bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimization of Friction Crush Welding of Two Dissimilar Metals: Aluminium 6061 T-6 and Stainless Steel AISI 304
Authors: Singh Prem , Deepak Dharmpal , Brar Gurinder Singh 
Published: January 2021

Abstract
In order to cater increasing need of lightweight and strong structures to be used in various industries like ship manufacturing, railways transportation, vehicle body cell etc., efforts have been made to develop and assess various welding or joining techniques. Dissimilar metal welding offers promising solution in this direction due to modification of properties by combining two dissimilar metals in terms of mechanical properties and better corrosion or electrical properties with lesser specific weight. Stainless steel of grade AISI 304 is widely used for manufacturing application in different industries and aluminum alloy 6061 T-6 has gaining importance in welding due to its high corrosive resistance and high weldability properties. In the present work, welding of dissimilar metals i.e. Aluminium 6061 T-6 and Stainless Steel – AISI 304 was carried out with new welding technique i.e. Friction Crush Welding (FCW). Dissimilar welds prepared at different levels of tool rotation and feed rate were characterized in terms of bond strength. Taguchi L9 Design of Experiments (DOE) was used to find optimal process parameters for dissimilar FCW. The theoretical optimum bond strength calculated using Taguchi L9 was 5134.53 N at tool rotation of 740 rpm and feed rate of 45 mm/mim. The theoretical optimum value was in line with the experimental results.
Generation of Surfaces With Isotropic and Anisotropic Wetting Properties by Curved Water Jet Guided Laser Micro-Machining
Authors: Shi Yi , Cao Jian , Ehmann Kornel F. 
Published: January 2021

Abstract
This experimental work utilizes a newly developed method, curved water jet guided laser micro-machining, to generate micro features on metallic surfaces. During the process, material is removed by a high-power nanosecond laser beam which is transmitted through a high-pressure micro water jet via total internal reflection. To achieve intricate texturing patterns, a secondary motion component is superimposed on the XY motion of the workpiece provided by the motion stage. The secondary motion is generated by deflecting the water jet trajectory by a controllable dielectrophoretic force. The induced secondary motion of the water jet cuts the processing time to one half when generating texture patterns for isotropic wetting as compared to processes with only XY motion. The ability to alter the water jet’s trajectory by tens of microns at high frequencies, which is beyond the capability of conventional CNC machines, allows a wide range of different micro patterns to be generated, profoundly increasing the flexibility and efficiency of the process as compared to conventional approaches. As a demonstration, surface textures for isotropic and anisotropic behaviors are generated on stainless steel surfaces. The influence of feature spacing, motion speed (frequency) and texturing patterns on surface wettability are studied.
Research on Positioning Error Analysis and Compensation Experiment of the Dual-Driving Feed Worktable
Authors: Xue Jiafu , Lu Hong , Liu Qi , Liu Qiong , Dou Haoyu , Wang Dong , Ling Zhi 
Published: January 2021

Abstract
The dual-driving feed worktable (DDFW) is widely used in feed system because of its high stability and load capacity, while its feed system is one of the important parts that affects the feed accuracy of machine tools. Due to the influence of assembly, manufacturing and other factors, the positioning error of DDFW is produced, which reduces the machining accuracy of the machine tools. Therefore, the research on the positioning error compensation of DDFW is of great significance. In this paper, the positioning error of DDFW is measured with absolute optical scale and the positioning error model of DDFW is established by modeling method of orthogonal polynomials at first. Then an electronic cam combined with virtual axis compensation strategy is designed for DDFW to reduce positioning error. Finally, the compensation experiment is carried out and the error compensation results are analyzed to verify the effectiveness of the error compensation strategy designed in this paper.
Delamination in Surface Machining of CFRP Composites Using Rotary Ultrasonic Machining With Horizontal Ultrasonic Vibration
Authors: Wang Hui , Zhang Dongzhe , Li Yunze , Cong Weilong , Burks Anthony R. 
Published: January 2021

Abstract
Surface machining of carbon fiber reinforced plastic (CFRP) using rotary ultrasonic machining (RUM) with vertical ultrasonic vibration was effective in reducing many issues, including high cutting force, high torque, and high tool wear rate. The vertical ultrasonic vibration also induced damages to machined CFRP surfaces and then resulted in increased surface roughness. To simultaneously decrease surface roughness and cutting force, the direction of ultrasonic vibration needed to be parallel with the surface generation direction (horizontal feeding direction). The horizontal ultrasonic vibration was then developed and applied for RUM surface machining of CFRP. The application of horizontal ultrasonic vibration in RUM surface machining produced simultaneously decreased surface roughness and cutting force. However, there were no investigations on delamination in such a process, and delamination was considered as one of the major factors to reject the machined CFRP products. This investigation would study the delamination under different machining-variable groups, the delamination generation mechanisms, and the relationships between delamination and cutting forces through the experimental method in surface machining of CFRP using RUM with horizontal ultrasonic vibration. Smaller cutting force and delamination thickness would be produced by the smaller depth of cut, smaller feedrate, or larger tool rotation speed. Smaller indentation depth was generated by larger tool rotation speed or smaller feedrate. Smaller material removal rate and abrasive-grain number taking part in the cutting process were produced by the smaller depth of cut. The delamination initiation at larger uncut CFRP thickness would be induced by higher cutting force.
Dynamic Mechanical Analysis of ABS From Hybrid Additive Manufacturing by Fused Filament Fabrication and Shot Peening
Authors: Hadidi Haitham , Mailand Brady , Sundermann Tayler , Johnson Ethan , Karunakaran Rakeshkumar , Negahban Mehrdad , Delbreilh Laurent , Sealy Michael 
Published: January 2021

Abstract
The mechanical properties of 3D printed polymers parts are process parameter dependent. Defects such as inadvertent voids between deposited rasters and layers lead to weakness in produced parts, which results in inferior mechanical properties as compared to injection molding. An alternative method to change energy absorption and stiffness of a polymer is hybrid additive manufacturing (AM). Hybrid-AM is the use of additive manufacturing with one or more secondary processes that are fully coupled and synergistically affect part quality, functionality, and/or process performance. In this study, fused filament fabrication (FFF) was coupled with layer-by-layer shot peening to study the dynamic mechanical properties of ABS 430 polymer using dynamic mechanical analysis (DMA). FFF is a heated extrusion process. Shot peening is a mechanical surface treatment that impinges a target with a stochastically dispersed, high velocity stream of beads. Compressive residual stress was imparted to preferential layer intervals during printing to modify the elasticity (stiffness), viscosity, toughness, and glass transition temperature. Viscoelastic and dynamic mechanical properties are important to the performance of polymers in automotive, aerospace, electronics, and medical components. Coupling printing and peening increased the storage and loss moduli as well as the tangent delta. DMA results suggest that preferential layer sequences exist that possess higher elasticity and better absorb energy upon sinusoidal dynamic loading.
Interval Multi-Objective Evolutionary Optimization for Disassembly Line Balancing With Uncertain Task Time
Authors: Fang Yilin , Zhang Hanke , Liu Quan , Zhou Zude , Yao Bitao , Pham Duc Truong 
Published: January 2021

Abstract
In the disassembly line balancing problem, the disassembly time of task is usually uncertain due to the influence of various factors. Interval number theory is very suitable to solve this problem. In this paper, a new interval mathematical model is proposed and the objectives are to minimize the cycle time and the total energy consumption of robots. To solve this problem, an evolutionary algorithm named γ based-NSGA-II for the interval multi-objective optimization is proposed. This algorithm directly solve the original interval multi-objective optimization problem by using interval Pareto dominance and interval crowding distance, rather than transforming the problem into a determined parameter optimization problem, which can retain the uncertain information, making the solution more reliable. And the local search operator is proposed to strength the local search ability of the algorithm. Experiment is executed in the three scale problems. By comparing the value of HV-U and HV-D, the influence of γ on the convergence, distribution and uncertainty of the algorithm is analyzed, and the optimal value of γ for this problem is found. On this basis, the performance of the proposed γ based-NSGA-II is compared with NSGA-II and MOEA / D by the value of IGD. The results show that the proposed algorithm has good performance in the small and medium scale problems.
Observation at the Interelectrode Gap of Micro Electric Discharge Milling
Authors: Mullya Satish A. , Karthikeyan G. , Patil Ranjit S. , Patil Rajkumar B. 
Published: January 2021

Abstract
The rapid phenomenon happening at the interelectrode gap (IEG) of 50 microns in the micro electric discharge milling (μED-milling) is complex. Various techniques such as computational fluid dynamics (CFD), scanning electron microscope (SEM), and the high-speed camera is utilized to study the behavior. As multiple process occurs in microseconds, high-speed video camera is useful to capture rapidly occurring events. The actual process images at the interelectrode gap (IEG) of the micro electric discharge milling (μED-milling) is captured using a high-speed video camera pco. dimax HS4 highspeed CMOS camera. This camera can capture images at a maximum frame rate of 46746 fps at a lower resolution of 320 × 200. The images of spark and dielectric flow are captured at a high resolution and a frame rate of 2277 fps. The high-speed images show sparking to be continuous along the periphery of the tool which is unique in μED-milling. The obtained images of the spark are used to find the IEG size and the bubble motion is used to calculate the velocity of the dielectric. The dielectric motion is majorly vortex flow and is observed at the back of the tool due to tool rotation. The SEM images show spherical debris particles deposited on the machined surface. The size of the debris particles depends on the input energy. Larger crater is formed on the workpiece surface at high energy levels which eventually forms large size debris particles. All the techniques used provide useful information and shows close resemblance.
Nanoclay Suspension-Enabled Extrusion Printing of 3D Soft Structures for Biomedical Applications
Authors: Jin Yifei , Antonelli Patrick J. , Long Christopher J. , McAleer Christopher W. , Hickman James J. , Xiong Ruitong , Huang Yong 
Published: January 2021

Abstract
Three-dimensional (3D) extrusion printing of cellular/acellular structures with biocompatible materials has been widely investigated in recent years. However, the requirement of suitable solidification rate of printable ink materials constrains the utilization of extrusion-based 3D printing technique. In this study, the yield-stress nanoclay suspension-enabled extrusion-based 3D printing system has been investigated and demonstrated to overcome solidification rate constraints during printing. Utilizing the liquid-solid transition property of nanoclay suspension, two fabrication approaches, including nanoclay support bath-enabled printing and nanoclay-enabled direct printing, have been proposed. For the former approach, nanoclay (Laponite EP) has been used as a support bath material to fabricate alginate-based tympanic membrane patches. The constituents of alginate-based ink have been investigated to have the desired mechanical property of alginate-based tympanic membrane patches and facilitate the printing process. For the latter approach, nanoclay (Laponite XLG) has been used as an internal scaffold material to help print poly (ethylene glycol) diacrylate (PEGDA)-based neural chambers, which can be further cross-linked in air. Mechanical stress analysis has been performed to explore the geometric limitation of printable Laponite XLG-PEGDA neural chambers.
A Framework for Industrial Robot Training in Cloud Manufacturing With Deep Reinforcement Learning
Authors: Liu Yongkui , Yao Junying , Lin Tingyu , Xu He , Shi Feng , Xiao Yingying , Zhang Lin , Wang Lihui 
Published: January 2021

Abstract
Cloud manufacturing is a service-oriented networked manufacturing model that embraces the concept of ‘Everything-as-a-Service’. In cloud manufacturing, distributed manufacturing resources encompassed in the product lifecycle are transformed into manufacturing services. Industrial robots are an important category of manufacturing resources in cloud manufacturing. During the past years, robots have been demonstrated to be able to learn various dexterous manipulation skills through training with deep reinforcement learning (DRL). In cloud manufacturing, there are many complex industrial application scenarios that require dexterous robots. Hence, robot training, which enables robots to learn various manipulation skills, becomes an important requirement for cloud manufacturing in the future, leading to the concept of ‘Robot Training-as-a-Service’. This paper focuses on industrial robot training in the context of cloud manufacturing. First, related work on cloud manufacturing, DRL, DRL-based robot training, and cloud-edge collaboration is briefly reviewed and analyzed. Then, a framework for industrial robot training in cloud manufacturing with DRL is proposed, and a simplified case study is presented to demonstrate the basic principle of the framework. Finally, possible future research issues are discussed.
Sketch-Based Tensor Decomposition for Non-Parametric Monitoring of Electrospinning Processes
Authors: Segura Luis Javier , Muñoz Christian Narváez , Zhou Chi , Sun Hongyue 
Published: January 2021

Abstract
Electrospinning is a promising process to fabricate functional parts from macrofibers and nanofibers of bio-compatible materials including collagen, polylactide (PLA), and polyacrylonitrile (PAN). However, the functionality of the produced parts highly rely on quality, repeatability, and uniformity of the electrospun fibers. Due to the variations in material composition, process settings, and ambient conditions, the process suffers from large variations. In particular, the fiber formation in the stable regime (i.e., Taylor cone and jet) and its propagation to the substrate plays the most significant role in the process stability. This work aims to designing a fast process monitoring tool from scratch for monitoring the dynamic electrospinning process based on the Taylor cone and jet videos. Nevertheless, this is challenging since the videos are of high frequency and high dimension, and the monitoring statistics may not have a parametric distribution. To achieve this goal, a framework integrating image analysis, sketch-based tensor decomposition, and non-parametric monitoring, is proposed. In particular, we use Tucker tensor-sketch (Tucker-TS) based tensor decomposition to extract the sparse structure representations of the videos. Additionally, the extracted monitoring variables are non-normally distributed, hence non-parametric bootstrap Hotelling T2 control chart is deployed to handle this issue during the monitoring. The framework is demonstrated by electrospinning a PAN-based polymeric solution. Finally, it is demonstrated that the proposed framework, which uses Tucker-TS, largely outperformed the computational speed of the alternating least squares (ALS) approach for the Tucker tensor decomposition, i.e., Tucker-ALS, in various anomaly detection tasks while keeping the comparable anomaly detection accuracy.
Identification of Young’s Modulus and Equivalent Spring Constraint Boundary Conditions of the Object With Incomplete Displacement Boundary Conditions
Authors: Xu Tian , Lei Yong 
Published: January 2021

Abstract
In endoscopic surgery, the surgical navigation needs to calculate the internal deformation of the soft tissue by biomechanical model which needs to determine the elastic properties and boundary conditions. However, these information cannot be obtained accurately in a real operation scenario. For example, only a limited portion of a liver surface can be observed in a hepatic surgery under endoscope while its elastic properties remain unknown. In addition, simple boundary conditions such as fixed constraints and free-force constraints are not physically adequate to simulate the elastic effect of ligaments attached to the liver. Biomechanical models of the soft tissue have been thoroughly studied in recent years. In these studies, boundary conditions play an important role in identification of elastic properties for mechanical model based methods. But they rarely combine these unknown conditions together to construct the model, and instead set boundary conditions or elastic properties as known for simplification. In this paper, we present a novel method to identify the Young’s modulus and equivalent spring constraint boundary conditions of a partially observed soft object with incomplete boundary conditions. The spring constraint boundary condition is applied to alternate the conventional displacement boundary conditions (e.g. free constraint and fixed constraint) and an inverse algorithm based on the standard finite element method (FEM) and Gauss-Newton (GN) method is developed, which takes external forces and displacements of observable nodes as inputs. A series of numerical simulation experiments are implemented and the analysis of simulation results show the feasibility of the proposed method.
Human-in-Cognition Manufacturing-Loop (HCML): Framework and Technologies
Authors: Jiang Yanan , Liu Yahui , Bao Jinsong , Li Jie , Zhang Jie , Fang Yunhao 
Published: January 2021

Abstract
The wave of intelligent manufacturing has swept the world, and intelligent manufacturing has realized the interconnection of the physical world and the information world. With the deep integration of intelligent manufacturing, cognitive computing and cognitive science, the manufacturing industry presents a new manufacturing model, which is called cognitive manufacturing. Cognitive manufacturing, as the evolution stage of intelligent manufacturing, endows industrial manufacturing system with perception and judgment ability. In addition, it enables the machine to realize self-adaptation, self-organization and self-decision-making based on cognition, thus completing accurate execution. But the manufacturing system cannot be entirely controlled by machines without the involvement of human. Based on the new generation of intelligent manufacturing for human-information-physical system and human-computer synthetic-intelligent system. This paper compares and extends the relevant technical models of intelligent manufacturing and cognitive manufacturing. Furthermore, it presents a framework that integrates the cognitive ability of human and machine, putting forward a cognitive manufacturing system architecture of human-machine collaborative cognition, called Human-in-Cognition Manufacturing-Loop (HCML). Additionally, the connotation, key implementation technology and future development trend of the system are discussed in details, and the role of artificial intelligence in the system are introduced.
Effects of Shield Gas Flow on Meltpool Variability and Signature in Scanned Laser Melting
Authors: Deisenroth David C. , Neira Jorge , Weaver Jordan , Yeung Ho 
Published: January 2021

Abstract
In laser powder bed fusion metal additive manufacturing, insufficient shield gas flow allows accumulation of condensate and ejecta above the build plane and in the beam path. These process byproducts are associated with beam obstruction, attenuation, and thermal lensing, which then lead to lack of fusion and other defects. Furthermore, lack of gas flow can allow excessive amounts of ejecta to redeposit onto the build surface or powder bed, causing further part defects. The current investigation was a preliminary study on how gas flow velocity and direction affect laser delivery to a bare substrate of Nickel Alloy 625 (IN625) in the National Institute of Standards and Technology (NIST) Additive Manufacturing Metrology Testbed (AMMT). Melt tracks were formed under several gas flow speeds, gas flow directions, and energy densities. The tracks were then cross-sectioned and measured. The melt track aspect ratio and aspect ratio coefficient of variation (CV) were reported as a function of gas flow speed and direction. It was found that a mean gas flow velocity of 6.7 m/s from a nozzle 6.35 mm in diameter was sufficient to reduce meltpool aspect ratio CV to less than 15 %. Real-time inline hotspot area and its CV were evaluated as a process monitoring signature for identifying poor laser delivery due to inadequate gas flow. It was found that inline hotspot size could be used to distinguish between conduction mode and transition mode processes, but became diminishingly sensitive as applied laser energy density increased toward keyhole mode. Increased hotspot size CV (associated with inadequate gas flow) was associated with an increased meltpool aspect ratio CV. Finally, it was found that use of the inline hotspot CV showed a bias toward higher CV values when the laser was scanned nominally toward the gas flow, which indicates that this bias must be considered in order to use hotspot area CV as a process monitoring signature. This study concludes that gas flow speed and direction have important ramifications for both laser delivery and process monitoring.
Mechanical Evaluation of Selective Laser Melted Ni-Rich NiTi: Compression, Tension, and Torsion
Authors: Safaei Baghbaderani Keyvan , Nematollahi Mohammadreza , Bayatimalayeri Parisa , Dabbaghi Hediyeh , Jahadakbar Ahmadreza , Elahinia Mohammad 
Published: January 2021

Abstract
Two unique behaviors of superelasticity and shape memory effect have made shape memory alloy such as NiTi, an interesting alloy for different applications. Recently, additive manufacturing (AM) as a powerful tool for fabricating NiTi has become of interest to make complex geometries. Selective laser melting (SLM) is an AM method that not only provides flexibility to make complex 3D shapes but also it can be possible to tailor the thermomechanical properties of the parts just by changing the process parameters. The non-homogenous microstructure of as-fabricated parts as well as asymmetric mechanical behavior of NiTi, make it important to study the properties of SLM NiTi parts under different loading condition. In this study, Ni50.8Ti (at. %) powder was utilized to fabricate cube, dog-bone, and tube by SLM technique. The transformation temperatures (TTs) of samples were measured by the differential scanning calorimetry (DSC) method and the variation of TTs was discussed. Three coupons were tested mechanically under compression, tension, and torsion. In-situ digital image correlation (DIC) was employed to measure and monitor the strain field of samples during the mechanical tests. The strain distribution showed localized strain for all three samples. The equivalent stress/strain was calculated to compare the result of compressive, tensile, and torsional responses and the significant asymmetric behavior was shown and discussed.