bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effects of Pressure on Reusable Self-Assembled Microsphere Masks for Microsphere Photolithography
Authors: Zhu Chen , Kinzel Edward C. 
Published: September 2022

Abstract
Microsphere photolithography (MPL) has shown promise for the low-cost large-scale manufacturing of infrared (IR) metasurfaces. One challenge of the technique is that the microsphere array needs to be in immediate proximity to the photoresist because of the near-filed effect of the photonic jet. This is typically accomplished by directly transferring the microsphere array onto the photoresist layer. The microspheres are then washed away during the development of the photoresist. While there may be a possibility of recovering, cleaning, and reusing the microspheres, this is not typically done. This work studies the self-assembly of the microspheres on a superstrate which can be reused as a contact mask. The microspheres are fixed to this superstrate to minimize debonding when they are brought into contact with the substrate. IR metasurfaces are fabricated and spectrally characterized. The resonant wavelength of IR metasurfaces is shown to be a good statistical metric for the variation of the patterned surface. The results indicate pressure between the substrate and superstrate is a critical factor in maintaining a minimum gap between the microspheres and photoresist. This work shows a way forward for mask-based microsphere photolithography and provides guidance for future microlens array-based photolithographic techniques.
Experimental and Numerical Investigation of Heat Assisted Incremental Sheet Forming Process of Magnesium Alloy
Authors: Kumar Narinder , Mahala Mohit , Agrawal Anupam 
Published: September 2022

Abstract
Magnesium alloys possess exceptionally good mechanical properties, primarily their excellent high strength to weight ratio, and have attracted many applications in the automobile and aerospace industries. However, their use is limited by the poor formability at room temperature when processed through conventional processes because the crystal lattice structure of magnesium is hexagonal closed packed (hcp), due to which there are limited sliding planes. At the elevated temperature ranges of 200–300 °C, more sliding planes get activated, which increases the ductility and decreases the flow stress. It leads to enhanced formability at a higher temperature for magnesium alloys. Therefore, several methods of heat-assisted single point incremental forming process (HA-SPIF) have been established by many researchers in order to improve the forming limits of such hard-to-deform materials. In this study, a new method of the heat-assisted single-point incremental forming process (HA-SPIF) is developed by using cartridge heaters to enhance the forming limits. The influence of higher temperature on fracture depth and thickness distribution of AZ31B magnesium alloy sheet is studied in detail. Experimental results indicate that the fracture depth and thickness distribution increases as the temperature increases. A coupled thermo-mechanical numerical simulation model using ABAQUS/EXPLICIT® is developed to predict forming limits; it was validated using the experimental results. The Johnson-Cook model was implemented as the constitutive model and also to define the fracture criterion. A reasonably good agreement between the results of the numerical simulation and those of the experiment is observed.
Ultrafast Laser-Induced Surface Structuring of Anti-Fouling Steel Surfaces for Biomedical Applications
Authors: Cholkar Abhijit , McCann Ronan , Kinahan David , Brabazon Dermot 
Published: September 2022

Abstract
Metallic surfaces are increasingly used in medical applications due to their favorable material properties such as high strength and biocompatibility. In medical applications anti-fouling properties are an important requirement especially for implants and medical devices which come into contact with different types of fluid streams. These should be anti-fouling in order to prevent contamination and corrosion. Laser processing methods such as ultrafast laser processing is a one-step and scalable process for surface texturing. This process can be used to produce well-defined surface nano- and microscale superficial textures such as Laser-induced Periodic Surface Structures (LIPSS) which can enhance the anti-fouling capability of the surface.
In this study, micro and nano scaled LIPSS structures are manufactured on a biocompatible grade stainless steel 316L substrate using an ultrafast (&lt; 370 fs) and low power (&lt; 4 W) laser system. With an aim to optimize the anti-fouling properties, laser process parameters such as pulse energy, pulse repetition rate and beam scanning speed were varied to produce microstructures on the stainless-steel surface of varying dimensions. Surface roughness was analyzed using a laser surface profilometer and changes in the hydrophobicity were examined using water contact angle goniometry.
Tiling of Cellular Structures Into 3D Parts According to the Density Values of SIMP Topology Optimization
Authors: Ozkapici Helvaci Damla , Yaman Ulas 
Published: September 2022

Abstract
In this study, a novel approach is proposed to enhance the performance of the parts optimized by Solid Isotropic Material with Penalization (SIMP) method. SIMP is a topology optimization method that aims the optimum distribution of material in a design domain subjected to predefined loads, constraints and boundary conditions. The method forces every finite element composing the geometry to have a density of either 1 or 0. The main reason behind penalizing is that regions with intermediate densities are difficult to fabricate. However, including these regions in the optimization output may provide better performance results. Based on this idea, a method is proposed to utilize intermediate densities in a manufacturable form and is applied to 3D geometries. Besides, the remodeled topology is checked against any unconnected cells. In contrast to many methods, which delete the unconnected elements, the proposed method provides connectivity by adding cells.
The outputs of the proposed method are fabricated by using Electron Beam Melting (EBM) and Stereolithography (SLA) technologies. EBM uses material powder and a heat source to melt and fuse the powders while SLA uses photosensitive resin and an ultraviolet light to cure the resin. A common limitation of both technologies is that powder/resin may remain inside the internal features which do not have access to outer surface of the part through the channels. The proposed method ensures the easy removal of excess powder/resin after fabrication. Performance of the method is compared with the SIMP method through test and analysis.
A Deterministic Inspection of Surface Preparation for Metalization
Authors: Shokri Shiva , Sedigh Pooria , Hojjati Mehdi , Kwok Tsz-Ho 
Published: September 2022

Abstract
To improve the surface properties of fiber-reinforced polymer composites, one method is to employ thermal spray to apply a coating on the composite. For this purpose, it uses a metal mesh serving as an anchor between the composite and the coating to increase adhesion. However, the composite manufacturing covers the metal mesh with resin, and getting an acceptable coating is only possible through an optimum exposure of the metal mesh by sand blasting prior to coating. Therefore, this study aims to develop a computer vision and image processing method to inspect the parts and provide the operator with feedback. Initially, this approach takes the images from a single-view microscope as the inputs, and then it classifies the images into two regions of resin and metal mesh using the Otsu’s adaptive thresholding. Next, it segments the resin areas into distinct connected clusters, and it makes a histogram based on the clusters’ size. Finally, the distribution of the histogram can determine the status of the surface preparation. The state-of-the-art has only examined the sand-blasted composites manually, requiring expertise and experience. This research presents a deterministic method to automate the inspection process efficiently with an inexpensive portable digital microscope. This method is practical, especially when there is a lack of standardized data for machine learning. The experimental results show that the method can get different histograms for various samples, and it can distinguish whether a sample is under-blasted, proper-blasted, or over-blasted successfully. This study also has applications to various fields of manufacturing for defect detection and closed-loop control.
Individual-Based Transfer Learning for Dynamic Human-Robot Collaborative Disassembly Line Balancing
Authors: Fang Yilin , Zhang Xiao 
Published: September 2022

Abstract
This paper analyzed the human-robot collaborative disassembly line balancing problem, which is significantly different from the traditional disassembly line balancing problem. In a human-robot collaborative disassembly line, multiple people and robots perform disassembly tasks at each workstation. Due to the uncertainties such as product quality and human capabilities, the human-robot collaborative disassembly line balancing problem is a dynamic optimization problem. We take into account the uncertainty of product quality and personnel capabilities. In addition, dynamic optimization problems require fast and accurate tracking of Pareto’s optimal solution set in a changing environment, and transfer learning has been proven appropriate. Therefore, an individual-based transfer learning-assisted evolutionary dynamic optimization algorithm has been developed to handle the human-robot collaborative disassembly line balancing problem. The algorithm uses an individual-based transfer learning technique to reuse experience, which accelerates the generation of the initial population and improves the convergence speed of solutions. Finally, based on a set of problem examples generated in this paper, the proposed algorithm is compared and analyzed with several competitors in terms of the mean inverted generational distance and the mean hyper-volume, verifying the effectiveness of the proposed algorithm on the dynamic human-robot collaborative disassembly line balancing. The results show that the proposed algorithm has good performance in large scale problems.
Developing Hybrid Hydrogels for Full-Scale Scaffold Fabrication Using Extrusion-Based Bioprinting Process
Authors: Nelson Cartwright , Tuladhar Slesha , Habib MD Ahasan 
Published: September 2022

Abstract
Three-dimensional (3D) bioprinting is a technology that has the power to positively change the medical and pharmaceutical fields in a new and more intuitive way. The goal of this rapidly growing field is to recreate functional tissues, but the process requires the ability to achieve large full-scale scaffolds that replicate human organs. There are many challenges when attempting to print large scaffolds ensuring proper internal and external geometric fidelity that is also suitable for the living cells that undergo the printing process. In order to fabricate a larger and more structurally sound scaffold, higher material viscosities are necessary. This increase in viscosity comes with an increase in printing pressure, which can create unbearable shear stress and eventually damage cells, diminishing viability and proliferation. A set of biomaterial compositions with high structural integrity and shape fidelity that did not require harmful amounts of pressure for extrusion was identified by analyzing rheological, mechanical, and microstructural properties. Many different large-scale scaffolds maintaining geometric fidelity were fabricated with heights up to 3.0 cm and 74 layers using these hybrid hydrogels. This advancement can ensure precise internal and external geometries of full-scale functional tissue replicating scaffolds using 3D bio-printing processes that utilize pressures and materials safe for live cell viability and proliferation.
Optimization-Based Disassembly Sequence Planning Under Uncertainty for Human-Robot Collaboration
Authors: Liao Hao-yu , Chen Yuhao , Hu Boyi , Behdad Sara 
Published: September 2022

Abstract
Disassembly is an integral part of maintenance, upgrade, and remanufacturing operations to recover end-of-use products. Optimization of disassembly sequences and the capability of robotic technology are crucial for managing the resource-intensive nature of dismantling operations. This study proposes an optimization framework for disassembly sequence planning under uncertainty considering human-robot collaboration. The proposed model combines three attributes: disassembly cost, disassembleability, and safety, to find the optimal path for dismantling a product and assigning each disassembly operation among humans and robots. The multi-attribute utility function has been employed to address uncertainty and make a tradeoff among multiple attributes. The disassembly time reflects the cost of disassembly and is assumed to be an uncertain parameter with a Beta probability density function; the disassembleability evaluates the feasibility of conducting operations by robot; finally, the safety index ensures the safety of human workers in the work environment. The optimization model identifies the best disassembly sequence and makes tradeoffs among multi-attributes. An example of a computer desktop illustrates how the proposed model works. The model identifies the optimal disassembly sequence with less disassembly cost, high disassembleability, and increased safety index while allocating disassembly operations between human and robot. A sensitivity analysis is conducted to show the model’s performance when changing the disassembly cost for the robot.
Effect of Powder Layer Thickness on Residual Stress in Laser Powder Bed Fusion of IN718
Authors: Mirkoohi Elham , Tran Hong-Chuong , Lo Yu-Lung , Chang You-Cheng , Lin Hung-You , Liang Steven Y. 
Published: September 2022

Abstract
Understanding the relationships between the processing factors in laser powder bed fusion (L-PBF) and residual stress formation is critical for improving the final part performance since tensile residual stress has a critical impact on fatigue life performance and final material properties of the manufactured part. Laser powder bed fusion has virtually infinite number of processing factors each can impact the residual stress, among which, layer thickness is one of them. This paper investigates the impact of powder layer thickness on residual stress formation for the Ni-based super-alloy Inconel 718 (IN718). Test coupons with different layer thicknesses are fabricated with the same geometry. Residual stress is determined via X-ray diffraction (XRD) at different locations along the build direction and transverse direction. In addition, the previously developed physics-based analytical model is used to draw a relationship between powder layer thickness and residual stress through the prediction of temperature field and thermal stress using incremental plasticity. The results of computational modeling and experiments are in good agreement and shows that the increase in powder layer thickness increases the residual stress in an additively manufactured part.
Physics-Informed Machine Learning for Accelerated Testing of Roll-to-Roll Printed Sensors
Authors: Chandra Mouli S. , Sedaghat Sotoudeh , Ramazan Oduncu Muhammed , Saha Ajanta , Rahimi Rahim , A. Alam Muhammad , Wei Alexander , Shakouri Ali , Ribeiro Bruno 
Published: September 2022

Abstract
Roll-to-roll printing has significantly shortened the time from design to production of sensors and IoT devices, while being cost-effective for mass production. But due to less manufacturing tolerance controls available, properties such as sensor thickness, composition, roughness, etc., cannot be precisely controlled. Since these properties likely affect the sensor behavior, roll-to-roll printed sensors require validation testing before they can be deployed in the field. In this work, we improve the testing of Nitrate sensors that need to be calibrated in a solution of known Nitrate concentration for around 1–2 days. To accelerate this process, we observe the initial behavior of the sensors for a few hours, and use a physics-informed machine learning method to predict their measurements 24 hours in the future, thus saving valuable time and testing resources. Due to the variability in roll-to-roll printing, this prediction task requires models that are robust to changes in properties of the new test sensors. We show that existing methods fail at this task and describe a physics-informed machine learning method that improves the prediction robustness to different testing conditions (≈ 1.7× lower in real-world data and ≈ 5× lower in synthetic data when compared with the current state-of-the-art physics-informed machine learning method).
Experimental Analysis of Metal Inert Gas Based Wire Arc Additive Manufacturing of Aluminum Nanocomposite AA7075
Authors: Darnell Mason , Harwig Dennis , Liu Xun 
Published: September 2022

Abstract
This work studies Metal Inert Gas (MIG) based Wire Arc Additive Manufacturing (WAAM) for nanoparticle enhanced AA7075. MIG WAAM is important for production and large structures due to its high deposition rates compared to Tungsten Inert Gas (TIG) or powder-based AM processes. Both MIG and TIG take advantage of wire feedstock, which is more readily available than powdered metals since the welding technology has been established for decades. Powder based processes allow for more complicated geometries but take significantly more time to produce and can suffer from voids which lead to non-uniform part density. TIG is normally used in welding of aluminum because it results in fewer defects, but the TiC/TiB2 nanoparticles eliminate solidification cracking normally associated with high strength aluminum alloys during welding. Porosity is another problem faced when welding aluminum, which can be affected by many things including deposition parameters, atmosphere and even the welding equipment used. Effects of different deposition parameters have been comprehensively studied including the deposition geometry and metallurgical properties. The process is also monitored with current/voltage measurement and high-speed imaging to understand the droplet transfer mode and molten pool development. The results are used to optimize process parameters to achieve the fewest defects possible while comparing different metal transfer modes. Multi-scale characterizations will be performed to examine the porosity distribution, solidification mode and grain size through optical microscopy. Future works will explore the distribution of secondary phases, precipitates, and nanoparticles through scanning electron microscopy (SEM) as well as conducting some mechanical testing of the as built structures such as hardness mapping and tensile tests.
Machine Vision Tracking and Automation of a Microrobot (sAFAM)
Authors: Warn Colin , Sherehiy Andriy , Alqatamin Moath , Ritz Brooke , Zhang Ruoshi , Chowdhury Sri S. , Wei Danming , Popa Dan O. 
Published: September 2022

Abstract
In this paper, we propose a method for tracking a microrobot’s three-dimensional position using microscope machine vision. The microrobot, theSolid Articulated Four Axis Microrobot (sAFAM), is being developed to enable the assembly and manipulation of micro and nanoscale objects. In the future, arrays of sAFAMS working together can be integrated into a wafer-scale nanofactory, Prior to use, microrobots in this microfactory need calibration, which can be achieved using the proposed measurement technique. Our approach enables faster and more accurate mapping of microrobot translations and rotations, and orders of magnitude larger datasets can be created by automation. Cameras feeds on a custom microscopy system is fed into a data processing pipeline that enables tracking of the microrobot in real-time. This particular machine vision method was implemented with a help of OpenCV and Python and can be used to track the movement of other micrometer-sized features. Additionally, a script was created to enable automated repeatability tests for each of the six trajectories traversable by the robot. A more precise microrobot workable area was also determined thanks to the significantly larger datasets enabled by the combined automation and machine vision approaches.
Process Mechanics – a Guide for Industry 4.0: Modelling Cutting of Nimonic 90 and Ti-6Al-4V
Authors: Lortz W. , Pavel Radu 
Published: September 2022

Abstract
The chip formation models developed to date give no exact representation of the physics phenomena occurring during the complex machine cutting process. Despite the large number of investigations and simulations, there is still limited clarity of the real chip formation process. The models try to solve the plastic flow through force or stress simulation, without proper regard to adequate process mechanics. Due to these circumstances, practical evidence is missing. Analyzing this situation very carefully, some scientists founded the Industry 4.0 initiative to create scientific space with new opportunities. Whereas second and third industrial revolutions have been focused on organization and automation — Industry 4.0 is focused on technology, data integration and artificial intelligence (AI). However, before teaching a computer AI, the adequate process mechanics should be systematically developed and understood. This paper presents the complex process mechanics of chip formation with non-linear conditions in the metal microstructure, with two different friction zones, with self-hardening or temperatures effects. These entire phenomena can’t be solved separately because they have an interdependent relationship. The developed mathematical equations for strain and stress lead to square grid deformation in the chip formation zone, and this grid deformation does not disappear after completing the process, so that the theoretical development can be compared with practical results. This will be presented for two different materials Nimonic 90 and Ti-6Al-4V. For Nimonic 90 a built-up-edge (BUE) will be identified, and this is based on the stream-line inflow-angle. Quite contrary is the chip formation process for Ti-6Al-4V. A diffusion process in the interface chip-tool take place resulting in a self-blockade with segmented chip. In addition, the developed temperatures during cutting could be estimated and will be presented for the two different creep-resistant alloys. Finally, a high agreement between the theoretical and experimental results could be documented.
Trajectory Control of 6-DOF Welding Robot Based on STM32
Authors: Li Dingzhong , Lu Hong , Zhang Yongquan , Wu Zidong , Huang He , Liu Meng , Wang Shaojun 
Published: September 2022

Abstract
Automatic welding technology has been widely used in China’s industrial production. Welding robots with the characteristics of high efficiency and high qualification rate began to appear in the industrial production line. However, in order to protect their own competitiveness, most companies use closed source control mode for welding robots, resulting in high control cost, low system openness and poor flexibility. Therefore, it is of great significance to design an open-source and low-cost six degree of freedom welding robot motion control system based on STM32 microcontroller. According to the requirements of motion control system, the development board of dual core processor is selected as the core to complete the hardware design of motion control system. The software design of the control system adopts the framework of cooperative work between the upper computer and the lower computer, and the upper computer is developed with software, which has good human-computer interaction function; The lower computer is programmed through the modular idea, which is convenient for secondary development and has good expansibility. According to the standard DH method, the trajectory planning of the 6-DOF robot is realized, and the S-type acceleration and deceleration algorithm and other related algorithms are used to realize its more efficient and smooth motion control.