High-speed Manufacturing Research Articles

Single-step and parallel high-speed fabrication for Au micro-/nanostructures.

Patterns fabricated with Au nanoparticles (Au NPs) exhibit significant potential in fields such as micro-optics and bioelectronics. However, the current manufacturing methods still suffer from complex processes and low efficiency. In this work, we propose a high-speed manufacturing method for Au micro-/nanostructures based on spatiotemporal focusing and maskless lithography, achieving a throughput of 0.5 mm2/min. The surface electric field enhancement of the structure was confirmed using Raman spectroscopy, indicating that this method holds significant promise for metasurface, biosensing, and plasmonic chemistry.

Metals strengthen with increasing temperature at extreme strain rates

The strength of materials depends on the rate at which they are tested, as defects, for example dislocations, that move in response to applied strains have intrinsic kinetic limitations1–4. As the deformation strain rate increases, more strengthening mechanisms become active and increase the strength4–7. However, the regime in which this transition happens has been difficult to access with traditional micromechanical strength measurements. Here, with microballistic impact testing at strain rates greater than 106 s−1, and without shock conflation, we show that the strength of copper increases by about 30% for a 157 °C increase in temperature, an effect also observed in pure titanium and gold. This effect is counterintuitive, as almost all materials soften when heated under normal conditions. This anomalous thermal strengthening across several pure metals is the result of a change in the controlling deformation mechanism from thermally activated strengthening to ballistic transport of dislocations, which experience drag through phonon interactions1,8–10. These results point to a pathway to better model and predict materials properties under various extreme strain rate conditions, from high-speed manufacturing operations11 to hypersonic transport12.

Engineering perovskite solar cells for efficient wireless power transfer

Metal halide perovskites are a promising photovoltaic technology for energy harvesting due to their potential for low cost via high-speed manufacturing and their flexible light form factors offering high power per weight. This study presents an investigation of the energy harvesting performance of perovskite solar cells under monochromatic illumination via finite element simulations and experimental validation with high-efficiency double cation perovskite solar cells. Device performance across a broad range of illumination intensity is analyzed, providing insights into the mechanisms limiting energy harvesting in medium- and long-range wireless power transfer. The simulations also provide a guideline for compositional engineering of wide bandgap perovskites to improve the spectral match to efficient monochromatic sources. Based on these results, we show how perovskite solar cells can become a platform for efficient (>33%) medium-range wireless power transfer at the 5–50 m scale for power levels of 1 mW to 1 W.

On the tensile response of formed fiber networks with low areal density

Fiber networks are ubiquitous. The networks of interest to this study are distinguished from the widely studied planar random fiber networks (RFN) by their low areal density (grammage), preferential orientation, and fiber curl. Oriented networks are created through a high speed manufacturing process called forming in paper making. A dilute suspension of elastic fibers in water impinges on a moving wire to create a formed network. A discrete element method (DEM) based forming model is developed that incorporates the qualitative effects of fluid shear (preferred fiber orientation) and viscous drag during drainage (fiber conformation to the wire topography). Virtual tensile tests performed on thus formed networks reveal that the tensile response is initially softer due to non-affine deformation, and anisotropic due to preferential orientation. Consequently, an orientation dependent power law with a non-unique exponent emerges for the scaling of modulus and strength with the network density. Tensile test simulations reveal the re-alignment of fibers along the loading direction, and strong strain localization resulting in a few fibers (∼1%) carrying the imposed strain energy. Fiber curl and orientation are observed to govern the degree of non-affine response, stiffness, and strain localization, suggesting that controlling the degree of anisotropy and fiber curl offers the possibility to design networks for specific stiffness and specific strength.

Enabling predictive maintenance in high-speed manufacturing machines through critical parameter identification with sensor data

Enabling predictive maintenance in high-speed manufacturing machines through critical parameter identification with sensor data

High-Accuracy Detection and Classification of Defect and Deformation of Metal Screw Head Achieved by Convolutional Neural Networks

Nowadays, the industry requires automatic production for high-speed manufacturing. However, the products must also maintain high quality and reliability. An efficient inspection technique should be conducted for the improvement in the manufacturing quality. In order to achieve high inspection rate, optical inspection based on machine vision often raises the threshold of the judgment and this will worsen false detection. In this study, we propose a high-accuracy optical inspection system based on deep learning technology. Various defects in screw head are precisely detected and analyzed, which include surface damage, unprocessed, and stripped surfaces. An industrial camera and microscope system are employed to collect the raw images of metal screws with different defect types. The raw images of 3200 are utilized to train the designed convolutional neural networks. The experimental results indicate that the proposed system reaches a detection accuracy of 92.8% and the average detection speed is 0.03 second per image. In comparison with conventional machine vision methods, the proposed measurement system is more suitable for the inspection of industrial production line.

Does speed kill or make friction better?—Designing materials for high velocity sliding

Many modern applications rely on the safe operation of components sliding at high speeds, e.g., in the fields of e-mobility, high-speed manufacturing, or impact-resistant materials. While the impact of mechanical energy and heat on the friction and wear behavior of dry metallic interfaces has been the focus of extensive research in the past, the effect of extreme speeds on the near-surface deformation mechanisms in polycrystalline metals has remained poorly understood. In this work, we have tackled this crucial issue by exploring sliding velocities ranging from 10 to 2560 m/s via large-scale molecular dynamics simulations to identify three distinct deformation regimes in CuNi alloys. The microstructural response does not vary much for any of the considered systems up to sliding velocities of 40 m/s, but then evolves drastically up to a maximum value located between 320 and 1280 m/s depending on the composition. We observe that the degree of plastic deformation at the highest sliding speeds drops down to a level almost as low as for the lowest sliding speeds. We attribute this behavior to a sharp increase in the contact temperature at these high sliding speeds, approaching or even exceeding the bulk melting temperature, which goes hand in hand with a decline in the contact area and the resistance to sliding. Our characterization of the non-linear and non-monotonic material response to increasing sliding velocities will aid the systematic selection of materials and the design of robust components for a variety of high-speed sliding and wear applications.

Investigation on deformation of DP600 steel sheets in electric-pulse triggered energetic materials forming

Electric-pulse triggered energetic materials forming (ETEF) is a high-speed manufacturing process, which utilizes the chemical energy released by energetic materials (EMs) triggered by underwater wire discharge to plastically shape metals. ETEF is not fully understood, particularly in research on the discharge characteristics of energetic materials triggered by metal wires and the deformation process of metal sheets. The above two problems were investigated in this paper using experimentation and numerical simulation. For the pulse discharge characteristics, the peak values of voltage and current were reduced during the triggering process of energetic materials, and the triggering energy consumption of energetic materials was quantified to be about 200 J. The matching parameters of different capacitor-voltage devices may be insensitive to triggering the energy release of energetic materials. The maximum major strain and thinning rate of the bulged specimen under ETEF conditions were significantly reduced when compared to the quasi-static specimen with the same bulging height, and the specimen’s deformation uniformity and strain distribution were improved. The simulation results showed that the addition of energetic materials significantly improved the plastic strain energy of the blank. The deformation of the blank in ETEF can be divided into two stages: the initial chemical energy action stage and the inertia action stage. The bulging height of sheet metal increased by nearly 301% in inertia action stage, accounting for 80% of the total deformation time, and the effective plastic strain distribution was more uniform.

Enhancing laser-based contacting of aluminum current collector foils for the production of lithium-ion batteries using a nanosecond pulsed fiber laser

Cost reduction is a major aim for innovations in lithium-ion battery production. A promising approach to meet the high economic requirements is using high-speed manufacturing technologies like laser beam welding. This process can be applied to electrically connect the pre-stacked electrode sheets at the uncoated part of the current collectors. However, laser beam welding of the aluminum current collector foils is particularly challenging due to emerging seam defects such as cracks.In order to eliminate cracks occurring between the seam and the base material, this paper presents investigations on joining aluminum foil stacks using a nanosecond pulsed laser. Forty aluminum foils were welded with an arrester tab in a lap joint. This work examined the influence of several process parameters on the seam characteristics. A detachment of the seam from the foils was prevented, and promising results regarding the mechanical and electrical seam properties were achieved.

High speed manufacturing of aluminum alloy 7075 tubing by Shear Assisted Processing and Extrusion (ShAPE)

Shear assisted processing and extrusion (ShAPE) was used to extrude aluminum alloy 7075 tubing at speeds up to 12.2 m/min without surface tearing. This work presents the first experimental evidence for high-speed extrusion of 7075, which improves upon conventional extrusion where 2.0 m/min is the limit. The increased speed is primarily attributed to more extensive shear deformation, compared to conventional extrusion, which results in a high density of low angle grain boundaries that facilitate continued deformation and delay the onset of surface tearing. Mechanical testing after heat treating to the T6 condition provided an ultimate tensile strength of 565.3 ± 4.6 MPa, yield strength of 495.7 ± 8.7 MPa, and elongation of 16.4 ± 1.0%. Strength values exceed the ASTM International minimum standard and are on par with American Society for Metals (ASM) typical values, while elongation was substantially improved compared to 7 and 11% for the ASTM and ASM values respectively. It was observed that low temperature extrusion at 341 °C and 40 rpm gave superior material properties in the T6 condition compared to high temperature extrusion at 441 °C and 120 rpm because of variances in nanoscale second phase size and distribution.

Towards using convolutional neural network to locate, identify and size defects in phased array ultrasonic testing

Machine learning algorithms are widely used in image recognition. In Phased Array Ultrasonic Testing (PAUT), images are typically formed through constructive and destructive superpositions of signals backscattered from flaws or geometric features. However, all PAUT data acquisition schemes require several emissions and the duration of the acquisition may be too slow in high-speed manufacturing. In this study, the Faster R-CNN was used to identify, locate and size flat bottom holes (FBH) and side-drilled holes (SDH) in an immersed test specimen using a single plane wave insonification. The training was performed on segmented and classified data generated using GPU-accelerated finite element simulations. SDH and FBH of different diameters, depths and lateral positions were included in the training set. The thickness of the test specimen was also variable. An ultrasonic phased array probe of 64 elements was simulated. All elements of the phased array probe were fired at the same time and the time traces from each element were recorded. The individual time traces were concatenated to form a matrix, which was then used in the training. This inspection scenario enables fast acquisition of data at the expense of poor lateral resolution in the resulting image. The trained neural network was initially tested using finite element simulations. Results were assessed in terms of the intersection of the union (IoU) between the ground truth geometry and the predicted geometry. With the simulated cases, the thickness of the test specimen was detected in all cases. When using a 40% IoU threshold, the detection rate of the FBH was 87% while only 20% for the SDH. The smallest detected FBH had a 0.56 wavelength depth and a lateral extent of 1.04 wavelength. Drawing a box using the −6dB drop method around the FBH always led to an IoU under 15%. On average, the lateral extent of the FBH using the −6dB method was three times larger than the diameter predicted by the proposed method. Then, the training was continued with a small augmented dataset of experiments (equivalent to 3% of the simulated dataset). In experiments, the results show that the test specimen was always correctly identified. When using a 40% IoU threshold the experimental detection rate of the FBH was 70%. The smallest detected defect in experiments had a depth of 2 wavelengths.

Optimization of laser-assisted jet electrochemical machining parameters by grey relational analysis and fuzzy logic

PurposeThe purpose of this paper is to optimize the laser-assisted jet electrochemical machining parameters, namely, supply voltage, inter-electrode gap, duty cycle and electrolyte concentration during machining of WC-Co composite using grey relational analysis and fuzzy logic.Design/methodology/approachIn this work, experiments were carried out as per the Taguchi methodology and an L16 orthogonal array was used to study the influence of various combinations of process parameters on material removal rate, hole taper angle and surface roughness height. As a dynamic approach, the multiple response optimization was carried out using grey relational analysis and fuzzy logic.FindingsThe process parameters were optimized using grey relational analysis and fuzzy logic for different machining conditions such as balanced manufacturing, high-speed manufacturing and high-quality manufacturing. The research documented in this paper can be scaled up for case studies regarding industrial applications to compare optimization methods for manufacturing processes that are already being carried out.Originality/valueAn attempt to optimize material removal rate, hole taper angle and surface roughness height together by a combined approach of grey relational analysis and fuzzy logic has not been previously done.

Indium tin oxide nanowires manufactured via printing and laser irradiation

Metallic and semiconductor nanowires can provide dramatically increased electrical and optical properties in a wide range of fields, ranging from photovoltaics to sensors and catalysts. In this research, a rapid manufacturing process has been developed for printing indium tin oxide microparticles and converting them into nanowires. Microparticle indium tin oxide (ITO) inks were formulated and printed. These were then converted into hierarchical nanowire films via laser irradiation (980 nm, NIR) with raster speeds of 40 mm s−1 in air, much faster compared to traditional manufacturing processes. For a 4 cm2 film, only 40 s of processing were required. A full materials characterization was performed on the materials pre and post laser processing with the most probable conversion mechanism found to be a laser induced carbothermal reduction process. Microstructural, chemical, and crystallographic evidence of the laser induced carbothermal reduction process were derived from SEM, XRD, XPS and TEM analysis. Compared to conventionally heat-treated printed samples, laser processing was found to increase the conductivity of the printed ITO from 0.88% to 40.47% bulk conductivity. This research demonstrates the ability of printing and laser processing to form nanowires in a high-speed manufacturing context, thereby enabling the development of printed non-transparent ITO nanowire electronics and devices.

Enhanced Light Outcoupling in Organic Light-Emitting Diodes Using Phase Separated Polymer Films

We report high performance internal light outcoupling films based on phase separation polymer for indium tin oxide-free organic light emitting diodes (OLEDs). The two immiscible polymers of poly(amic acid) and polyimide in a blend film result in nanoporous structures after spin-coating by self-assembly process. The OLEDs are prepared by solution process including phase separation films and transparent electrodes, allowing for low-cost and high-speed manufacturing. The phase separation films prepared between the glass substrate and the poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) transparent electrode remarkably improve the outcoupling performance of OLEDs. The poly(methyl methacrylate) (PMMA)-assisted phase separation films significantly improve the external quantum efficiency and power efficiency of OLEDs by a factor 1.88 and 1.87, respectively, compared to the reference device without any outcoupling structure. Our results demonstrate that phase separation films developed here offer new opportunities in improving the outcoupling efficiency in OLEDs.

Reliability Testing of 3D-Printed Polyamide Actuators

3D printing is a rapidly emerging low-cost, high-yield, and high-speed manufacturing technique that has already been utilized in fabricating sensor and actuator devices. Here we investigate the cyclic fatigue and the effect of heating on 10 $\times$ 10 mm2-sized, 3D-printed polyamide-based laser scanning electromagnetic actuators, which are intended for integration with miniaturized laser-scanning imagers to yield a wide variety of optical imaging modalities. The tested actuators offer compact sizes and high-scan angles, comparable to their MEMS counterparts. We have tested N = 15 devices, at 5 different total optical scan angles between 40° - 80°, and observed their lifetimes (up to 108 cycles ≈ 10 days each), as well as the variability in their scan angle and mechanical resonance. A selected scanner was also tested under increased temperature conditions up to 60 °C for 10 hours, showing no sign of fatigue when returned to room temperature. Overall, it is concluded that 3D printed polymeric actuators are promising low-cost alternatives for short-term use in disposable opto-medical imaging units.

Determining key parameters of continuous wet granulation for tablet quality and productivity: A case in ethenzamide.

This paper aims to determine key parameters that affect tablet quality and productivity in continuous tablet manufacturing. Experiments were performed based on design of experiments using a continuous high-shear granulator and ethenzamide as the active pharmaceutical ingredient. To guide a systematic and comprehensive parameter analysis, a parameter framework was defined that comprised five input parameters on raw material properties and process parameters, 11 intermediate parameters on granule properties, and 11 output parameters on tablet quality and productivity. The interrelationships were analyzed statistically and were described as matrix functions. The liquid/solid ratio was the key parameter that affected circularity, density, and flowability as the granule properties, and disintegration and dissolution as the tablet quality. The maximum acceptable manufacturing rate that governs productivity was also affected by the liquid/solid ratio. Circularity was found to affect disintegration and dissolution. This result was specific to the setup of the study, but suggested development opportunities for a new process analytical technology system/quality-by-design application based on circularity. In addition, practical findings were obtained as follows: (1) high-speed manufacturing favored a lower liquid/solid ratio, and (2) high circularity slowed down disintegration/dissolution. This obtained knowledge will enhance the applicability of continuous technology in an actual manufacturing environment.

HIGH-SPEED LOCOMOTIVE XBOM ONTOLOGY MODELING RESEARCH SUPPORTING MRO SEMANTIC KNOWLEDGE REPRESENTATION

The new trends of high-speed rail locomotive manufacturing set higher requirement for MRO knowledge representation and XBOM. Therefore, XBOM ontology modeling supporting MRO semantic knowledge representation has become an important research topic of the high speed railway locomotive manufacturing industry. This paper firstly expounds the model frame of high-speed locomotive XBOM ontology, then take the global ontology, the construction ontology and the maintenance plan ontology as examples; respectively carding and analyzing four approaches each ontology contains that class (concept), object, data attribute, and constraint rule and central with the supporting MRO semantic knowledge representation, the XBOM ontology conceptual model can be created; At last, High speed rail train MRO semantic knowledge representation was realized by using protégé4.1 ontology modeling of XBOM for high-speed locomotive

Periodic folding of a falling viscoelastic sheet.

A viscoelastic solid sheet fed from a certain height towards a rigid horizontal plane folds on itself provided that there is no slip. This phenomenon commonly occurs in the manufacturing process of textile and paper products. In this paper we apply a particle dynamics model to investigate this phenomenon. At a low feeding velocity and low viscosity, the inertial effect and the viscous dissipation within the sheet are negligible, and our model successfully reproduces the existing quasistatic results in the gravitational regime. As the feeding velocity and the viscosity of the sheet increase, the folding process changes significantly. The length of the folds decrease and the "rolling back" motion of the sheet vanishes. In the inertial regime, a scaling law between the fold length and the feeding velocity is derived by balancing the kinetic energy and the elastic bending energy involved in folding, which is verified by the simulation. It is found that above a critical feeding velocity, the folding morphology transforms from line contact into point contact with the sheet exhibiting a lemniscate-like pattern. Finally, a phase diagram for the folding morphology is constructed. The results presented in this work may offer some insights into the high-speed manufacturing of paper and fabric sheets.

Regressive Event-Tracker: A Causal Prediction Modelling of Degradation in High Speed Manufacturing

The proposed work describes a dynamic regression based event-tracker for high speed production process. The methodology discussed is a causal system and provides trends and estimations of the sensors based on a flexible regression model of the historical sensor values. A safety threshold is defined that provides a boundary of the tolerant working for the regime condition of production. This threshold is used as a reference to calculate the remaining useful life of the critical component. The estimated remaining useful life is compared with the Weibull reliability analysis. The proposed methodology provides a remaining useful life of ∼ 10 weeks for the thermal regulator use-case when compared to ∼ 9 weeks for Weibull analysis. The overestimation of the methodology is discussed and along with the alternative methodology. The sensitivity analysis is conducted on the noise and training periods are studied for better prediction.

Investigation of process-affected zone in ultrasonic embossing of microchannels on thermoplastic substrates

In this paper, the process-affected zone in ultrasonically embossed thermoplastic substrates is investigated both numerically and experimentally. Commercialization of microfluidic devices challenges the need for high-speed manufacturing of plastic chips. Ultrasonic embossing is considered as an alternative method since the cycle time can be as low as a few seconds per chip while keeping the cost relatively low. To examine the ultrasonic embossing process, experiments were carried out to replicate 200 μm wide and 150 μm high straight channels on 3 mm thick polymethylmethacrylate (PMMA) substrates. The mold was fabricated by milling on aluminum. The features could be embossed by applying an 85 N static force at 28 kHz ultrasonic vibration and 10 μm amplitude for 5 s at room temperature with replication rates of 99.5 % and 100 % for the width and the depth, respectively. During the experiments, a clearly visible process-affected zone typically bounded by a half-circle with the center at the channel axis was observed. It was proven that the process-affected zone was bounded by the isothermal surface at the glass transition temperature of the substrate material (107 °C), both numerically and experimentally. It was also shown that the composition of the substrate material remains unaffected within the process-affected zone.