bluuebunny/crossref_metadata_2025_split huggingface dataset:
An Approach to Extend the Digital Thread From Requirements to Model Geometry
Authors: Zhou Jiwei , D. Camba Jorge , Hartman Nathan , Li Zhongtian 
Published: September 2022

Abstract
As organizations embrace Industry 4.0 and its corresponding digital transformation, new technologies and practices are enabling more resilient, integrated, and sustainable approaches to product development. Researchers have explored the information flows and data relationships between requirements management (RQM) practices and Computer-Aided Design (CAD) to improve New Product Development (NPD) processes. Similarly, Life Cycle Assessment (LCA) tools can be used to assess the environmental impact of a product at the early stages of development. In this paper, we propose a novel approach to integrate RQM, CAD, and LCA in the NPD process in a manner that extends the “digital thread” of information from the definition of design requirements to the geometry of the digital product model. Specifically, we demonstrate the seeding of mechanical design models directly from design requirements as a starting point for parametrization, the linking of data items to facilitate subsequent design changes involving geometry, and the use of data connections between requirements and 3D models for continuous design verification. Our approach is supported by a Product Lifecycle Management (PLM) system and involves a workflow with several stages and various inputs from stakeholders. We validate our approach through the implementation of a case study involving a mechanical assembly and a commercial PLM system.
Thermoplastic Forming Process for Manufacturing Arbitrary Blade Edge Geometries From Bulk Metallic Glass
Authors: Dancholvichit Nattasit , Salapaka Srinivasa , Kapoor Shiv 
Published: September 2022

Abstract
In corneal surgery, several incision instruments including the curvilinear or straight incision blades are required to construct a scleral tunnel to ensure that the wound is self-sealing after the operation. Bulk metallic glass (BMG) is proving to be a good candidate for making surgical blades, where sharp edges can be produced through a thermoplastic molding and a drawing process implemented by designing and controlling the drawing velocity at supercooled temperature. This article presents a mechanistic approach to obtain drawing velocity profile of drawing actuators that accommodates various shapes of the blade edges without having to carry out the entire extensional drawing process, which is extensive and tedious. To manufacture the multi-facet BMG knife blade edges that result in good quality, the velocity profile is developed based on the filament stretching process and the geometry and shape of the mold along with the blade profile to maintain the imposed flow stress during the blade edge formation. Two types of geometrical transformational features including drawing distance and offset angle of the draw direction to the profile, are considered to ensure that the flow stress of the drawing process is in the desirable Newtonian region. To demonstrate the feasibility of the proposed approach, H∞ control design is used to facilitate consistent good quality necking of the blade formation. The velocity profile of 45° and crescent BMG blades are generated and used to manufacture these blades. The 45° blade edge samples are successfully manufactured with the average of X-Z, X-Y straightness, and the edge radius of the blade of 1.4 ± 0.5 μm, 1.4 ± 0.5 μm, and 42.4 ± 2.3 nm, respectively. The crescent blade edge samples are manufactured with roundness deviation, and the edge radius of the blade of 5.4 ± 1.6 μm, and 35.7 ± 4.2 nm, respectively. The effects of BMG sample temperature settings on the quality of the manufactured blades are presented.
Image-Based Fractographic Pattern Recognition With Cluster Analysis
Authors: Guo Shenghan , Paradise Paul , Van Handel Nicole , Bhate Dhruv 
Published: September 2022

Abstract
Scanning Electron Microscopy (SEM) is traditionally leveraged to image fracture surfaces and generate information for analysis. Conventionally, experts identify patterns of interest in SEM images and link them to fracture phenomena based on knowledge and experience. Such practice has substantial limitations. It relies on expert opinions for decision-making, which poses barriers for practitioners without relevant background; manual inspection must be done for individual SEM images, thus time-consuming and inapt for industrial automation. There is a genuine demand for a fast, automatic method for fractographic pattern recognition. Targeting the problem, this study proposes a two-stage data-driven approach based on clustering. In offline analysis (Stage 1), a clustering algorithm identifies the generic fractographic patterns on part. Each pattern corresponds to a cluster. Expert evaluation of the part’s crack status is leveraged to map individual patterns (clusters) to a crack type. In in-situ monitoring (Stage 2), SEM images of new parts are matched to the clusters from stage 1, which reveals the generic patterns on the part and indicates the potential crack status. The proposed approach enables automatic fractographic analysis without experts. It is demonstrated to be effective on real SEM images of additively manufactured Inconel-718 specimens subjected to high cycle fatigue.
Decision Support for Locating Manufacturing Plants in Emerging Economies Using a Reliability Approach
Authors: Gadalla Mohamed , Azab Ahmed 
Published: September 2022

Abstract
In today’s distributed manufacturing reality, investors worldwide are faced with the dilemma of deciding on the optimal geographic spot for their manufacturing plants. On the one hand, emerging economies could be appealing because of their cheap labor as well as possibly their lack of or reduced regulations, litigation, and paperwork in some cases. On the other hand, these very same emerging economies can be quite risky because of the lack of stability of their political systems and hence, the associated economic volatility. Such economies can collapse in a relatively short period of time due to factors such as political instability, corruption, lack of democracy and the rule of law, social and racial injustices, and religious extremism, to name a few. In this paper, we propose a modeling approach where an economy is represented as an engineering system, the lifespan of which is subject to potential conditions, events, and failure modes. Such conditions and factors in the face of these fragile economies are modeled as pushers and deflators contributing to their instability. Hence, all laws of Reliability Engineering can be used to decide on the probability of success of such a system and its lifetime in the face of all uncertainty and given risks in today’s global climate. It is imperative that the health of the economic climate is a critical element solving the facility location and allocation problem; this entails deciding on large manufacturing investments in the form of new manufacturing plants being constructed and the accompanied supply chains. Enablers to allow for packageable manufacturing systems easier to relocate in the wake of this uncertain economic turmoil are also discussed. System Dynamics will be used as future work to account for the forces (deflators and pushers) when quantifying the proposed metrics. AI and Data Analytics techniques are also recommended to quantify the reliability parameters.
A Functionally Gradient NiTi Shape-Memory Alloy Fabricated by Selective Laser Melting
Authors: Li Kun , Zhan Jianbin , Ma Ruijin , Ren Yingzhi , Lin Jinxin 
Published: September 2022

Abstract
The near-equiatomic NiTi alloy has a shape memory function, but the simple forming structure limits its application. Selective laser melting is a promising way to manufacture functionally complex structures due to its layer-wise production advantage, which could broaden the applications of NiTi alloy in the engineering fields. This work explored a novel method of controlling the repetition of laser remelting to manufacture NiTi alloys with multiple phase-transformation temperatures via selective laser melting (SLM). The results demonstrates that the remelting strategy not only increases the ultimate tensile strength and elongation of the SLMed NiTi alloy, but also increases the Ms above room temperature. The increase in laser power increases the temperature at which martensite starts (Ms) to transformation in the range higher room temperature (25°C), thus increasing the critical stress of martensitic detwinning in the final sample. Through the optimized repetitive laser remelting strategy with different laser powers on specific areas of the sample, a functionally gradient NiTi build is successfully obtained. This study suggests SLM embedded with laser remelting is a potential method to realize 4D printing for NiTi alloys.
Directed Energy Deposition Using Non-Spherical Metal Powders?
Authors: Garg Richie , Singh Dhami Harish , Ranjan Panda Priti , Viswanathan Koushik 
Published: September 2022

Abstract
Metal additive manufacturing (AM) enables the production of non-trivial geometries and intricate internal structures. Directed energy deposition (DED) is one such AM process that has the inherent advantage of producing multi-material components on complex pre-existing geometries. Significant recent interest in DED processes has been driven by the need for inexpensive powders and potential material recycling. In this work, we explore the possibility of using non-standard arbitrary shaped metal powders within the DED process. A standard numerical model, comprising a three-dimensional viscous, compressible, turbulent solver with two-way discrete phase coupling is employed to understand the mechanics of gas-driven non-spherical powder flow. Spatial distributions of non-spherical powder on a set of pre-existing geometric features (e.g., corners, curved surfaces) are evaluateds and compared with standard spherical powders. The effect of particle collisions on the substrate is evaluated and corresponding density distributions are quantified. Non-spherical particles are generally found to exhibit higher velocities, and greater deposition track width, compared to spherical particles. Our simulations also reveal the effect of particle shape on their flow properties and final powder density. Using a custom-built DED configuration, we present preliminary experimental results of single-track depositions using both spherical and non-spherical powder particles. Based on our findings, we make a case for the use of non-spherical powders for DED applications.
Vibration Reduction in Robotic Milling Through Spindle Speed Modulation
Authors: Huschke Dominic , Melkote Shreyes N. 
Published: September 2022

Abstract
A simple strategy for the reduction of vibrations during robotic milling is proposed. Here, the vibrations are reduced through a sinusoidal variation of the spindle speed as has been done in machine tools. Experimental results show a significant reduction in the measured forces. Furthermore, an improvement of the generated surfaces through modulation of the spindle speed is observed. Based on the experimental results, a simple empirically-based control strategy for the on-line detection and reduction of vibrations through spindle speed modulation is implemented. On-line detection of vibrations is achieved through comparison of the measured and the expected forces, which are calculated using a mechanistic milling force model.
Ultra-Fine Bubbles (UFB) Inserted Novel Coconut Oil Based Metal Working Fluid (MWF) As a Sustainable Lubricant for Turning of Ti-6Al-4V
Authors: Wickramasinghe K. C. , Sasahara Hiroyuki 
Published: September 2022

Abstract
As for the first time in the advanced manufacturing research and development sector, the nano range bubbles (i.e., UFB) were injected to the coconut oil-based metal working fluid (COCO) to facilitate better cooling and lubrication condition for machining difficult to cut materials. Higher heat transfer characteristics, and better purification properties of the UFB were incorporated to the higher free fatty acid contained COCO to facilitate a favorable machining condition. Moreover, COCO ensures health and environmental friendliness and express higher potential to replace the toxic and hazardous synthetic oil based MWF (SynO) from the machining process. In this study, the cooling and lubrication performance of the UFB inserted novel COCO was clarified and benchmarked with a commercially available high performance SynO for machining Ti-6Al-4V. Eighteen percent cutting force reduction was obtained due to the hybrid effect of UFB and free fatty acid. Additionally, lower work tool interface temperature, surface roughness, and tool wear were obtained at the UFB inserted COCO compared to the SynO. Hence, the excellent tribological and rheological properties of the UFB inserted novel COCO has concluded high performance sustainable machining and provided a promising solution to conquer the challenges (i.e., low machinability index and sustainability) of machining Ti-6Al-4V.
1D and 2D Nanoparticle Assembly Compliant With Tuned 3D-Printed Topology
Authors: Jambhulkar Sayli , Song Kenan 
Published: September 2022

Abstract
Nanoparticle-included polymeric composite coatings with preferential nanoparticle alignment and oriented structures show improved functional and structural properties than randomly oriented structures, suitable for broad applications in microelectronics, automobile, defense, and space missions. Traditionally used techniques, such as drop-casting, chemically modified surfaces, and external fields, have been used for self-assembly but with several disadvantages, such as material limitations. Thus, there is a need to develop a new approach for generating hierarchical nanoparticle structures. Our unique processing is based on advanced additive manufacturing with a colloidal suspension-based deposition approach for layer-by-layer deposition of anisotropic nanoparticles. Leveraging the colloidal deposition technique, these anisotropic nanoparticles were deposited onto the 3D printed substrates with designed patterning. The presence of micropatterns generates selective nanoparticle distribution and assembly along with hydrodynamic forces to initiate the region-specific microscale patterning and nanoscale alignment of 1D and 2D nanoparticles. The polymer and nanoparticle composite film showed different deposition morphologies (e.g., straight or wavy films). In addition, the influence of nanoparticle deposition morphology on functional properties was investigated. This novel technique shows the potential to scale up microelectronics production by 3D printing electronic structures, including interdigitated devices, supercapacitors, fuel cells, and circuits.
Tooling Engineering and its Role in Manipulating Fiber Spinning and Enabled Nanostructures
Authors: Xu Weiheng , Song Kenan 
Published: September 2022

Abstract
One of the challenges to multimaterial multifunctional composite fibers is their scalability during the fabrication process. Additive manufacturing is a cost-effective tooling solution for fast prototyping fiber spinning spinnerets. This work demonstrates a laser powder bed fusion-based tri-axial spinneret that could accommodate three different materials as inner, middle, and outer layers. In the first work, continuous graphene nanoplatelets (GnPs) channel was embedded between core polymer and sheath polymer layers to simultaneously achieve electrical conductivity and high mechanical properties. This multimateiral, multichannel system is too expensive with conventional manufacturing. Our 3D printed spinneret will generate shear stress during the polymer drawing process, resulting in thinning and alignment of the two-dimensional (2D) GnPs. Similarly, in the second research, a multilayered chemiresistor for volatile organic compounds (VOCs) was fabricated in a single step. Each layer played a significant role in the overall sensor functionalities. For instance, (i) the hollow core supported inline gas transportation, (ii) the porous polymer inner layer assisted VOC diffusion, (iii) the middle electrical conductive layer responded to VOCs types and concentrations, and (iv) the outer mechanically stable layer secured sensor’s physical stability.
Digital Twin Platforms: Architectures and Functions
Authors: Huang Huiyue , Ji Tang , Xu Xun 
Published: September 2022

Abstract
In the Industry 4.0 era, many emerging technologies are being embraced by manufacturers, including Digital Twin (DT) technology. DT has been known as a critical enabler for smart manufacturing and has attracted much attention from academia and industry. Meanwhile, the demand for DT platforms is growing as they enable more effective and easy development and deployment for DTs. DT expands to different industrial scenarios, which has led to an increasing variety of DT platforms. However, there are many different understandings and concepts of DT from diverse backgrounds, so it is essential to acquire a good understanding of DT platforms. This paper aims to provide a literature review of DT platforms in manufacturing. Firstly, the current state of DT technology is presented, and a generalized definition of the DT platform is proposed. A comprehensive search for literature related to the DT platform was conducted using the Web of Science database through the definition. Meanwhile, the importance of ISO 23247, an international standard on DT frameworks for manufacturing, has been discussed to give a general view of requirements for building a DT platform. After that, typical DT platforms in both academia and industry were analyzed separately. Finally, a discussion is carried out to summarise the architecture, features, and functions that are important for DT platform development.
Metal Powders via Surface Grinding: Applicability and Performance Evaluation for Laser Sintering
Authors: Singh Dhami Harish , Panda Priti Ranjan , Saikiran Puli , Viswanathan Koushik 
Published: September 2022

Abstract
Commercial metal powders used as feedstock for additive manufacturing (AM) applications are primarily produced via gas or water atomization techniques. These are highly capital-intensive and inflexible, making the resulting powders as much as 3–10 times more expensive than corresponding cast ingots. Recently, we have demonstrated a potential alternative route for making metal powders — using surface grinding. The resulting powders have shown promise for use as stock in metal directed energy deposition (DED) processes. This work explores the applicability of these alternatively produced powders for laser sintering and related applications. Spherical metal powder particles (AISI 52100, SS 304) in the range of 5–100 microns were first produced using surface grinding. These powders were post-processed and segregated into monodisperse and polydisperse batches, representing high quality-low yield and low-quality-high yield stock, respectively. A high-power fiber laser source of 50 microns spot diameter was used to sinter these two stock powders, with nitrogen as a shielding gas, and their performance was evaluated using a range of ex situ analysis techniques. The latter included metallography, SEM/EDS and XRD analysis and was used to evaluate sintering quality in both cases, including melt pool and heat-affected zone characterization. Based on these results, we present recommendations for the use of mono- and polydisperse metallic powders and demonstrate the potential utility of using grinding as an alternative technique for the production of metal powders for laser sintering applications.
Time Domain Simulation of Turning Operations With Flank Textured Tool
Authors: Suzuki Norikazu , Fujinaka Tsubasa , Yokokawa Yuya 
Published: September 2022

Abstract
A flank textured cutting tool has been proposed to improve the chatter stability in cutting. Although excellent stability improvement effects have been reported through experimental studies, a simulation method to estimate the effects has not been established so far. In this study, we propose a time-domain simulation method that can take into account the effect of the flank face textures. In order to consider the effect of arbitrary texture geometry on the flank face, the finite element method (FEM) analysis is applied. The relationship between the chatter vibration and the process damping force is modeled, and the process damping coefficients, which represents the process damping effect quantitatively, is obtained. The process damping coefficients are calculated comprehensively by considering the regions where the amplitude and wavelength of chatter vibration can generate. To verify the validity of the proposed method, the face turning experiment was conducted with the prototyped tools consisting of two straight cutting edges. As a result of the verification experiment, it was confirmed that the chatter stability was improved by using a flank-textured tool. The proposed method could demonstrate roughly this chatter stabilization phenomenon.
Modeling and Model-Driven of Holonomic System Based on MBSE: a Case of Internet of Things Platform
Authors: Yang Hao , Zhao Chun , Shen Nana , Liu Wenzheng , Zhang Lin 
Published: September 2022

Abstract
By integrating the Internet of Things, artificial intelligence, 5G, and other new-generation electronic information technologies, the fourth industrial Revolution represented by intelligent manufacturing and industrial internet is promoted, which is the era of comprehensive intelligent industry 4.0. As a key technology of the industrial Internet, the Internet of Things (IoT) connects intelligent manufacturing complex systems and machines with built-in sensors to the network for real-time data collection, transmission, processing, and feedback, to optimize device management and production efficiency. With the increasing number and variety of IoT devices, improving the scalability and maintainability of IoT systems is a challenging demand and requires continuous efforts. This paper proposes an architecture of IoT platform based on Model-Based Systems Engineering (MBSE). In this architecture, a modeling method based on Integrated Modeling language and a model-driven method for cloud-edge collaboration platform is further proposed. The standardization, readability, and reusability of the model are used to drive the device expansion and management. The characteristics of interaction behaviours between cloud and edges are extracted, and models of Holonomic System are built by an integrated modeling language, called X language. Block Definition Diagram (BDD) of X language is used to build the static models of IoT devices and drive the platform to manage the devices. State Machine Diagram (SMD) of X language is used to build the dynamic models of process between the edges and cloud, and drive the processes of the platform. Through experiments and analysis, the feasibility and effectiveness of the X-Language-driven IoT platform are verified.