bluuebunny/crossref_metadata_2025_split huggingface dataset:
Fused Filament Deposition of Silicone Blends With Tunable Mechanical Properties
Authors: Jaipean Bryson , Estelle Kevin , Tandel Ruchira , Gozen B. Arda 
Published: January 2021

Abstract
Addition-cured silicones are widely used in emerging soft robotics and wearable device technologies which can benefit greatly from the customizability offered by versatile 3D printing methods such as fused filament deposition (FFD). However, precursors of addition-cured silicones, particularly the ones with high compliance, are generally incompatible with 3D printing due to their rheological properties. Several silicones with rheological properties suitable for 3D printing lacks the compliance necessary for many application. This paper explores FFD of composite silicone inks consisting of two types of addition cured silicone precursors with different rheology and mechanical properties: inherently 3D-printable Dow SE-1700 with low compliance and non-printable Smooth-On EcoFlex 00-10 with high compliance. Specifically, blended ink rheology, morphology and the mechanical properties of the printed structures are experimentally studied. It was shown that 3D printable rheology was maintained in inks that contained up to 33% EcoFlex 00-10, even though the reduction in the elastic moduli and the yield stress were noted. Inclusion of EcoFlex 00-10, led to smoother side walls of the printed structures at an optimal composition. Through varying the relative composition of the two components, 100% tensile moduli of the printed structures can be controlled between 959–347 kPa. Several issues are noted associated with the transient behavior of the blended inks due to short pot life of the EcoFlex 00-10.
Fabrication of a Graded Micropillar Surface for Guided Cell Migration
Authors: Krishnamoorthy Srikumar , Xu Changxue 
Published: January 2021

Abstract
The migration of cells is caused by the interaction of cells and the local microenvironment around them, such as changes in stiffness, chemical gradients etc. The local topography of substrates in contact with cells is a key factor that regulates the migration of cells. The interaction between the topography of the substrate and cells is crucial for the understanding of tissue development and regeneration. In this paper, the fabrication of a graded micropillar substrate for studying topography-based cell migration is described in detail. The fabrication protocol comprises of the utilization of dynamic maskless lithography system, capillary molding, and corona arc surface treatment. The fabricated micropillar substrate has been shown and the cells have been successfully seeded on the substrate. Guided cell migration on the substrate with graded microtopography has been demonstrated to occur from the sparser zone to the denser zone. Moreover, some examples of potential applications are provided.
Demand Response for Sustainable Manufacturing Systems Considering Buffer Content Utilization
Authors: Zhou Xue , Zhao Jing , Yun Lingxiang , Sun Zeyi , Li Lin 
Published: January 2021

Abstract
Due to the rapidly rising energy price and increase in public awareness of environmental protection, the manufacturers are facing the ever-increasing moral and economic pressures from the community, government, and society. Hence, the significance of energy related studies in manufacturing systems has gradually become recognized in recent years. In most cases, the techniques to reduce the energy consumption are either renewable energy methods (solar, tidy and wind) or improving energy efficiency for existing energy modes. The approach to cut the energy related costs for manufacturing plants has not been comprehensively considered, although the same methods such as demand response and load shedding have been widely studied in the building research. In this paper, a brief analysis of the unique challenges to the application of the demand response technique in manufacturing systems is presented. The feasibility and profitability of demand response in manufacturing systems under the constraint of system throughput are studied and explored. An initial study about customer side decision making on demand response is introduced, and a numerical case of a section of a manufacturing system is used to show the benefits of the proposed idea, which illustrates over 6% bill reduction and over 5% consumption reduction during a billing cycle without sacrificing system throughput.
Spatially-Constant Material Removal Control Under Variable-Speed Robotic Sanding
Authors: Devine Cameron , Garbini Joseph , Devasia Santosh 
Published: January 2021

Abstract
During manufacturing, minor flaws in the surface of commercial airplane interior panels are often corrected using hand sanding, sometimes leading to repetitive stress injuries. Robotic sanding is an attractive option to mitigate these injuries. However, in preprogrammed automated sanding, both the sander path and the speed along that path are predetermined. Such fixed automation has limited effectiveness due to the part-to-part variability of surface condition. In addition, in typical fixed automation, a constant contact force and path speed are used to maintain constant material removal depth. Teleoperated robotic sanding allows a skilled operator to monitor the process and the condition of the surface in real time to correct the individual flaws. However, during teleoperated sanding, the path and speed along the path are inherently both time-varying and unknown a priori. The principal contribution of this work is to facilitate precision teleoperated sanding by developing a process model and control strategy that ensures constant material removal depth along the sanding path. Experimental results, with and without the proposed contact-force adjustments, for the same variable speed motion of the sander, shows 65% improvement in spatial variation of material removal with the proposed approach.
Study of Aging Heat Treatment Parameters for 7050 and 7075 Aluminum Alloys
Authors: James Sagil , Roy Ambarneil 
Published: January 2021

Abstract
Among the different commercially used Aluminum (Al) alloys, the 7000 series offers some of the highest mechanical properties making them the material of choice for several critical engineering applications. These Al alloys often required to undergo a heat treatment (HT) process to enhance their mechanical and metallurgical properties to the desired levels. Currently, there is a growing need to find the optimal operational parameters for the HT process of Al 7000 series alloys. The operators have to resort to a start/stop approach, while intermittently evaluating and testing the mechanical properties until the desired level is reached. Among the various steps, aging is the final and often the longest step in the HT process. Consequently, the age soak time parameter needs to be narrowed to the smallest possible operating range for industrial applications. This study aims to experimentally optimize the age soak time of Al 7000 series alloys (7050-T74 and 7075-T73) by measuring its hardness, electrical conductivity (EC), fatigue properties. The study found that the optimal age soak times for 7050-T74 and 7075-T73 Al alloys are between 24–27 hours and 22–24 hours, respectively. The results of the study are subsequently confirmed using the grain flow and grain direction analysis. The results of this study are crucial in extending the applications of Al 7000 series alloys in several critical engineering industries.
Human Point Cloud Inpainting for Industrial Human-Robot Collaboration Using Deep Generative Model
Authors: Wang Le , Xie Shengquan , Xu Wenjun , Yao Bitao , Cui Jia , Liu Quan , Zhou Zude 
Published: January 2021

Abstract
In complex industrial human-robot collaboration (HRC) environment, obstacles in the shared working space will occlude the operator, and the industrial robot will threaten the safety of the operator if it is unable to get the complete human spatial point cloud. This paper proposes a real-time human point cloud inpainting method based on the deep generative model. The method can recover the human point cloud occluded by obstacles in the shared working space to ensure the safety of the operator. The method proposed in this paper can be mainly divided into three parts: (i) real-time obstacles detection. This process can detect obstacle locations in real time and generate the image of obstacles. (ii) the application of the deep generative model algorithm. It is a complete convolutional neural network (CNN) structure and introduces advanced generative adversarial loss. The model can generate the missing depth data of operators at arbitrary position in the human depth image. (iii) spatial mapping of the depth image. The depth image will be mapped to point cloud by coordinate system conversion. The effectiveness of the method is verified by filling hole of the human point cloud occluded by obstacles in industrial HRC environment. The experiment results show that the proposed method can accurately generate the occluded human point cloud in real time and ensure the safety of the operator.
Numerical Simulation and Experimental Validation of Pure Water Jet Machining of Ti-6Al-4V
Authors: Pasken Greg , Ma J. , Jahan Muhammad P. , Lei Shuting 
Published: January 2021

Abstract
The most common problem when machining titanium using traditional metal cutting processes is that tools rapidly wear out and need to be replaced. This study examines the ability of a pure water jet to machine Ti-6Al-4V via simulations using ABAQUS’s Smoothed Particle Hydrodynamics (SPH). These simulations are then validated experimentally at two pressures, 138 MPa and 317 MPa. Using a Maxiem water jet built by Omax, experiments are conducted by creating a series of 5 lines that are 5 inches (127 mm) long placed 0.5 inches (12.7 mm) apart on a 1 mm thick Ti-6Al-4V workpiece. Predictive modeling is also conducted using the two additional pressures 400 MPa and 621 MPa as well as three orifice diameters 0.254 mm, 0.3556 mm, and 0.4572 mm. The simulations are validated at both pressures and had a percent error less than 2.6% which were within the standard deviation of the experimental results. The predictive modeling indicates that the pressures above 317 MPa create a near identical percent increase from the orifice diameter but the kerf has a more noticeable decrease in width of cut as the pressure increases. The 138 MPa has the smoothest surface profile compared to the other pressures. The volume of removed material decreases as the pressure increases but the material removal rate (MRR) increases as the pressure increases. This is due to the velocity of the water increasing as the pressure increases causing a lower run time. The 621 MPa is the best pressure to machine Ti-6Al-4V as it has a better MRR than the other pressures used in the predictive modelling.
Friction Stir Forward Extrusion: Small Scale Tooling Development and Preliminary Test Results
Authors: Emblom William J. , Huval Dillon J. , Oustalet Dylan J. , Rubi Jacob , Olayinka Ayotunde , Wagner Scott W. , Wahab Muhammad A. 
Published: January 2021

Abstract
Preliminary work on a new research project frequently entails proof-of-concept tests and modeling. The current project is investigating friction stir processing to produce small macroscale aluminum solid cylinders. The tooling was designed to be used in a 2-HP Bridgeport Mill for initial proof of concept tests and then later used in a CNC mill. The work pieces for these first tests were A1100 annealed ½ in. (12.7 mm) diameter work pieces, the final diameters were ¼ in (6.35 mm), and 3/18 inches (9.53 mm). The nominal speeds of the mill were 850 and 1000 RPM and were limited by the power available and the age of the mill. The paper discusses tooling design, instrumentation, preliminary results, and analysis. Temperature was measured during the tests but force was not measured due to limits to the available instrumentation. The future directions of this project are discussed.
Numerical Simulation of Pulsed Water Jet Machining of Al 6061-T6 and Ti-6Al-4V
Authors: Pasken Greg , Ma J. , Jahan Muhammad P. , Lei Shuting 
Published: January 2021

Abstract
Aluminum, known for its low density and its ability to resist corrosion through passivation, is vitally important to the aerospace industry, transportation, and building industries. The most common problem when machining titanium using traditional metal cutting processes is that tools rapidly wear out and need to be replaced since the variation of chip thickness, high heat stress, high-pressure loads, spring back, and residual stress result in higher tool wear and worse machined surface integrity. Thus, a technique that allows high precision machining of titanium that preserves the integrity of the machined material, reduces tool wear or even eliminates tooling entirely is an important advance. This study examines the ability to machine Al 6061-T6 and Ti-6Al-4V using a pulsed water jet by simulation using ABAQUS Smoothed Particle Hydrodynamics (SPH). The aluminum results showed that between the three diameters the 0.4572 mm orifice is a better choice based upon the percent increase from the orifice diameter; but based off of the kerf, the 0.3556 mm is the better choice. The results show that the 621 MPa has the highest MRR for Al 6061-T6, 232.1 mm3/s. For the four pressure simulations for the titanium, the 138 MPa pressure has the smoothest surface. Even though the volume removed decreased as the pressures increased for the titanium, the MRR increased due to the shorter machining times with 621 MPa pressure having the second highest MRR, 170.051 mm3/s. The results show that overall the 621 MPa is the best choice from the parameters chosen for machining Al 6061-T6 and Ti-6Al-4V.
Embedded Sensing Capabilities in an FDM Printed Object
Authors: McGrady Garrett , Jain Neel , Jackson Douglas , Walsh Kevin 
Published: January 2021

Abstract
The objective of this paper is to demonstrate the flexure properties of ABS plastic in a 3D printed object as a process to enable embedded pressure sensing capabilities. Developing the potential for non-static 3D parts broadens the scope of the fused deposition modeling (FDM) process to include printing ‘smart’ objects that utilize intrinsic material properties to act as microphones, load sensors, accelerometers, etc. In order to demonstrate a strain-based pressure transducer, strain gauges were embedded either directly on top or in the middle of a flexible ABS diaphragm.
Securing a strain gage directly on top of the diaphragm traced a reference pressure more closely than diaphragms with the strain gage embedded halfway into the diaphragm. To prevent temperature-related drift, an additional strain gage was suspended above the secured gage, inside the 3D printed cavity. The additional gage allowed for a half-bridge circuit in lieu of a quarter-bridge circuit, which minimized drift due to temperature change. The ABS diaphragm showed no significant signs of elastic hysteresis or nonlinear buckling. When sealed with 100% acetone, the diaphragm leaked ∼50x slower than as-printed sensors. After pressurizing and depressurizing the devices multiple times, they output pressure readouts that were consistent and repeatable for any given pressure within the operational range of 0 to 7psi.
The repeatability of each of the final generation sensors indicates that ‘smart’ objects printed using an FDM process could be individually calibrated to make repeatable recordings. This work demonstrates a concept overlooked previous to now — FDM printed objects are not limited to static models, which lack dynamic motion of the part as an element of design. Altering FDM’s bottom-up process can allow for easily embedding sensing elements that result in printed objects which are functional on the mesoscale.
Order Fulfilment Progress Estimation for Collaborative Manufacturing Enabled by Industrial Internet of Things
Authors: Peng Chen , Zhang Zheng , Peng Tao , Tang Renzhong , Zhao Xiaoliang 
Published: January 2021

Abstract
It has been recognized by manufacturing companies that working collaboratively is the way to advance their competiveness. Order fulfillment estimation addresses the issue of uncertainty from vendors. It is significant for collaborative manufacturing, which enhances companies’ responsiveness to market dynamics. In a data-rich scenario, order fulfillment estimation can be performed based on information extracted from data acquisition devices, such as smart sensors. The analysis result should serve the decisions-making of the production planning, and an indicator should be passed along the production chain even to its end customer for collaborative purpose. In the meanwhile, the manufacturer’s sensitive or confidential information is excluded to avoid risks. This article studies a method to effectively evaluate the order fulfillment process in an Industrial Internet of Things (IIoT) facilitated make-to-order production system. An order fulfilment progress (OFP) indicator is proposed to dynamically represent the fulfillment progress, and its estimation mathematical models are proposed. To improve the practicability of the OFP indicator in production, the influence of abnormal event scenarios are discussed to modify the OFP. A case study presented in this research demonstrates the proposed indicator with consideration of job in process (JIP) is promising comparing to conventional indicators that are represented by the proportion of finished over total products.
Parametric Study and Multi-Criteria Optimization in Laser Directed Energy Deposition of 316L Stainless Steel
Authors: Kersten Samuel , Praniewicz Maxwell , Elsayed Omar , Kurfess Thomas , Saldana Christopher 
Published: January 2021

Abstract
Directed Energy Deposition (DED) is an additive manufacturing technique in which a heat source is used to generate a small pool of molten material while powder feedstock is fed into the melt pool to create tracks of raised material on the surface of a part. Given the appropriate process parameters for the chosen material system and process conditions, fully dense complex geometric features are able to be constructed. In order to generate a high quality clad, two main criteria must be met: sufficient bonding with the substrate with minimized dilution of the clad by the base material and minimal porosity. Track shape is a key indicator in determining the quality of the process.
This paper evaluates the influence of several of the key processing parameters — laser power, scanning speed, and powder mass flowrate — on single-clad track morphology. An analysis of variance (ANOVA) is performed to evaluate the significance of the main input parameters and the interactions between multiple parameters. A second-order polynomial model is then fit to the data to allow for predictive modelling of track shape based on a set of inputs. Finally, a multi-criteria cost function is generated, and sequential quadratic programming is performed to solve the objective function. Through these operations, the correct combination of processing parameters can be selected in order to generate a cladded track with desirable geometric traits.
Human-Robot Collaboration in Smart Manufacturing: Robot Reactive Behavior Intelligence
Authors: Nicora Matteo Lavit , Ambrosetti Roberto , Wiens Gloria J. , Fassi Irene 
Published: January 2021

Abstract
To enable safe and effective human-robot collaboration (HRC) in smart manufacturing, seamless integration of sensing, cognition and prediction into the robot controller is critical for real-time awareness, response and communication inside a heterogeneous environment (robots, humans, equipment). The specific research objective is to provide the robot Proactive Adaptive Collaboration Intelligence (PACI) and switching logic within its control architecture in order to give the robot the ability to optimally and dynamically adapt its motions, given a priori knowledge and predefined execution plans for its assigned tasks. The challenge lies in augmenting the robot’s decision-making process to have greater situation awareness and to yield smart robot behaviors/reactions when subject to different levels of human-robot interaction, while maintaining safety and production efficiency. Robot reactive behaviors were achieved via cost function-based switching logic activating the best suited high-level controller. The PACI’s underlying segmentation and switching logic framework is demonstrated to yield a high degree of modularity and flexibility. The performance of the developed control structure subjected to different levels of human-robot interactions was validated in a simulated environment. Open-loop commands were sent to the physical e.DO robot to demonstrate how the proposed framework would behave in a real application.
Corrosion Evolution in Al/Steel Dissimilar Joints
Authors: Wen Weiling , Liu Tian , Banu Mihaela , Simmer Joseph , Carlson Blair , Hu S. Jack 
Published: January 2021

Abstract
Al/steel joints are increasingly used in the automotive industry to meet the requirement of energy saving and emission reduction. Among various joining technologies, self-pierce riveting (SPR) and resistance spot welding (RSW) are two promising technologies to fabricate dissimilar joints with stable and high mechanical performance. However, corrosion will occur in these joints inevitably due to different electrochemical properties, which can degrade the surface quality and the mechanical performance, including strength, ductility, etc. In this paper, 1.2 mm AA6022 and 2.0mm HDG HSLA340 are joined by SPR and RSW. After the fabrication of these Al/steel joints, cyclic corrosion tests are performed, which lasts 26 cycles and 48 cycles. By comparing the microstructure of the joints with and without corrosion, different corrosion mechanisms in SPR and RSW are revealed, including the corrosion initiation and propagation.
Numerical Investigation of Various Coaxial Nozzle Designs for Direct Laser Deposition
Authors: Gabor Theodore T. , Joe Hang-Eun , Akin Semih , Jun Martin Byung-Guk , Kim Kyung-Han , Park Jong-Kwon 
Published: January 2021

Abstract
Direct Laser Deposition (DLD) is a form of metal-based additive manufacturing. The DLD process involves ejecting powder out of a nozzle by means of an compressed gas and irradiating a laser beam to heat up the powder and the substrate. During the powder spray ejection, tight focusing of the powder stream has the potential to improve the DLD process by reducing powder wastage. Thus, nozzle design and computational fluid dynamics (CFD) analysis of the design parameters become important. This study focuses on the numerical simulation of the gas-solid flow inside a coaxial DLD nozzle and how design features of the nozzle affect powder focusing. The two-phase gas/powder flow was analyzed using a Eulerian-Lagrangian scheme. A total of twelve designs were simulated and analyzed through CFD simulation, with features such as inlet angle, inlet offset, and the presence and shape of flow-straightening grooves considered. It was determined that geometry reducing particle tangential velocity such as flow-straightening grooves produce the best focusing effects, whereas offset inlets without the presence of grooves reduces focusing by maximizing particle swirling. Finally, the simulations show that the distribution of powders within the nozzle is also affected by nozzle inlet angle, with horizontal inlets providing more even distribution over inlets angled towards the nozzle tip.