Kornel F. Ehmann

Conventional laser trepanning drilling (LTD) often produces microholes with excessive taper, high surface roughness, and thick recast layers, severely limiting its application in precision manufacturing. To address these limitations, this study proposes and systematically investigates ultrasonic vibration-assisted laser trepanning drilling (UVLTD). A combined experimental and multi-physics numerical approach is employed to elucidate the mechanisms by which ultrasonic vibration controls hole geometry and surface quality. Results obtained using 304 stainless steel as the substrate demonstrate that ultrasonic vibration induces periodic fluid disturbances and flow reversal within the molten pool, thereby significantly enhancing convective heat transfer and melt expulsion. This is evidenced by an 18 % increase in melt flow velocity and volumetric forces reaching 1.2 × 109 N/m3, which collectively suppress bottom overheating and resolidification. Compared to conventional LTD, UVLTD reduces hole taper by 12.1 %, surface roughness by 67 %, and recast layer thickness by 43.5 %. The developed numerical model demonstrates high accuracy, predicting hole geometry with errors of less than 10 %. Furthermore, comprehensive parametric studies confirm that UVLTD consistently yields larger hole diameters and smaller taper angles than LTD across a wide range of processing conditions, with the most pronounced advantages observed at high pulse frequencies and trepanning speeds. This work provides both a fundamental understanding and experimental validation of UVLTD as an effective strategy for high-quality microhole fabrication in precision manufacturing.

Abstract This study investigates the impact of surface texturing on the durability of slippery liquid-infused porous surface (SLIPS) coatings applied to sheet metal substrates by the double-sided incremental forming (DSIF) process. Toolmarks generated during the DSIF process were leveraged as an efficient method for texturing, enabling both the formation and texturing of surfaces using a single set of universal tools. The effects of texture patterns, spacing, and tool movement on the SLIPS performance were evaluated by comparing samples generated in the presence and absence of tool spinning/rotation. The results indicate that textures with dimple patterns significantly improve coating durability by acting as lubricant reservoirs, reducing oil depletion, and supporting self-healing. In contrast, continuous grooves were less effective due to limited capillary action and increased edge effects. Tool spinning further enhanced the surface topography, producing an undulating texture that minimized contact line pinning and improved the surface hydrophobicity. Low-speed spinning (approximately 10 rpm) facilitated a transition to mixed sliding–rolling friction, resulting in smoother textures and extended coating durability. Combining dimple patterns and controlled spinning provides a synergistic approach for optimizing SLIPS coatings, offering a practical solution for enhancing durability without requiring additional equipment. This study underscores the potential of controlled texturing and tool movement to improve the SLIPS efficacy and broaden its applications in industrial, clinical, and consumer environments.

This paper explores and identifies commonalities among recent Digital Twin (DT) technology definitions. additionally, it introduces a framework for a digital twin of Human-Robot Collaboration (HRC) focusing on English wheel manufacturing as its foundational context. To achieve this, two 3D simulators, namely Grasshopper and Rhino, were employed to faithfully replicate the English wheel process digitally. Subsequently, optimizing these simulators’ performance paved the way for a comprehensive visualization of the English wheel using the Microsoft HoloLens. This visualization integrates digital and physical interactions, resulting in a mixed reality environment. The ultimate goal of this research is to enable a bi-directional collaboration within the digital representation of the English wheel, bridging the gap between the virtual and physical realms.

An English wheel is an exceedingly adaptable instrument in traditional metalworking. It is a manual manufacturing technique, enabling skilled craftsmen and blacksmiths to shape complex compound curves in sheet metal panels. Accurate measurements and precise adjustments are essential when operating an English wheel to ensure that the metal is shaped with the desired curvature. An automated method to form English wheeled panels through robot forming has recently been proposed. For such a method to be successful, accurate tracking of sheet information including positions, orientations, and deformation is important for error compensation and the design of the subsequent tool paths. In this study, a Vicon motion capture system is employed to monitor the position and shape of the sheet metal during the English wheeling process. The initial experimental results demonstrate the potential of such an in-process metrology system, along with possible avenues for future work.

The concept of molds with gradient cooling characteristics is introduced to actively control the microstructure and, thereby, the physical properties of micro-castings. Such molds are composed of materials with different thermal properties arranged in different geometric configurations imposing varying cooling rates at each point of the casting. To ascertain the feasibility of this concept, molds made of materials with different thermal conductivities were used and their cooling properties were measured. The changes in the microstructure of the castings depending on their location in relation to the mold's body were evaluated. The results confirm the plausibility of microstructure control with such molds.

Abstract Laser polishing (LP) provides a fast and efficient way of remelting part surfaces manufactured by additive manufacturing to alter both their geometric as well as physical properties. Depending on the laser parameters, remelted surfaces with different properties are achieved, with a majority exhibiting lower surface roughness compared to the original surface. In this study, a high-power continuous fiber laser is used to polish Inconel 718 (IN718) surfaces produced by depositing a single layer of clads on a steel substrate by the powder-blown directed energy deposition (DED) process. Polishing was performed under different sets of parameters, namely, laser power, beam diameter, feed rate or feed, hatch spacing, and the number of polishing passes. Their effects on the surface roughness profiles and the microstructural properties of the sample cross section were analyzed after one and two polishing passes. Optical microscopic images of the sample's cross sections show the presence of supersaturated γ phase particles, γ′+γ″ precipitates, Laves phases, and δ phase needles. The combined effect of high-temperature gradients and lower solidification rates in certain regions within the cross section results in undercooled regions and pseudo-heat treatment of unmelted regions close to the undercooled regions. These results are corroborated by indenting the various regions of the IN718 sample cross section with a pyramidal diamond indenter in the form of a grid, resulting in different micro-hardness values due to different densities of precipitate and phase transformed δ particles.

A theoretical framework, united by a "system effect" is formulated to model the cutting/haptic force evolution at the cutting edge of a surgical cutting instrument during its penetration into soft biological tissue in minimally invasive surgery. Other cutting process responses, including tissue fracture force, friction force, and damping, are predicted by the model as well. The model is based on a velocity-controlled formulation of the corresponding equations of motion, derived for a surgical cutting instrument and tissue based on Kirchhoff's fundamental energy conservation law. It provides nearly zero residues (absolute errors) in the equations of motion balances. In addition, concurrent closing relationships for the fracture force, friction coefficient, friction force, process damping, strain rate function (a constitutive tissue model), and their implementation within the proposed theoretical framework are established. The advantage of the method is its ability to make precise real-time predictions of the aperiodic fluctuating evolutions of the cutting forces and the other process responses. It allows for the robust modeling of the interactions between a medical instrument and a nonlinear viscoelastic tissue under any physically feasible working conditions. The cutting process model was partially qualitatively verified through numerical simulations and by comparing the computed cutting forces with experimentally measured values during robotic uniaxial biopsy needle constant velocity insertion into artificial gel tissue, obtained from previous experimental research. The comparison has shown a qualitatively similar adequate trend in the evolution of the experimentally measured and numerically predicted cutting forces during insertion of the needle.

: 19 Dramatic changes in global recovered paper markets, triggered in large part by Chinese import 20 restrictions, challenge the U.S. to find sustainable pathways for increasing the domestic paper 21 recycling rate. This study presents a technology-rich process model of the U.S. domestic paper 22 recycling industry to assess the energy consumption, carbon emissions, and system costs. A 23 scenario analysis shows the viability of three potential pathways for achieving the national goals

Abstract The process parameters of Directed Energy Deposition (DED) have been widely studied including laser power, powder flow rate, and scanning speed. These parameters affect clad dimension and melt pool temperature, which are directly related to part quality. However, laser/powder profiles and their alignment have obtained less attention due to the cumbersome characterization process, although they can be directly associated with local energy density for melt pool formation. This study examines the impact of the alignment between the laser beam and powder flow distributions in DED on clad dimension and melt pool temperature. The laser beam and powder profiles are characterized by measuring their respective 2D Gaussian profiles for a given standoff distance. Aligned and misaligned laser-powder profiles are then used to build single-clad square geometries. It was found that a 500-µm offset between the centers of the laser and powder profiles causes up to a 20% change in both the width and the height of a single clad as well as an average temperature increase of 100 K. To understand the interaction between powder flow, energy flux, and local temperature, the local specific energy density distribution was plotted in 2D. These results suggest that laser-powder misalignment may significantly alter the thermal history and shape of deposited clads, possibly preventing DED-manufactured parts from meeting design properties and causing build failures.

Abstract Electrohydrodynamic (EHD) printing is a versatile process that can be used to pattern high-resolution droplets and fibers through the deposition of an electrified jet. This highly complex process utilizes a coupled hydrodynamic and electrostatic mechanism to drive the fluid flow. While it has many biomedical, electronic, and filtration applications, its widescale usage is hampered by a lack of detailed understanding of the jetting physics that enables this process. In this paper, a numerical model is developed and validated to explore the design space of the EHD jetting process, from Taylor cone formation to jet impingement onto the substrate, and analyze the key geometrical and process parameters that yield high-resolution structures. This numerical model applies to various process parameters, material properties, and environmental factors and can accurately capture jet evolution, radius, and flight time. It can be used to better inform design decisions when using EHD processes with distinct resolution requirements.

The English wheel is a highly flexible traditional metalworking tool. Currently, English wheeling is a manual manufacturing process that allows skilled craftsmen / smiths to form compound curves. The geometric accuracy and repeatability of the forming pieces are heavily influenced by human factors. Consequently, its applications in modern production industries are limited due to its mechanism. This paper presents the application of a single-robot automation system in the English wheeling process (i.e., robot forming). The automation system reads simulation-based toolpaths or camera-tracked trajectories, autonomously computes the end-e ff ector trajectory and ensures e ffi cient robotic end-e ff ector motion planning by avoiding workspace constraints in operation setup. The automation system hardware (UR5e robotic arm) setup and software program structures developed are demonstrated. Experiments are conducted to compare the automation system performance against human performance when following the same toolpath data. It is found that the automation system is compatible with various types of trajectory data and the system e ff ectively enhances the accuracy and repeatability of toolpath executions.

Abstract Though modern mass production has the advantages of low production costs and high efficiency, it cannot meet the needs of low-volume production with the agile demand for point-of-need manufacturing. Here, we aim at the construction of the hull of unmanned underwater vehicles (UUVs). UUVs provide safe and convenient solutions for underwater exploration, but the market and unique features of UUVs call for rapid digital manufacturing technologies. In this work, we propose a novel manufacturing method rooted in Double-Sided Incremental Forming (DSIF) for rapidly producing shell structures with riblet textures to aid drag reduction and anti-biofouling without the burden of specially designed tools or dies. First, a base hull structure is formed using the DSIF method. Then, the same setup is used for surface texturing with a different toolpath strategy utilizing the tool marks/textures on the surface for drag reduction. A coating based on Slippery Liquid Infused Porous Surfaces (SLIPS) technology is applied afterward to the textured surface. Finally, the drag coefficient and anti-biofouling performance are examined in experiments. Results show that with the combination of texture and SLIPS coating, the best drag reduction performance is achieved. The SLIPS coating is very effective in anti-biofouling and remains firmly attached to the surface under different flowing conditions. We anticipate that our method can be used in a broad range of functional shell structure applications with flexibility and cost efficiency.

Abstract Process defects currently limit the use of metal additive manufacturing (AM) components in industries due to shorter fatigue life, potential for catastrophic failure, and lower strength. Conditions under which these defects form, and their mechanisms, are starting to be analyzed to improve reliability and structural integrity of these highly customized parts. We use in situ, high-speed X-ray imaging in conjunction with a high throughput laser, powder-blown directed energy deposition setup to observe powder particle impact behavior within the melt pool. Through fundamental observations of the stochastic, violent powder delivery in powder-blown DED, we uncover a unique pore formation mechanism. We find that a pore can form due to air-cushioning, where vapor from the carrier gas or environment is entrapped between the solid powder particle surface and liquid melt pool surface. A critical time constant is established for the mechanism, and X-ray computed tomography is used to further analyze and categorize the new type of “air-cushioning” pores. It is shown that the air-cushioning mechanism can occur under multiple laser processing conditions, and we show that air-cushioning pores are more likely to be formed when powder particles are larger than 70 μm. By quantifying the effect of powder particle impact, we identify new avenues for development of high-quality laser, powder-blown DED products. Furthermore, we deepen knowledge on defect formation in metal additive manufacturing, which is being increasingly utilized in high performance situations such as aerospace, automotive, and biomedical industries.

Understanding the thermal behavior of additive manufacturing (AM) processes is crucial for enhancing the quality control and enabling customized process design. Most purely physics-based computational models suffer from intensive computational costs and the need of calibrating unknown parameters, thus not suitable for online control and iterative design application. Data-driven models taking advantage of the latest developed computational tools can serve as a more efficient surrogate, but they are usually trained over a large amount of simulation data and often fail to effectively use small but high-quality experimental data. In this work, we developed a hybrid physics-based data-driven thermal modeling approach of AM processes using physics-informed neural networks. Specifically, partially observed temperature data measured from an infrared camera is combined with the physics laws to predict full-field temperature history and to discover unknown material and process parameters. In the numerical and experimental examples, the effectiveness of adding auxiliary training data and using the pretrained model on training efficiency and prediction accuracy, as well as the ability to identify unknown parameters with partially observed data, are demonstrated. The results show that the hybrid thermal model can effectively identify unknown parameters and capture the full-field temperature accurately, and thus it has the potential to be used in iterative process design and real-time process control of AM.

The surface integrity of machined parts is critical to their in-service function, longevity and overall performance. The integrity of the surface is dominantly affected by the chip formation process that can be significantly altered and controlled, among other methods, by ultrasonic vibration assistance. This work will explore the integrity of surfaces generated in three-dimensional ultrasonic vibration-assisted turning (3D-UVAT). The integrity of the obtained workpiece surfaces will be systematically explored in terms of surface roughness, the microstructure of the surface obtained by heat-assisted turning, surface hardness and wettability. A comparative assessment with other surface generation methods, i.e., common turning (CT), one-dimensional (UVAT) and two-dimensional elliptical ultrasonic vibration-assisted turning (EUAT) is also given. The results show that 3D-UVAT can reduce the depth of surface damage and enhance the hydrophobicity of the surface while reducing surface roughness.