High-precision Manufacturing Research Articles

Effects of Build Direction and Heat Treatment on the Defect Characterization and Fatigue Properties of Laser Powder Bed Fusion Ti6Al4V

Laser powder bed fusion (LPBF) is one of the high-precision additive manufacturing techniques for producing complex 3D components. It is well known that defects appear in additive-manufactured parts, and they deeply affect the fatigue properties; even heat treatment is performed after printing. In order to meet the safe-life design requirements of additive-manufactured aircraft structures, the effects of build direction and heat treatment on defects and fatigue properties need to be quantified. Hence, Ti6Al4V alloy samples with different build directions were designed and printed by LPBF. X-ray computed tomography was used to quantitatively analyze the defect size, the sphericity, and the defect orientation. And their effects on fatigue properties were studied. An extended effective defect size and a defect-based fatigue anisotropy evaluation process are proposed to qualify the effects of the defect size, sphericity, and defect orientation. It is shown that the build direction can affect the porosity distribution and maximum defect size, while the annealing treatment can cause the coalescence of small defects and higher porosity. The defect orientation exhibited a fluctuating trend of 0°–90°–0°–90°–0° as the volume increased. The elongated lack of fusion defects related to the build direction was the main crack source and could lead to fatigue anisotropy of LPBF Ti6Al4V.

Experimental Study on Seismic Performance Evaluation of a Multi-Story Steel Building Model with Rolling-Type Seismic Base Isolation

Critical structures such as hospitals, high-precision manufacturing facilities, telecommunications centers, and fire stations, especially, need to maintain their functionality even during severe earthquakes. In this sense, seismic isolation technology serves as a vital design method for preserving their functionality. Seismic isolators, also known as earthquake isolation systems, are used to reduce the effects of earthquakes on buildings by isolating them from the ground they are located on. By ensuring that less acceleration and force demand is transmitted to the superstructure, both the building and the equipment and the devices in the building are prevented from being damaged by earthquakes. This experimental study aims to conduct vibration tests on a small-scale multi-story steel-building model equipped with a specially designed rolling-type seismic base isolation system. The relationship between the test model and the prototype was achieved by frequency simulation. The tests will be performed on a shake table under six different earthquake accelerations to examine the model’s dynamic behavior. The primary goal is to evaluate the isolation performance of the rolling-type seismic base isolator under seismic loads, with a focus on recording the vibrations at the top of the test building. It has been observed that the isolator placed at the base of the building significantly reduced the peak acceleration and displacement values of the floor motion. Under the most severe earthquake record applied to the shake table, the acceleration at the top of the building with the isolator was found to be reduced by approximately 50%, compared to the non-isolated case.

Preparation of ultrafine WC-V8C7-Cr3C2-co cemented carbides by spark plasma sintering in-situ synthesis of composite grain growth inhibitors

The growing high-precision manufacturing industry is increasing the demand for cemented carbide which has fine grain size and excellent machinability. In this research, ultrafine cemented carbide was successfully prepared by the method of in-situ synthesis using spark plasma sintering as densification method, V, Cr, WC and carbon black as raw materials. The formation mechanism of in-situ preparation of grain growth inhibitors (GGIs) and its influence on the properties of alloys were investigated. An excellent mechanical property (HV 2254 kgf/mm2, KIC 9.20 MPa·m1/2) and uniform microstructure of the alloys (0.8 wt% V8C7–0.8 wt% Cr3C2) prepared under 1350 °C, 6 min, 25 MPa were demonstrated by the results. The WC grain growth was significantly inhibited (about 200 nm). The in-situ synthesized GGIs significantly inhibited grain coarsening by interfering with the dissolution-precipitation process of WC during liquid-phase sintering. The combination of SPS and in-situ synthesized GGIs offers a novel approach to exploration of the preparation of high-performance ultrafine or nanocrystalline cemented carbides.

Kalman filter-driven state observer for thermal error compensation in machine tool digital twins

Sustainable reduction of thermal errors during production is the key challenge in modern high-precision manufacturing. Numerical compensation models provide an energy-efficient solution, but in the case of data-driven models, high-quality experimental data must be time-consuming and expensive to produce, negatively impacting overall productivity. Furthermore, robustness concerns arise in the case of new operating conditions, which were not contained in the training data. This paper presents a novel use of a Kalman filter together with model order reduced finite element models to observe the entire thermal state, which allows the subsequent solution of the mechanical model and computation of the thermal errors in real-time without requiring any training data but instead purely based on the physical system model. The effectiveness of this approach is evaluated using experiments on a thermal test bench with 16 out of 40 temperature sensors employed for observation and demonstrated on a 5-axis machine tool (MT) with 13 out of 25 temperature sensors used. Due to the combination of the reduced order model and Kalman filter these 13 temperature sensors are sufficient to represent a MT mesh of more than 350’000 elements. The entire temperature profile of the thermal test bench is reconstructed to achieve a root mean square error (RMSE) of the unobserved temperature sensors of only 2.7 °C, which accounts for more than 83% of all temperature variations and 1.3 °C for the 5-axis MT. For the thermal error of the thermal test bench, the RMSE could be reduced from 67.4μm to 33.3μm, corresponding to a reduction of 52.7 %. This could be achieved without the need for experimental data for model calibration, in a real-time capable physics-based model.

Harnessing interpretable and ensemble machine learning techniques for precision fabrication of aligned micro-fibers

Electrospinning is a robust technique for producing micro/nano-scale fibrous structures, influenced by intricate interplays of fluid dynamics, aerodynamics, and electromagnetic forces. Depending on the desired outcome, these fibers can adopt various morphologies, including solid, tubular, concentric, and gradient. Such morphologies are modulated by parameters such as collector configuration, flow rate, voltage, solution properties, and nozzle dimensions. However, the task of modeling and predicting these multifaceted morphologies remains complex. Aligned microfibers with 3D orientation hold promise in tissue engineering, regenerative medicine, and drug delivery, necessitating meticulous control over the fabrication parameters. In our research, we tapped into machine learning (ML) to address these challenges. Classification ML models were designed to predict fibrous patterns—aligned, random, or jet branching—based on determinants like voltage, flow rate, and collector configurations. Notably, the Random Forest (RF) and Support Vector Machine (SVM) models, especially with radial kernel-trick, displayed outstanding predictive capabilities on the test data. Furthermore, regression-based ML was harnessed to discern fiber alignment coherency and inter-fiber distances. Models such as Lasso and Ridge regression elucidated predictive coefficients for these characteristics, while ensemble models, like gradient-boosting (GB) decision trees (DT), showcased prowess in regression scenarios. Key findings spotlighted the significance of parameters like plate gap for alignment coherency and needle-to-collector distance for inter-fiber spacing. As we strive to gain granular control over micro/nano feature morphology in electrospinning, understanding predictor-response dynamics is imperative. Our investigation underscores the essential role of ML in enhancing both qualitative and quantitative precision in fabricating advanced fibrous structures. Moreover, fusing ML with real-time process monitoring offers groundbreaking potential, particularly in Bio-Fabrication, regenerative medicine, and tissue engineering, where high-precision manufacturing remains a top priority.

Effect of Al precursor’s properties on interactions with self-assembled monolayers for area selective deposition

Area selective deposition (ASD) is a high-precision atomic-level manufacturing technology that enables the development of bottom-up manufacturing methods in the future semiconductor field. The area selective deposition behavior of Al precursors on 1-octadecylthiol (ODT) passivated Cu/SiO2 surfaces was studied through experimental and theoretical analysis. The relationship between precursor steric hindrance, symmetry, penetration depth in ODT, and adsorption energy was elucidated. The loss of selectivity caused by different penetration depths of the precursor in ODT can be post-treated with acids or H2 plasma to remove the physisorption of precursor molecules between ODT chains, thereby improving the selectivity. Reliable ASD technology has been successfully applied to Cu/SiO2 patterns. Dimethylaluminum isopropoxide can selectively deposit about 10 nm of Al2O3 on SiO2 without detectable defects on the Cu area. This provides important insights into the choice of precursors in the ASD process and can extend its application to a wider range of device manufacturing schemes.

Biomimetic Contact Behavior Inspired Tactile Sensing Array with Programmable Microdomes Pattern by Scalable and Consistent Fabrication.

Flexible sensor arrays have attracted extensive attention in human-computer interaction. However, realizing high-performance sensor units with programmable properties, and expanding them to multi-pixel flexible arrays to maintain high sensing consistency is still struggling. Inspired by the contact behavior of octopus antenna, this paper proposes a programmable multistage dome structure-based flexible sensing array with robust sensing stability and high array consistency. The biomimetic multistage dome structure is pressurized to gradually contact the electrode to achieve high sensitivity and a large pressure range. By adjusting the arrangement of the multistage dome structure, the pressure range and sensitivity can be customized. More importantly, this biomimetic structure can be expanded to a multi-pixel sensor array at the wafer level with high consistency through scalable and high-precision imprinting technologies. In the imprinting process, the conductive layer is conformally embedded into the multistage dome structure to improve the stability (maintain stability over 22000 cycles). In addition, the braced isolation structure is designed to effectively improve the anti-crosstalk performance of the sensor array (crosstalk coefficient: 26.62dB). Benefitting from the programmable structural design and high-precision manufacturing process, the sensor array can be customized and is demonstrated to detect human musculation in medical rehabilitation applications.

Laser in-situ measurement in robotic machining of large-area complex parts

High-precision manufacturing of key components in aerospace plays a crucial role in determining their operational performance, and shape measurement during machining is essential for controlling component accuracy. This article proposes a laser in-situ high-precision measurement method based on improved ICP registration during robotic machining to resolve the contradiction between measurement accuracy and range. Firstly, a robotic in-situ measurement system based on line laser scanning is constructed. Subsequently, the FM-BiKD-ICP algorithm based on geometric feature matching and bi-directional KD-tree proposed in this article is used to complete the high-precision registration of multi-million-scale point cloud data of complex parts with large surface area. Finally, the standard ball target ruler is measured, with the RMSE is under 0.079 mm after multiple registrations, and the average error of hole center distance is less than 0.037 mm on large-area complex parts. These results indicate the high precision of the proposed robot in-situ measurement system.

Task-driven geometric synthesis method of a bistable compliant mechanism for the rigid guidance problem

Abstract. Compliant bistable mechanisms are specialized mechanisms that have specific self-locking characteristics in two positions. They are widely used in aerospace, micro-electromechanical systems, and high-precision manufacturing. The coupling of kinematic with elastomechanical behaviors of compliant mechanisms, known as kinetostatics, increases the difficulty of synthesizing compliant mechanisms. Currently, most research relies on optimization approaches to find compliant mechanisms that meet motion requirements. To address this challenge, this paper proposes a geometric synthesis method for compliant bistable mechanisms to solve the rigid guidance problem. The pole similarity transformation characteristics of planar beams and the static equilibrium characteristic of bistable mechanisms at stable positions are utilized to decouple the kinematic synthesis and static analysis. The proposed method introduces a task-driven synthesis process, where the critical structural parameters in compliant mechanisms are determined based on the desired guidance positions of motion tasks. This approach eliminates the need for a tedious and time-consuming iterative optimization process. The resulting bistable mechanisms have two stable positions that correspond to the desired guidance positions of the motion task. To illustrate the effectiveness of the geometric synthesis method, a two-position problem of a compliant bistable mechanism is provided as an example.

Size shrinkage and compressive behaviour of Al2O3 honeycomb structures fabricated via Digital Light Processing technology

Al2O3 ceramic have excellent chemical inertness, superior heat resistance, and excellent corrosion resistance, so they are considered ideal materials for manufacturing high-performance components such as thermal end devices in aerospace, heat dissipation panels in electronic communication, and exhaust filters in the automotive industry. Digital Light Processing (DLP) is a useful technology to fabricate complex Al2O3 ceramic components. However, the size shrinkage effect of DLP-fabricated components need to be investigated deeply before its further application. In this work, we utilized DLP technology to fabricate Al2O3 ceramic honeycomb structures and systematically investigated their microstructure, size shrinkage, and mechanical properties. Our findings revealed that the Al2O3 ceramic grains exhibit flake-like structures with an average diameter of 1–2 μm, and the ceramic particles are tightly bonded. The shrinkage rates in the X and Y axes were 7.54 % and 7.42 %, respectively, while the Z-axis exhibited a more significant shrinkage of 13.04 %. This anisotropic shrinkage in different direction was attributed to accumulation of the interlayer bonding under gravity action during debinding and sintering process. The compressive stress-strain curve of the honeycomb structures demonstrated a typical brittle compressive behavior, including elastic, stress plateau, and brittle fracture stages. The honeycomb structures exhibited an elastic modulus of 54.49 ± 1.22 MPa and a compressive strength of 10.22 ± 0.42 MPa. The fracture analysis indicated that the fractures region of honeycomb structures initiated at the corners of the honeycomb structures, indicating their easy-broken compared to the walls. These findings provide valuable guidance for the high-precision and high-performance manufacturing of complex Al2O3 ceramic components.

Pose Selection Based on a Hybrid Observation Index for Robotic Accuracy Improvement

The problem of the insufficient accuracy performance of industrial robots in high-precision manufacturing is addressed in this paper. Firstly, a kinematic error model based on an M-DH model was presented. Secondly, a hybrid observability index O6 was proposed to select the optimal poses for parameter identification. O6 is the combination of O1 and O3. The optimal poses were obtained by using the IOOPS algorithm. Thirdly, the fitness function for parameter identification was established, and the Levenberg–Marquardt (LM) algorithm was applied for the accurate identification of kinematic parameter errors. Finally, several experiments were conducted to evaluate the performance of the proposed hybrid observability index O6. The average position error and average attitude error of Staubli TX60 robot were reduced by 89% and 49%. The results show that the proposed hybrid observability index O6 has great stability and effectiveness for robot calibration.

A Review of an Investigation of the Ultrafast Laser Processing of Brittle and Hard Materials.

Ultrafast laser technology has moved from ultrafast to ultra-strong due to the development of chirped pulse amplification technology. Ultrafast laser technology, such as femtosecond lasers and picosecond lasers, has quickly become a flexible tool for processing brittle and hard materials and complex micro-components, which are widely used in and developed for medical, aerospace, semiconductor applications and so on. However, the mechanisms of the interaction between an ultrafast laser and brittle and hard materials are still unclear. Meanwhile, the ultrafast laser processing of these materials is still a challenge. Additionally, highly efficient and high-precision manufacturing using ultrafast lasers needs to be developed. This review is focused on the common challenges and current status of the ultrafast laser processing of brittle and hard materials, such as nickel-based superalloys, thermal barrier ceramics, diamond, silicon dioxide, and silicon carbide composites. Firstly, different materials are distinguished according to their bandgap width, thermal conductivity and other characteristics in order to reveal the absorption mechanism of the laser energy during the ultrafast laser processing of brittle and hard materials. Secondly, the mechanism of laser energy transfer and transformation is investigated by analyzing the interaction between the photons and the electrons and ions in laser-induced plasma, as well as the interaction with the continuum of the materials. Thirdly, the relationship between key parameters and ultrafast laser processing quality is discussed. Finally, the methods for achieving highly efficient and high-precision manufacturing of complex three-dimensional micro-components are explored in detail.

Coating-assisted picosecond laser ablation for microstructure fabrication of SiC ceramics

Silicon carbide (SiC) ceramics have emerged as critical materials in the production of high-precision components. Ultrafast laser processing is deemed the optimal technique for micro-nano manufacturing of SiC. However, the permanent deposition layer induced by laser ablation can critically impact the precision of the component. In this work, a coating-assisted picosecond laser ablation (CAPLA) method was proposed, in which sacrificial photoresist coating was utilized to improve surface quality without efficiency loss. The coating serves to prevent the uncooled plasma from contacting with the substrate, thereby preventing the formation of a permanent deposition layer. By comparing the CAPLA method with laser direct ablation, the influence of laser parameters and photoresist coating characteristics on the deposition layer was investigated systematically. A processed surface devoid of deposition layers can be achieved by CAPLA with low pulse energy and a high number of scans. The uniformity is critical to ensure the transmission of the laser beam, and a larger thickness can improve the processing efficiency by increasing the limit of pulse energy capacity. Pin arrays and vacuum grooves for SiC ceramic vacuum chucks were fabricated to demonstrate the superiority of the CAPLA method. These results suggest that this method can be a novel and promising approach for high-precision component manufacturing.

High-precision and Large-Scale Vat Photopolymerization Printing based on "Spatial-Pixel Integration Compensation" method

Vat photopolymerization (VPP) is widely known for its exceptional printing accuracy, but effectively controlling stitching errors to achieve high-precision, large-scale printing remains a significant challenge. This study introduces a novel compensation method, termed "Spatial-Pixel Integration Compensation" (SPIC), to address this key obstacle. SPIC combines Spatial Motion Compensation to initially control stitching errors between adjacent sub-images to be within 100 µm and Pixel Compensation for precise adjustments, further reducing stitching errors. Integrating SPIC with our high-precision printing system resulted in a remarkable reduction of stitching errors by a factor exceeding 40. Crucially, this method minimizes the stitching error between any two sub-images to be less than one pixel point, specifically below 4 µm. Notably, SPIC is the first method specifically focused on effectively controlling and reducing stitching errors to achieve large-scale printing while maintaining high precision. To validate the practical applicability of the SPIC method, we used SPIC to print both Zig-Zag and herringbone structures (HBS) and achieved high-precision large-scale manufacturing with dimensions of 44 mm × 33 mm. In the HBS structure, the minimum feature size was 14.2 µm, and the printing error was less than 1 µm. These printed structures were used as molds to fabricate proof-of-concept polydimethylsiloxane (PDMS) microfluidic chips, demonstrating the successful mixing of rhodamine B and ethanol within the microfluidic channels. Furthermore, SPIC was extended to the printing of complex three-dimensional (3D) Triple-Periodic Minimal Surface (TPMS) structures, successfully producing TPMS-Gyroid and TPMS-Diamond structures with a minimum feature size of 20 µm and a printing error below 1.5 µm. These results demonstrate that the SPIC algorithm effectively enables high-precision, large-scale printing. This work significantly advances the application of VPP technology in fields requiring complex, high-precision, and large-scale 3D structures and provides valuable insights for future research in high-precision and large-scale printing.

The effects of electrolyte composition and deposition voltage on the copper-nickel alloy micropillars fabricated by Jet ECD

With the rapid development of micro electronic component technology, higher requirements are put forward for high performance and high precision manufacturing process. In this paper, copper-nickel alloy micropillars were manufactured by jet electrochemical deposition (Jet ECD) technology with high deposition rate, aiming to provide an effective material and process solution for the manufacture of micro-thermocouples and other components. By optimizing the process parameters such as electrolyte composition, pH value and deposition voltage, the homogeneous deposition of copper-nickel alloy micropillar was realized. The cross-section morphology and elementary composition of the deposition micropillars were characterized in detail by using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The results show that the adjusted formula and process parameters can stably manufacture copper-nickel alloy micropillars with a nickel-copper ratio (close to 0.8), and compact, void free microstructure.

Effects of laser power on microstructure and mechanical properties of titanium alloy fabricated by laser-arc hybrid additive manufacturing

Laser-arc hybrid additive manufacturing (LAHAM) based on the synergistic interaction of laser and arc has vast potential applications due to the advantages of high precision and fast manufacturing speed. Titanium alloy is a kind of indispensable material in the aerospace and marine industries because of its superior performance. This study primarily investigates the effect of laser power on formability, microstructure evolution, and mechanical properties of Ti-6Al-4V, a titanium alloy fabricated by LAHAM. The results indicate that the material utilization of the Ti-6Al-4V wire first increases and then decreases with the increasing laser power, reaching a maximum value of 95.48% at a power of 1500 W. As laser power increases, the acicular martensite α′ content in the LAHAM samples decreases, while the α phase increases and exhibits a coarsening phenomenon. Tensile strength increases with the rise in laser power, reaching a maximum horizontal tensile strength of 1080 MPa and a maximum vertical tensile strength of 1100 MPa. However, elongation decreases with increasing laser power. Microhardness decreases with the rise in laser power. The increase in laser power enhances the bonding between deposition layers, significantly improving the tensile strength of the specimens.

Chip breakage in silk microfibre production using elliptical vibration turning

To overcome the precision limitation and environmental impact of current chemical-based production methods for manufacturing silk microfibres used for targeted drug delivery, this paper presents a high-precision, scalable, eco-friendly mechanical machining approach to produce such microfibres in the form of discontinuous chips obtained through elliptical vibration turning of silk fibroin film using a diamond tool. The length and waist width of fabricated microfibres can be precisely controlled. As each vibration cycle will produce one silk microfibre, complete and deterministic chip breakage becomes an essential and challenging task in this approach due to its unique two-phase structure. Thus, the hybrid FE-SPH numerical simulations and machining experiments were conducted to gain a pioneering and in-depth exploration of the chip-breaking mechanism in this process. It was found that applying a low depth ratio (ratio of the nominal depth of cut to the tool path vertical amplitude) and a high horizontal speed ratio (the nominal cutting speed versus the critical workpiece velocity) could effectively reduce the average tool velocity angle (the angle from the deepest cut to the tool exit point along the cutting direction). A smaller angle would enhance the diamond tool's shearing action and led to the reduction of hydrostatic pressure in the cutting zone and a consequent decrease in the ductility of silk fibroin due to its unique structure dominated by beta-sheet crystallites. The above adjustments collectively facilitated chip breakage. This paper, therefore, established a governing rule for the controlled and repeatable formation of microfibres based on the average tool velocity angle for the first time and revealed that the cutting chips would undergo complete and deterministic breakages once the angle approached below 22.6°. On this basis, the high-precision and scalable manufacturing of silk microfibres with precisely controllable length and waist width was ultimately achieved.

Frequency mismatch analysis of hemispherical shell resonators with both radius and thickness imperfections

The hemispherical shell resonator (HSR) is the core element of the hemispherical resonator gyroscope (HRG), and its frequency mismatch is a key property influencing gyroscope accuracy. Investigating the mechanism of frequency mismatch is vital for improving the quality of HSRs and performance of HRGs. Midsurface radius imperfections and thickness imperfections are two principal causes of frequency mismatch, but their combined effects have rarely been discussed. This paper develops a model to comprehensively analyze the frequency mismatch of HSRs with both radius and thickness imperfections. The model derives a quantitative relation between the frequency mismatch and the two imperfections, and provides principles for evaluating dominant imperfections. To validate the model, we conduct experiments on a batch of 12 HSRs with random geometric imperfections. We apply the model in calculating the theoretical frequency mismatches of these HSRs, and the results agree well with the experimental data. The experiment also confirms that for macro-HSRs, thickness imperfections have a larger impact than radius imperfections, and the frequency mismatch is approximately linear to the fourth thickness harmonic. Our research can be a useful reference for the design and fabrication of HSRs and may open new possibilities for high-precision manufacture of HRGs.

3D-printed, citrate-based bioresorbable vascular scaffolds for coronary artery angioplasty

Fully bioresorbable vascular scaffolds (BVSs) aim to overcome the limitations of metallic drug-eluting stents (DESs). However, polymer-based BVSs, such as Abbott's Absorb, the only US FDA-approved BVS, have had limited use due to increased strut thickness (157 μm for Absorb), exacerbated tissue inflammation, and increased risk of major cardiac events leading to inferior clinical performance when compared to metallic DESs. Herein we report the development of a drug-eluting BVS (DE-BVS) through the innovative use of a photopolymerizable, citrate-based biomaterial and a high-precision additive manufacturing process. BVS with a clinically relevant strut thickness of 62 μm can be produced in a high-throughput manner, i.e. one BVS per minute, and controlled release of the anti-restenosis drug everolimus can be achieved by engineering the structure of polymer coatings to fabricate drug-eluting BVS. We achieved the successful deployment of BVSs and DE-BVSs in swine coronary arteries using a custom-built balloon catheter and BVS delivery system and confirmed BVS safety and efficacy regarding maintenance of vessel patency for 28 days, observing an inflammation profile for BVS and DE-BVS that was comparable to the commercial XIENCE™ DES (Abbott Vascular).

Minimum-cost ordering for selective assembly

We consider the minimization of input cost for a selective assembly system that features two random inputs and a finite number of matching classes. This setup frequently arises in high-precision manufacturing when input tolerances are not tight enough for the required output precision. We determine optimality conditions for the cost-optimal input portfolio given an expected-output target, first using a normal approximation of the multinomial binning distribution, and second employing a simple upper envelope of the output objective. We show that the relative error tends to zero as the production scale becomes sufficiently large. The envelope optimization problem also yields a closed-form solution for the cost-minimizing inputs as well as total costs, which are easy to understand for managers. A numerical study tests the practicality of the envelope approach. The latter can be used as seed for a numerical solution of the exact problem, as well as a closed-form approximation, which allows for an analysis of structural properties.