Dimensional Surface Research Articles

Performance Analysis of FFF-Printed Carbon Fiber Composites Subjected to Different Annealing Methods

Annealing is a popular post-process used to enhance the performance of parts made by fused filament fabrication. In this work, four different carbon-fiber-based composites were subjected to two different annealing methods to compare their effectiveness in terms of dimensional stability, surface roughness, tensile strength, hardness, and flexural strength. The four materials include PLA-CF, PAHT-CF, PETG-CF, and ABS-CF. The annealing methods involved heating the printed composites inside an oven in two different ways: placed on a tray and fluidized bed annealing with sharp sand. Annealing was conducted for a one-hour time interval at different annealing temperatures selected as per the glass transition temperatures of the four materials. The results showed that oven annealing provides better results under all scenarios except dimensional stability. PETG-CF and ABS-CF composites were significantly affected by oven annealing with expansion along the z-axis as high 8.42% and 18% being observed for PETG-CF and ABS-CF, respectively. Oven annealing showed better surface finish due to controlled and uniform heating, whereas the abrasive nature of sand and contact with sand grains caused inconsistencies on the surface of the composites. Sand annealing showed comparable hardness values to oven annealing. For tensile and flexural testing, sand annealing showed consistent values for all cases but lower than those obtained by oven annealing. However, oven annealing values started to decrease at elevated temperatures for PETG-CF and ABS-CF. This work offers a valuable comparison by highlighting the limitations of conventional oven annealing in achieving dimensional stability. It provides insights that can be leveraged to fine-tune designs for optimal results when working with different FFF-printed carbon-fiber-based composites, ensuring better accuracy and performance across various applications.

To investigate the effect of discharge energy and addition of nano-powder on processing of micro slots using EDM assisted µ-milling operation

ABSTRACT Micro-electric Discharge-Milling (µ-ED-M) is a non-contact process that uses an electrical spark to remove the material from a submerged workpiece with an electrode in a dielectric. The present paper focuses on optimizing process energizing (Capacitor, Voltage) and process stabilizing (Tool Travel Speed, Nano-Powder) parameters for controlling the size and surface characteristics of micro-crater. The present work focuses on the effect of nano-powder concerning dimensional aspects and surface characteristics at high and low capacitance levels. A µ-slot has been generated on the copper material by a tungsten carbide electrode. The experimentation is performed with two capacitor levels and three voltage and tool travel speed levels using full factorial design technique using with and without mixing of nano-powder in dielectric. The desirability functional multi-objective optimization approach is used to analyze the MRR, TWR, Width, and Depth. Field emission scanning electron microscopy (FESEM), non-contact optical profilometer, and x-ray diffraction (XRD) techniques are used to analyze the surface morphology of machined surfaces. The ANOVA is used to optimize the results; at low discharge energy, tool travel speed contributes 41% and promotes a higher thickness of recast layer 12.7 µm, whereas high discharge energy and nano-powder concentration contribute approx.—36% with 8.56 µm of recast layer.

Processing Parameter Setting Procedure for a Commercial Bowden Tube FDM Printer

Additive manufacturing (AM), especially fused deposition modeling (FDM), has experienced great development and diffusion during recent years. However, it still faces some limitations, such as poor dimensional accuracy or surface defects, the improvement of which motivates the elaboration of the present work. Contrary to an approach based on the optimization of parameters to obtain a single invariant value, the main objective of this study is the design of a procedure that anyone can follow to generate a printing profile for their specific FDM printer, environment, and imposed constraints through the adjustment of some selected parameters in the popular slicing software UltiMaker Cura. The resulting procedure consists of four ad hoc designed specimens and their analysis algorithms, all connected by a general workflow that ensures the correct execution of the procedure. Its applicability and effectiveness have been proved in a case study where a printing profile was developed for the real manufacturing project of a custom 3D object in polylactic acid (PLA), obtaining an improvement of 50% in tolerances and proving that the proposed parameter setting procedure represents a reduction in the setting time and material consumption versus conventional trial and error methodologies.

Comparative analysis of the wear behaviour of TiN/TiAlN, TiAlVN, and TiAlYN coated tools in milling operations of Inconel 718

Abstract Milling is widely used in the aeronautical and aerospace industries, due to the possibility of producing parts with good dimensional stability and surface quality. Because of its exceptional mechanical qualities and limited thermal conductivity, Inconel 718 is a nickel superalloy that is regarded as a challenging material to process. Due to the flexibility of milling, this is the most commonly used process for machining INCONEL alloys. However, high levels of tool wear can be observed. Coatings can be deposited on the cutting tools to improve process performance. Nonetheless, doping elements such as yttrium and vanadium when added to TiAlN-based coatings can increase the coating's resistance. Furthermore, multilayer coatings tend to be very promising resistance to crack propagation. Thus, this work intends to compare three coatings deposited via PVD, in terms of the quality of the machined surface and wear resulting from the process: TiAlVN, TiAlYN, and TiN/TiAlN. The cutting speed (Vc), feed per tooth (fz), and cutting length (Lcut) were varied. It was possible to verify that the multilayer coating had better results, in terms of average roughness (Ra) and in measuring wear (VB3) and its characterisation. On the other hand, the TiAlVN coating showed the worst results. It was concluded that due to the TiN layer, the TiN/TiAlN coating has better resistance to crack propagation, as its adhesion to the substrate is good and there is no delamination.

A scenario–neutral approach to climate change in glacier mass balance modeling

Abstract Scenario–neutral methods are commonly used to rapidly compare system responses to changes in climate. Using glacier mass balance as a system response, we present a bottom-up, scenario–neutral method as an effective tool for preliminary and overview studies on glacier sensitivity and a complementary approach to traditional top–down methods. The method's main characteristic is its visual result: two–dimensional response surfaces depicting glacier mass balance. Their axes represent perturbations in temperature and precipitation relative to a baseline. The simplicity of our approach makes it applicable to all global glaciers. As a proof–of–concept, the Open Global Glacier Model (OGGM) is used to perform a scenario–neutral glacier sensitivity analysis for four glaciers. In addition, the integration with a top–down approach is demonstrated by overlaying temperature and precipitation from four Coupled Model Intercomparison Project Phase 6 (CMIP6) models, under four Shared Socioeconomic Pathways (SSP). Finally, the benefits of the method are discussed for decision–making and science communication. Assessing results shows that overall, this scenario–neutral method can provide useful information for the research of climate change impact on glacier mass, from aiding study design to science communication.

Experimental investigation of FDM manufacturing of 316 l stainless steel

Continuous research in the field of metal additive manufacturing has led to the need for constant improvement of manufacturing parameters especially in the case of FDM (Fused Deposition Modeling) manufacturing. In recent years, the main directions outlined for productivity and quality improvement were related to higher printing speed and the use of ironing-type processes. This article aims to study the manufacturing parameters of the dimensional accuracy and surface quality of FDM-manufactured 316L stainless steel. The degree of novelty is given by the application of the ironing process for the green part. A full factorial 33 experimental design was designed for this study, in which the factors studied were ironing angle, ironing speed, and layer spacing during ironing. The dimensional accuracy and surface roughness were analyzed by means of deviation measurement from CAD to the green part and final part after the sintering process. Using the design of experiments offers the possibility of applying the analysis of variance (ANOVA) which provides information about the degree of influence of each of the studied factors. The results obtained for the dimensional accuracy showed that the ironing direction had the biggest influence on the Z-axis shrinkage. Overall, approximately 6% shrinkage in the Z and Y directions was obtained while in the X directions, the shrinkage percentage was around 20%. Surface roughness showed an improvement with higher ironing speeds for the green part while for the sintered part the most significant factor was ironing spacing.

Development of an Additively Manufactured Stationary Diffusion System for a Research Aeroengine Centrifugal Compressor

Abstract This paper introduces the next generation of the Centrifugal Stage for Aerodynamic Research (CSTAR) facility at the Purdue University Compressor Research Lab. The research centrifugal compressor is designed with an additively manufactured stationary diffusion system which comprises a vaned diffuser, a turn-to-axial bend, and deswirler vanes. The dimensional accuracy and surface finish of the diffusion system has allowed for rapid prototyping of several iterative diffusion system designs and has allowed for configuration of in situ pressure and temperature measurements to experimentally evaluate the aerodynamics and performance of centrifugal compressor diffusion systems. The diffusion system is manufactured from a commercially available stereolithography (SLA) resin, and the design of the parts is adapted to the constraints imposed by current technological and material limits of resin 3D printing. The implementation of additive manufacturing in the prototyping of the diffusion system has allowed for decreased cost and lead time while allowing rapid turnaround to generate experimental data. Performance data have verified the repeatability and temperature independence of the additively manufactured diffusion system through several design iterations. A survey of candidate materials for additively manufacturing these parts is also presented, and the tradeoffs of their material properties are discussed.

Effect of tool orientation on surface roughness and dimensional accuracy in ball end milling of thin-walled blades

AbstractIn the aerospace industry, high-precision components like impellers and blisks present considerable challenges in machining due to their intricate geometries and the need for reliable performance. Blades, often classified as thin-walled parts with complex, free-form surfaces, are crucial in ensuring the efficiency and safety of aircraft engines. Their geometries and materials require strict control over cutting parameters, such as tool path and orientation, to avoid deformation and maintain surface integrity. This study investigates the impact of tilt angle variation during ball end milling of Ti6Al4V thin-walled parts. Four different tilt angles (15°, 30°, 45°, and 60°) were analysed to evaluate their effect on dimensional accuracy and surface roughness. The results show that tilt angle significantly influences surface quality and dimensional precision. A tilt angle of 30° achieved the best balance between surface finish and dimensional tolerances, with flatness values ranging from 0.038 mm at 30° to 0.101 mm at 60°, representing a 152.5% increase in flatness. The findings provide practical guidelines for optimizing ball end milling of thin-walled components, emphasizing the importance of tool orientation in reducing deformation and enhancing surface quality.

Impact of Surface Finishing on Ti6Al4V Voronoi Additively Manufactured Structures: Morphology, Dimensional Deviation, and Mechanical Behavior

Additively manufactured medical devices require proper surface finishing before their use to remove partially adhered particles and provide adequate surface roughness. The literature widely investigates regular lattice structures—mainly scaffolds with small pores to enhance osseointegration; however, only a few studies have addressed the impact of surface finishing on the dimensional deviation and the global and local mechanical responses of lattice samples. Therefore, the current research investigates the impact of biomedical surface finishing (i.e., corundum sandblasting and zirconia sandblasting) on Voronoi lattice structures produced by laser powder bed fusion (LPBF) with large pores and different thicknesses on the surface morphology and global and local mechanical behaviors. MicroCT and SEM are performed for the assessment of dimensional mismatch and surface evaluation. The mechanical properties are investigated with 2D digital image correlation (DIC) in quasi-static compression tests to estimate the impact of surface finishes on local maps of strain. In the quasi-static tests, both the global mechanical performances, as expected, and local 2D DIC strain maps were mainly affected by the strut thickness, and the impact of different surface finishings was irrelevant; on the contrary, different surface finishing processes led to differences in the dimensional deviation depending on the strut thickness. These results are relevant for designing lattice structures with thin struts that are integrated into medical prostheses that undergo AM.

Enhancing the machinability and formability of tool steels through spheroidizing annealing heat treatment

This research focuses on enhancing the machinability and formability of tool steels by applying different heat treatment scenarios. Machinability is the process of cutting metals with the least energy effort, while formability is the ability of a metal to be shaped into different forms without severe damage. Enhancing machinability and formability improves dimensional tolerance and surface finish and increases the lifetime and reliability of tool steels. This research will use two tool steel materials, “D2” and “O1,” which are widely used in industry. They contain high percentages of carbon by weight (1.55% and 0.95%, respectively). The “O1” tool steel is used in blanking dies and room-temperature cutting tools, whereas the “D2” tool steel is used for carpentry cutting tools and gauges. The different heat treatment scenarios are based on the latest literature, which shows excellent results with other materials. The heat treatment plan is set to cover various scenarios to determine the most effective treatment for machinability and formability. The experimental work will include several mechanical tests: tensile tests, compression tests, hardness tests, and toughness tests. The conclusions regarding the different heat treatments will be based on the test results.

Deep learning of 3D point clouds for detecting geometric defects in gears

Geometric integrity directly impacts the functionality, reliability, and safety of final manufactured products, making the qualification of parts based on measurements of their geometry a fundamental quality control activity in modern manufacturing. Recent advancements in three-dimensional (3D) metrology technologies have enabled fine-scale inspection of geometric integrity characterized by dimensional accuracy, surface quality, and shape conformity. However, the widespread adoption of high-resolution 3D metrology in manufacturing faces some significant challenges posed by the inherent data structures of 3D point clouds such as high dimensionality, unstructured nature, and sparsity in defective regions. To address these challenges, this paper first creates a “MFGNet-gear” dataset, which is a scalable and comprehensive benchmark dataset comprising 12 part designs with four quality classes for each design. Subsequently, we develop a deep learning model adapted from the PointNet++ architecture to enable automated, end-to-end analysis of 3D point clouds. The model can be configured for different decision-making tasks including part design classification and multi-class geometric defect detection. Implementations of the proposed model on the “MFGNet-gear” dataset achieve accuracies up to 100% in classifying gear designs and up to 85% in four-class quality inspection. Additionally, we systematically investigate the impacts of measurement resolution and precision on the classification performance through a series of case studies. The obtained results highlight the potential of using deep learning methods for automated analysis of 3D point clouds for a variety of quality control tasks beyond gear manufacturing. This study also proposes future research directions, including the development of new deep learning architectures specifically designed for manufacturing 3D point clouds and strategies for adaptive measurement planning.

Novel processing of micro-channels in micro-grinding with automated laser-assistance

AbstractMicro-structures are widely utilized in various fields such as optical, medical, defense, and aerospace. The accuracy and performance of micro-structures depend on fabrication methods, including conventional and non-conventional machining. High-quality micro-channel fabrication is challenging by conventional micro-grinding (CMG) which uses a micro-pencil grinding tool during micro-machining. However, in CMG, high-cutting forces act in the machining zone leading to tool deflection, tool failure, high temperature, and poor surface finish. The challenges of CMG can be overcome by using automated laser-assisted micro-grinding (LAMG), one of the modern micro-machining processes for fabricating high-quality, precise micro-channels. The novel processing of micro-channels in this work is through the in tandem use of LAMG and CMG. In this, the laser structuring is performed using LAMG followed by a micro-pencil grinding tool processing in a sequential manner on a same machine tool to achive high-quality parts and accuracy. This helps in fabrication of a micro-channel directly in one go without the need to remove the part to perform the two operations on two different machining setups, thereby reducing systematic fixturing errors which are significant when we are working at the micro-scale. This paper thus investigates the effect of various parameters viz. laser input energy densities and laser power on cutting forces and surface roughness on the tool as well as the work surface with two distinct scan patterns. In LAMG, at lower laser input energy density (pattern 1), the tangential and normal forces decreased by 10.3% and 20.5%, and surface roughness Sa and Sq reduced by 24% and 22% compared to CMG. Similarly, a normal force decreased by 20.5% in pattern 1 and 38% less in pattern 2. Still, the higher laser energy density (pattern 2) is unsuitable for structure due to an increase in Sa and Sq by 11% and 14.6%, respectively. Results have shown a maximum reduction in the normal and tangential force magnitude by 31 and 44% at 25 W compared to CMG. The work concludes that LAMG with novel laser assistance scan patterns has lower dynamic deflections resulting in better dimensional accuracy and surface finish compared to CMG with a lower tool.

Design, Fabrication, and Commissioning of Transonic Linear Cascade for Micro-Shock Wave Analysis

Understanding shock wave behavior in supersonic flow environments is critical for optimizing the aerodynamic performance of turbomachinery components. This study introduces a novel transonic linear cascade design, focusing on advanced blade manufacturing and experimental validation. Blades were 3D-printed using Inconel 625, enabling tight control over the geometry and surface quality, which were verified through extensive dimensional accuracy assessments and surface finish quality checks using coordinate measuring machines (CMMs). Numerical simulations were performed using Ansys CFX with an implicit pressure-based solver and high-order numerical schemes to accurately model the shock wave phenomena. To validate the simulations, experimental tests were conducted using Schlieren visualization, ensuring high fidelity in capturing the shock wave dynamics. A custom-designed test rig was commissioned to replicate the specific requirements of the cascade, enabling stable and repeatable testing conditions. Experiments were conducted at three different inlet pressures (0.7-bar, 0.8-bar, and 0.9-bar gauges) at a constant temperature of 21 °C. Results indicated that the shock wave intensity and position are highly sensitive to the inlet pressure, with higher pressures producing more intense and extensive shock waves. While the numerical simulations aligned broadly with the experimental observations, discrepancies at finer flow scales suggest the need for the further refinement of the computational models to capture detailed flow phenomena accurately.

Evaluation of dimensional accuracy and surface roughness of lingual bracket slot –An in vitro study

The paradigm shift with the increasing number of adults and teens seeking aesthetic options for orthodontic treatment led to the increased demand for lingual orthodontics. When it comes to size and slot dimensions, lingual brackets are very different from labial brackets.With the rise of lingual orthodontics in our everyday practice, it's more critical than ever for practitioners to understand these potential bracket size variations. The resistance to sliding mechanics can occur if the contact angle between the archwire and bracket increases, this creates the need for precise bracket slot dimension. The amount of friction varies proportionally to the accuracy of the dimensions and the roughness of the bracket slot.To evaluate the precision of commercially available orthodontic lingual bracket slots in inch dimensions with manufacturers’ published dimensions using a stereomicroscope and to compare the surface roughness of commercially available orthodontic lingual bracket slots using an atomic force microscope.Lingual brackets from four different manufacturers were taken for evaluation of slot dimensions. Twenty brackets of each manufacturer were randomly selected. Trinocular Stemi 2000 Stereo Zoom Microscope with Digital Camera (Carl Zeiss, Germany) was used for measurement of bracket slot dimensions. An atomic Force Microscope (AFM) (Nanoscope® IV Di digital instrument, California, USA) was used to evaluate the surface roughness of lingual bracket slots. Comparison of dimensions between mesial processes and comparison of dimensions between distal processes showed that the difference was only marginal with no significant statistic value. Statistically significant results proved that slot dimensions were not precise as per the manufacturer’s standards for given lingual brackets and were oversized for all bracket systems. Statistically insignificant results showed that the bracket systems were similar concerning the surface roughness of the bracket.The analyzed series of lingual bracket systems exhibited significant differences with manufacturers’ standards in slot dimension, which will clinically result in torque play. Lack of standardization of slot dimensions during the manufacturing process may be clinically associated with undesirable tooth positioning and movement; inferring that the bracket systems were similar concerning the surface roughness of the bracket slot.

Regulating emulsion properties through tannin acid-mediated gelatin/cellulose nanocrystal complexes: From low-oil emulsion to high internal phase emulsion gel for 3D printing

In this study, a stabilized low-oil emulsion and high internal phase emulsion gels (HIPE gels) integrated preparation method is proposed. Highly stable low-oil emulsions, prepared using tight ternary complexes formed by incorporating tannic acid (TA) into gelatin/cellulose nanocrystals (GLT/CNC) complexes mainly through strengthening hydrogen-bonding interaction. The subsequent heating-centrifugation process was used to enable the conversion of GLT/CNC/TA stabilized low-oil emulsions to stabilized HIPE gels, and systematically investigated the regulation of emulsion properties by TA concentrations. The ternary complexes formed by appropriate concentration of TA (0.6 %) can form stable low-oil emulsions with smallest average particle (36.1 ± 0.25 μm) size and best rheological properties, while the rheological properties of HIPE gels were similarly regulated by the TA concentration (0 %, 0.2 %, 0.6 %, 1.0 %, 1.2 %). Heating induced flocculation of low-oil emulsions without causing demulsification, allowed for the subsequent centrifugation to yield stable HIPE gels, significantly superior to the GLT/CNC/TA-stabilized HIPE gels prepared by conventional methods that typically exhibit thermal instability. TA effectively promoted the interfacial adsorption of GLT/CNC and tight stacking of oil droplets to build a more stable network structure in the continuous phase. HIPE gels with 0.6 % TA demonstrated excellent 3D printability with optimal dimensional resolution and surface quality, presenting a novel strategy for HIPE gel preparation and versatile emulsion applications.

An experimental study on the wear performance of 3D printed polylactic acid and carbon fiber reinforced polylactic acid parts: Effect of infill rate and water absorption time

AbstractRapid prototyping, also known as additive manufacturing, is a nascent technology that is gaining traction in the context of environmental concerns and waste reduction, as well as the growing trend towards customized design. The additive manufacturing method, which has applications in diverse fields such as aviation, architecture, biomedical and automotive engineering, has also begun to be utilized in the construction of yachts and yacht hulls within the maritime industry. In this experimental study, the influences of sea water on polylactic acid (PLA) and carbon fiber reinforced polylactic acid (PLA/CF) parts manufactured at different infill rates (20%, 60% and 100%) were investigated. The parts were exposed to sea water for three different periods (1, 5, and 10 days) and subsequently subjected to wear tests. The dimensional accuracy, surface roughness, hardness, water absorption, volume loss, and friction coefficient of parts were measured and calculated. Additionally, the worn surfaces of the parts were investigated using field emission scanning electron microscope (FESEM) images. The findings indicate that PLA and PLA/CF parts can be produced with high dimensional accuracy. Furthermore, it can be reported that the water absorption of PLA/CF parts increased, particularly with an increase in the infill rate, while the volume loss decreased. Obtained results indicate the necessity of optimizing the 3D printing parameters and the relationship between the ambient conditions and the wear performance of the 3D printed parts.Highlights 3D printing is a highly promising method for the production of polymer composites. A pioneering study into the effect of infill rate and water absorption on the wear performance. Coefficient of friction values of PLA and PLA/CF parts ranged between 0.37 and 0.75. PLA/CF mostly exhibited higher volume loss than PLA with water absorption. Volume loss declines with a raise in the infill rate from 20% to 100%.

Confinement Effects of Two-dimensional Surfaces on Water Adsorption and Dissociation over Pt(111).

It has been established that the confined space created by stacking a two dimensional (2D) surface atop a metal catalyst serves as a nano-reactor. According to recent research, when a graphene (Gr) overlayer encloses a Pt catalyst from above, the activation barrier for the water dissociation reaction, a process with major industrial significance, decreases. In order to investigate how the effect of confinement varies among different two-dimensional (2D) materials, we study the adsorption and dissociation barriers of water molecule on Pt(111) under graphene, hexagonal boron nitride (h-BN), and heptazine-based graphitic carbon nitride (g-C3N4) layers using density functional theory calculations. Our findings reveal that the strength of adsorption does not decrease consistently with a reduction in the height of the 2D overlayer. Furthermore, a smaller barrier is not always the consequence of poorer adsorption of the reactant. We also examine the effect of confinement on the shape of the reaction path, on the frequencies of vibrational modes, and on the rate constants derived using the harmonic transition state theory. Overall, all three of the 2D surfaces cause a decrease in barrier height and a weakening of adsorption, though to differing degrees due to a mix of mechanical, geometric and electronic variables.

Evaluation of Macro- and Micro-Geometry of Models Made of Photopolymer Resins Using the PolyJet Method.

Additive manufacturing (AM) techniques are among the fastest-growing technologies for producing even the most geometrically complex models. Unfortunately, the lack of development of metrology guidelines for these methods, related to dimensional and geometry accuracy and surface roughness, significantly limits the commercialization of finished products manufactured using these methods. This paper aims to evaluate the macro- and micro-geometry of models manufactured using the PolyJet method from three types of photopolymer resins: Digital ABS Plus, RGD 720, and Vero Clear. For this purpose, test parts were designed and then manufactured on an Object 350 Connex3 3D printer. The Atos II Triple Scan optical system and the InfiniteFocusG4 microscope were used to evaluate macro- and micro-geometry, respectively. For both systems, measurement procedures were developed to obtain statistical results for evaluating geometric accuracy and surface roughness parameters. In the case of macro-geometry, for Digital ABS Plus and Vero Clear materials, 50% of the central deviations (between first quartile Q1 and third quartile Q3) lie within the range (-0.06, 0.03 mm) and for RGD 720 material within the range (-0.08, 0.01 mm). For micro-geometry, the arithmetic mean height (Sa) values for the Digital ABS Plus and Vero Clear samples were approximately 1.6 and 2.0 µm, respectively, while for RGD 720, it was 15.9 µm. The total roughness height expressed by reduced peak height (Spk) + core height (Sk) + reduced dale depth (Svk) for the Digital ABS Plus and Vero Clear samples was approximately 9.1 and 10.5 µm, respectively, while for the RGD 720, it was 101.9 µm.

Dual-control of incubation effect for efficiently fabricating surface structures in fused silica

Abstract Fused silica with surface structures has potential applications in microfluidic, aerospace and other fields. To fabricate structures with high dimensional accuracy and surface quality is of paramount importance. However, it is indeed a challenge to strike a balance between accuracy and efficiency at the same time. Here, a temporally shaped femtosecond laser Bessel-beam-assisted etching method with dual-control of incubation effect is proposed to achieve this balance. Instead of layer-by-layer ablation continuously with Gaussian pulses, silica is modified discretely by double pulse Bessel beam with one single layer. During the modification process, incubation effect is dual-controlled in single shot process and spatial scanning process to generate even modified region efficiently. Then, the modified region is etched to form designed structures such as microholes, grooves, etc. The proposed method exhibits high efficiency for fabrication of surface structures in fused silica.

Neural-network-based trajectory error compensation for industrial robots with milling force disturbance

ABSTRACT Industrial robots are increasingly used in advanced manufacturing fields such as aerospace due to their high efficiency and low cost. In robotic machining applications, deviation of the tool centre point trajectory from the desired path due to load disturbances acting on the end-effector of an industrial robot can result in poor dimensional accuracy and surface quality of products. Therefore, improving robot trajectory accuracy under external load disturbances is extremely important. This study proposes an error compensation methodology using neural networks optimized by a hybrid marine predators-grid search algorithm to compensate for robot trajectory error. Two neural networks are developed: one for predicting load disturbances and the other for predicting trajectory errors in robotic machining. The milling experiment results show that the compensated robot trajectory errors in x, y, and z directions are reduced by 65%, 76%, and 77% respectively, which proves the effectiveness of this method in improving the robotic milling accuracy.