insoles. In the future, by the introducing smart material into 4D printing, which can adapt to variable factors and change their structural characteristics, has the potential to enable a single pair of insoles to meet various usage scenarios. Moreover, the concept of 4D printing combined with sensors can elevate the application of insoles from medical usage for preventing or treating illness to daily usage forpredicting illness. This is a goal worth researching further to elevate worldwide healthiness.

Abstract

Battery state of health (SOH) estimation is imperative for preventive maintenance, replacement, and end-of-life prediction of lithium ion batteries. Herein, we introduce a data-driven approach to state of health (SOH) prediction for battery cells using a Deep Neural Network (DNN). Our DNN model, trained on short discharge curve segments, outperforms Multilayer Perceptron (MLP) and Support Vector Regression (SVR) models. The Mutual Information (MI) score guides the selection of voltage range and width for model training, reflecting nonlinear degradation characteristics. A transfer learning strategy is applied for outlier cells, initially training on normal cells and fine-tuning with outlier cells, resulting in improved SOH predictions, particularly at higher cycles. The study finds that increasing the segment width reduces SOH prediction error, with the smallest segment of 0.05 V demonstrating good performance (RMSE of 0.0246), decreasing to 0.0142 at a width of 0.2 V. For outlier cells, transfer learning leads to a 48% reduction in RMSE. The partial segment-based approach offers potential for rapid SOH prediction in laboratory and field applications, enhancing efficiency in the development process.