bluuebunny/crossref_metadata_2025 huggingface dataset:
Monitoring and Screening of Pipelines for Movement: A Fast and Cost-Effective Alternative for Pipeline Operators to Measure Drift in Pipelines
Authors: Schorr Michael , Kole Klaas , Foessing Ferdinand
Published: November 2019

For pipelines in the oil, gas, and mining industry, movement of pipelines is one of the main integrity hazards. This movement in most cases is caused by landslides instigated by heavy rain, earthquakes or volcanic activities. If the pipeline movement remains undetected at an early stage, it can lead to the need for costly repairs to prevent, remove, or repair potential or actual damage. Moreover, if the movements stay undetected for too long, these lines may fail and lead to catastrophic events.

This paper will illustrate what a fast and cost-effective solution to avoid these threats at an early stage looks like and how it works. It will explain the process and demonstrate the full power of this technology on the basis of a case study.

The standard solution for pipelines without a permanent position monitoring system at the time of installation includes the use of intelligent tools that are able to detect even the slightest changes in the trajectory. These inspection tools are quite expensive to run, especially when multiple screening runs are required throughout a year, e.g. before and after the rainy season or after a seismic event. Other monitoring solutions are either limited to only a specific area where the movement has already been detected at an earlier stage or lack the precision required to serve as an early warning system, such as LIDAR or satellite image comparison.

Over the years, ROSEN has developed a technology that can bridge the gap between frequent measurements and cost-effective service. It is based on an electronic gyroscope that is commonly used in Inline Inspection tools but can also be installed in readily available cleaning tools. When first run in a pipeline, it records the whole pipeline trajectory, leaving no segment undocumented. The next step is to compare these recorded pipeline routing measurements with already existing trajectory baseline data, recorded earlier by any ILI tool with an optical gyro or similar. This comparison will reveal any deviation between both trajectories and precisely determine any pipeline movement. A case study will demonstrate how the comparison is achieved.

When performing repetitive inspections, this screening comparison enables the operators to detect the onset of movements and monitor the progress of any known pipeline movement. It allows them to distinguish between stable areas from dynamic ground movements and keeps close track of changes in the pipe course. Through regular repetitions, any further development of the movement is tracked, and appropriate reactive measures can be scheduled in a timely manner. This new service provides a cost-effective and powerful early warning tool for geological pipeline integrity threats that can lead to loss of integrity, the asset, or — worst-case scenario — loss of life or environmental contamination, while at the same time, it reduces the necessity of pipeline intervention that will affect production.
Smart Factory of Industry 4.0: Connection Infrastructure, Data Acquisition, Data Processing, and Applications
Authors: Zhiqiang Zhao , Quan Chua Wei , Xiaoming Ding , Ashok Prabhu Vinayak
Published: November 2019

Smart factory adopts cyber-physical technologies integrating independent discrete systems into a context-sensitive manufacturing environment to optimize manufacturing processes using decentralized information and real-time communication. This paper presents our work in the realization of a smart factory, which comprises of a four-layer hierarchical architecture, i.e. connection infrastructure, data acquisition, data processing and smart applications. In the connection infrastructure layer, all shopfloor machines are connected through diverse protocols, IoT sensors, PLC interfaces and DNC connectors. A centralized IoT gateway supports such a scalable and adaptable connection and ensures a reliable communication among all heterogeneous manufacturing systems. In the data acquisition layer, the real-time machine and job data are acquired from shopfloor systems. Machine data indicates machines’ working condition and job data reveals the production information. The data processing layer comprises of three modules, i.e. shopfloor monitoring, data visualization and data analytics, which monitor and visualize shopfloor activities and analyze the semantics of various data using AI-based TPM engines providing the scientific indicators for next-step decisions. The smart application layer provides with several decision-making and remote control functions for shopfloor productivity and efficiency, such as predictive maintenance, shopfloor management, machine & job optimization and digital twin. The smart factory system has been implemented in the manufacturing shopfloor at Nanyang Polytechnic. The results and validation show that the system can simultaneously collect and analyze the manufacturing data from shopfloor systems, and further communicate with and control the shopfloor systems with decision-support functions. The overall shopfloor efficiency and flexibility can be significantly improved towards a smart factory of Industry 4.0.
FEM Investigation of Damage Evolution at Elevated Temperatures With Multiple Impact Hits in Vibration Assisted Nano Impact Machining by Loose Abrasives
Authors: Duong Nick H. , Ma Jianfeng , Lei Shuting , Sundaram Murali , Jahan Muhammad P.
Published: November 2019

In this paper, a computational study of a novel nanomachining process, Vibration Assisted Nano Impact machining by Loose Abrasives (VANILA), is conducted using the commercial FEM software package ABAQUS. In this novel nanomachining process, an atomic force microscope (AFM) is utilized as a platform and the nano abrasives are injected in the slurry which is located between the workpiece and the vibrating AFM probe. These nano abrasives impact the workpiece and result in nanoscale material removal. In this research, diamond particles are used as loose abrasives and the ductile mode machining is used to describe the behavior of the brittle silicon workpiece. This study aims to investigate the effects of operating temperature and number of multiple impact hits on material removal mechanism of VANILA process. The impact speed of the loose abrasives is kept constant at 200 m/s and the impact angle is fixed at 90°. The frictional coefficient during the machining is considered to be 0.05. The material removal mechanism at various operating temperatures (20°C, 100°C, 200°C, 400°C, 600°C, and 800°C) and multiple impacts are tested. It is found that the operating temperature and number of impact hits have substantial influence on material removal volume in the VANILA process.
Numerical Simulation of Pure Water Jet Machining of Al 6061-T6 With Experimental Validation
Authors: Pasken Greg , Ma Jianfeng , Jahan Muhammad P. , Lei Shuting
Published: November 2019

Pure water jets are not as effective as abrasive water jets for cutting hard materials at large scales. Pure water jets can have kerfs as small as 0.076 mm, which is approximately the width of a human hair. This allows for small detailed cuts on workpiece material [1]. Research into using pure water jet to machine aluminum at small scales is important, as this will allow small scale and precision machining of the work piece material. At micro scales, water jet cutting with typical abrasives is not possible because the abrasive particles are typically in the micron range which is around the size of the cut. At small scales a pure water jet is more effective than abrasive water jet machining, as special nanometer size abrasives would be needed at small scales. A pure water jet only needs the correct size orifice to conduct machining at the small scale. These are the reasons why this study uses a pure water jet to conduct small scale machining of aluminum. This study investigates the use of ABAQUS’s Smoothed Particle Hydrodynamics to simulate pure water jet machining of metals and compares the simulation results of a water jet machining of Al6061-T6 to experimental results using the same material. The simulation results compare favorably to experimental results with only 2.81% error in the width of the cut. The predictive FEM modeling is then conducted for other combinations of machining parameters (orifice diameter and inlet pressure). It is found that orifice diameter and inlet pressure have substantial influence on the width and depth of cut. The results of the study open new possibilities for machining metals using a pure water jet at the micrometer scale and at smaller scales.
Experimental Investigation of Stratasys J750 PolyJet Printer: Effects of Orientation and Layer Thickness on Mechanical Properties
Authors: Wei Xingjian , Bhardwaj Abhinav , Shih Chin-Cheng , Zeng Li , Tai Bruce , Pei Zhijian
Published: November 2019

The J750 PolyJet printer is the newest model of full-color, multi-material 3D printer from Stratasys. Currently, limited information is available about the effects of control factors on mechanical properties such as elastic modulus, ultimate tensile strength, and elongation. In this study, the effects of two control factors, orientation and layer thickness, on mechanical properties of samples printed by the Stratasys J750 printer are investigated. The results show that orientation significantly affects mechanical properties. Specifically, samples printed with its axial direction parallel to the direction of printing have the highest elastic modulus, and elongation, whereas samples printed with its axial direction perpendicular to the direction of printing have the highest ultimate tensile strength. Also, layer thickness makes a significant difference for mechanical properties, and larger layer thickness leads to higher ultimate tensile strength and elongation. These results would be valuable to researchers and practitioners who use J750.
Assessment of Microstructure and Mechanical Properties in Laser Cladding, Welding and Surface Polishing Through Online Monitoring of Thermal History
Authors: Nath Ashish Kumar , Gopinath Muvvala
Published: November 2019

Monitoring and controlling the microstructure, phases, and thermal stresses in laser cladding of materials which determine their mechanical properties is essential for ensuring repeatability and reproducibility in refurbishing engineering parts and building functional parts by layer-by-layer deposition in additive manufacturing process. Several studies have been reported on on-line monitoring of temperature, melt-pool geometry, and porosity etc. in laser powder deposition process, but only a few on the assessment of solidification morphology, microstructure, and thermal stresses. Since these features are dictated by the melt-pool lifetime, cooling and solidification rates, their effects on the evolution of microstructure and the state of ceramic particles in laser deposition of Ni-super alloy and metal matrix composites of WC and TiC are investigated in the current study. Good correlation exists between the thermal history monitored online and the solidification characteristics. Process maps based on the melt-pool lifetime as a function of laser cladding parameters for these materials are developed. On-line monitoring of thermal cycle is extended to laser welding of stainless steel and titanium which are difficult to join together due to the formation of brittle intermetallic phases, and laser polishing of thermal sprayed ceramic coating to develop a better understanding and control of these processes. Melt-pool lifetime is found to have significant effect on the crack growth in fusion welding and by optimizing the former the later could be mitigated. Similarly, the cooling rate in laser polishing of thermal sprayed ceramic coating is found to have significant influence on the surface roughness and residual stress. These studies show that the online monitoring of thermal history can be exploited for controlling the process quality and ensuring the repeatability and reproducibility in different laser material processing modalities.
Adaptive Tool Path Planning Strategy for 5-Axis CNC Machining of Free Form Surfaces
Authors: Mane Hrishikesh , Pande S. S.
Published: November 2019

This paper presents a curvature based adaptive iso-parametric strategy for the efficient machining of free form surfaces on 5-axis CNC machine using the flat end mill tool. One iso-parametric boundary of the surface is selected as the initial tool path. Set of cutter contact (CC) points are chosen adaptively on the initial tool path considering desired profile tolerance. Adjacent iso-parametric tool paths are computed adaptively based on the scallop height constraint unlike the traditional iso-parametric approach. The path topology is post-processed to generate the part program for 5-axis CNC machine in ISO format. The system was rigorously tested for various case studies by comparing the results with the traditional 5-axis iso-parametric tool path strategy, iso-scallop strategy and iso-planar strategy of a commercial software. Our system was found to generate efficient tool paths in terms of part quality, productivity and memory storage compared to the conventional strategies.
Multi Response Optimization and Process Capability Analysis of Fused Filament Fabrication and Chemical Vapor Smoothing Operations for Rapid Casting of Biomedical Implants
Authors: Chohan Jasgurpreet Singh , Singh Rupinder , Boparai Kamaljit Singh
Published: November 2019

Despite numerous applications of Fused Filament Fabrication (FFF), the poor surface finish, being an inherent defect, is major obstruction against utilization of prototypes for rapid casting applications. The conventional finishing methods are effective, however, the dimensional stability is compromised which is completely unacceptable in case of biomedical implants as minute dimension variations may lead to post-operative complications. The paper explores possibilities to produce chemically finished plastic replicas of hip implant through FFF which can be further used as patterns for investment casting. An advanced post-processing technique i.e. Chemical Vapor Smoothing (CVS) is tested to improve surface characteristics and dimensional accuracy of ABS replicas. The repeatability and consistency of coupled CVS and FFF processes is tested through experimentation and statistical analysis in order to endorse an alternative process for mass production of biomedical implants. The Taguchi L18 DOE was used to perform experiments which measures impact of two input parameters of FFF i.e. orientation angle and density, and four parameters of Chemical Vapor Smoothing i.e. pre-cooling time, smoothing time, smoothing time and number of cycles. The multi response optimization technique was employed to acquire optimum set of parameters yielding best surface finish, dimensional accuracy and surface hardness and hence, the overall desirability of 0.7891 was achieved. The process capability and reliability was tested at optimum settings by manufacturing twenty replicas by measuring surface roughness, hardness and dimensional accuracy at different locations of parts. It was observed that values of Cp for all the response parameters was greater than 1.33 while Cpk was greater than 1. The analysis of histograms and capability indices reveal that the FFF-CVS process carried out at optimized conditions can be defined as “statistically controlled” for fabrication of ABS replicas for biomedical applications.
An Indirect Method for the Measurement of Micro-Milling Forces
Authors: Lu Xiaohong , Wang Furui , Yang Kun , Feng Yixuan , Liang Steven Y.
Published: November 2019

Nowadays, the measurement of micro-milling forces is mainly achieved by a force transducer. However, the frequency of force signal is high, due to the spindle super-speed, which leads to failure of the micro-milling forces measurement by using common force sensors. Additionally, micro force sensors with high-resolution and high sampling frequency are preferred, but they are often expensive. To determine the average micro-milling force with low cost and high precision, we propose an indirect method, by determining the power of the main transmission system of a micro-milling machine. First, the measurement system for the micro-milling machine tool power was introduced, and various sensors were used to measure the current and voltage respectively. Then, a high-frequency sampling system based on the Labview was developed to process the current and voltage signals, and to obtain the power data of the main transmission system. Through this process, the indirect measurement of micro-milling forces was achieved. Finally, we validated the effectiveness of the developed on-line measurement system and the proposed indirect measurement method for average micro-milling force by using experiments. The proposed method is practical and low-cost, and it can lay the foundation for further research on cutting energy consumption.
Modelling of Brushing Processes
Authors: Sommerfeld Christian , Uhlmann Eckart , Hoyer Anton
Published: November 2019

Brushes consist of a body with fixed highly flexible filaments and can be used for deburring and surface finishing operations. During the brushing process, axial and tangential deflections of the highly flexible filaments lead to an adaptation to the shape of the workpiece and interaction between the filaments. The described complex contact behavior has been insufficiently investigated so far.

For a better understanding of the contact between a brush and the workpiece surface, this paper presents a model based on physical principles. The model describes the dynamic behavior of a brush in contact with different workpiece geometries and consists of separate physical descriptions for the filaments of the brush, the workpiece surface and the occurring contacts. A description of a single filament is given by a multi-body system of rigid links. The rigid links are connected by joints which approximate the material behavior of the filaments. To approximate different geometries, the workpiece surface is specified by a polynomial. Contact can occur between the filaments and the workpiece surface as well as between the filaments. For the description of the occurring contacts, Hertz’s theory of elastic contact and Coulomb’s law of friction are used. The aforementioned physical descriptions are included in the Lagrange’s equations to obtain a system of equations of motion that calculates the deflection of the filaments of the brush and the acting forces during the contact with the workpiece surface. A numerical solution to the system of equations of motion was calculated by using experimentally determined material and contact properties of the filament. A comparison of the calculated forces with experimentally determined values shows good correlations for different workpiece surfaces and process parameters. In this context, the developed model calculates the progression and the maximum value of the acting contact forces. The results show a shorter contact length of the filament lc for a circular surface compared to a plane surface, and a rise of the maximum normal force Fn with the depth of cut ae. Furthermore, consideration of the filament interactions leads to a more accurate approximation of the brush-workpiece contact. Based on the findings, the developed model can be used to calculate predictions for different brushing processes which reduce the number of time-consuming preliminary tests for the process design.
Convolutional Neural Network Using Bayesian Optimization for Laser Welding Tailor Rolled Blanks Penetration Detection
Authors: Zhang Zhehao , Zhang Yi , Luo Feng , Li Jie , Lu Cheng , Zhao Yuze , Zhang Hang , Lu Ange
Published: November 2019

Convolutional neural network (CNN) is an efficient and robust method which can accurately detect the Tailor Rolled Blank laser welding pool penetration status. To select proper hyperparameters and optimization of CNN model are black box problem. In this paper, an innovative method based on CNN to identify the penetration status of the weld pool during laser welding was introduced. A coaxial monitoring platform is set up, as well as two-class, three-class and four-class datasets are created for training and validating the CNN. The Bayesian Optimization (BO) method is used to optimize hyper-parameters which are adopted for training CNN model, determine the best parameters of depth, initial learning rate, momentum and L2 regularization. The results show that using BO method leads to accuracy improvement compared with the CNN model trained from scratch with default hyper-parameters, hence it can effectively solve the problem that the hyper-parameters of CNN are difficult to adjust. Under various laser welding parameters, high-accuracy detection of penetration status can be acquired with the test accuracy of four-class reaching 95.2%, which slightly lower than the test accuracy of the three-class and two-class.
Solar PV Power Generation Forecasting and O&M Management Applications: A Review
Authors: Zhang Chen , Yang Tao , Gao Wei , Wang Yong
Published: November 2019

The growing resource shortage and environmental concerns have forced mankind to develop and utilize renewable energy sources. The penetration of solar photovoltaic (PV) power in the electricity market has been increasing over the past few decades due to its low construction costs, zero pollution nature, and enormous support from governments. However, the intermittency and randomness of PV power also cause huge grid fluctuations which limit its integration in the system. An accurate forecasting of solar PV power generation and optimization of operation and maintenance (O&M) management are essential for further development of the solar PV farms.

A great number of related researches have been done in recent years. A review of PV power generation forecasting techniques together with their brief applications on the optimization of O&M management is presented in this paper. Machine learning methods are thought to be the most suitable at the present stage because of their ease of implementation and their capability in processing non-linear, complex data sets. Typical forecasting accuracy measures are summarized and further applications of PV power forecasting on the O&M management are also presented.
Development of a Pilot Manufacturing Cyberinfrastructure With an Information Rich Mechanical CAD 3D Model Repository
Authors: Bharadwaj Akshay , Xu Yang , Angrish Atin , Chen Yong , Starly Binil
Published: November 2019

Data driven advanced manufacturing research is dependent on access to large datasets made available from across the product lifecycle — from the concept design phase all the way down to end use and disposal. Despite such data being generated at a rapid pace, most product design data is archived in inaccessible silos. This is particularly acute in academic research laboratories and with data generated during product design and manufacturing courses. This project seeks to create an infrastructure that allow users (academia and the general public) to easily upload project data and related meta-data. Current manufacturing research must shift from siloed repositories of product manufacturing data to a federated, decentralized, open and inter-operable approach. In this regard, we build ‘FabWave’ a cyber-infrastructure tool designed to capture manufacturing data. In its first pilot implementation, we focused our attention to gathering information rich 3D Mechanical CAD data and related meta-data associated with them, with the intent to make it easier for users to upload and access product design data. We describe workflows that we have initially tested out within the two academic universities and under two different course structures. We have also developed automated workflows to gather license appropriate CAD assemblies from commercial repositories. Our intent is to create the only known largest available CAD model set within academia for enabling research in data-driven computational research in digital design, fabrication and quality control.
Study on Selective Electroless Plating of 3D Printed Counter Electrodes for Dye-Sensitized Solar Cells
Authors: James Sagil , Parikh Karan
Published: November 2019

Dye-Sensitized solar cells (DSSC) are considered to be the replacement for traditional silicon solar cells. DSSCs have been noticed widely due to its simplified material handling, easy fabrication, durability and their ability to perform better under diverse lighting conditions. However, there are significant challenges that are faced by DSSCs such as lower efficiency, chemical instability, and leakage of the electrolyte under high-temperature conditions. The fabrication of counter electrodes for DSSCs require the use of expensive materials and techniques which increases the cost as well as limits mass production. These limitations can be addressed through a cost-effective fabrication process for counter electrodes of DSSCs. This research focuses on enhancing the conductivity and catalytic activity of the counter electrodes of DSSCs through a novel selective electroless plating technique. The proposed selective electroless plating technique helps to overcome the issues of high cost, toxicity, and complex manufacturing processing of conventional DSSC. Moreover, the fabrication of the DSSC is supplemented using additive manufacturing technology. The technique further helps to enhance the performance, provide excellent design flexibility while reducing the manufacturing cost. The results of the study show selective electroless plating is an effective technique for the fabrication of low-cost counter electrodes for DSSCs. The efficiencies of the DSSC are comparable with DSSC fabricated through conventional expensive and toxic materials.
An Experimental Study on Direct Current Dieless Drawing of 4130 Steel Tubes
Authors: Nikhare Chetan P. , McMahon Paul , Aqlan Faisal
Published: November 2019

Forming of tubes in various shapes has been a major interest in vehicle, instrumentation, decoration and precision industries. Due to a variety of shapes that can be achieved by tube forming, this manufacturing process has taken a major part in research and application. In this manufacturing process, a tube with a certain diameter and thickness can be considered to shape the part. The shaping or forming can be achieved by end forming, expanding the section, bending the section, buckling the tube, and/or reducing the section. Traditionally, to form these sections the rigid tool, flexible tool or fluid pressure would be needed to shape the tube. However, tools like mandrel or plug and their sizes limit the size of the tube to be formed. In this paper, tubes are formed by stretching them while simultaneously passing the direct current through. This process has been explored earlier by heating the tube using induction heating or rotary laser heating method. However, as no dies or tools are used to form these tubes, the process is considered dieless tube drawing which involves heating the tubes and drawing them into a reduced section. This study considers two different thicknesses but the same outer diameter tubes. The drawing force, shape, and microstructure are investigated. Based on the stress-strain curve, the yield to fracture and tensile to fracture strains are determined and discussed.
Human-Robot Collaboration for Disassembly Line Balancing Problem in Remanufacturing
Authors: Liu Bin , Xu Wenjun , Liu Jiayi , Yao Bitao , Zhou Zude , Pham Duc Truong
Published: November 2019

Remanufacturing is able to reduce the environmental pollution and the manufacturing cost by recycling the end-of-life products. Disassembly is a critical step for the production process of remanufacturing. Traditional disassembly process is finished by either manual disassembly that has low efficiency or robotic disassembly that has low flexibility. Human-robot collaboration for disassembly integrates the advantages of manual disassembly and robotic disassembly, which has both high efficiency and high flexibility. For the design step of human-robot collaborative disassembly line, how to balance the human-robot collaboration workstation is an important optimization objective. The major difference between the human-robot collaboration for disassembly line and the traditional disassembly line is that it is necessary to ensure safety of the operator. This paper develops a set of models for the human-robot collaboration for disassembly line balancing problem, and the task classification and the allocation of human-robot collaborative disassembly are conducted. In order to ensure the safety of human-robot collaboration in disassembly, the safety strategy between the operator and the robot is considered in disassembly workstations. Subsequently, human-robot collaboration for disassembly line balancing problem with three objectives is solved by an improved discrete bees algorithm. Finally, the case studies based on disassembling bearing parts are conducted to verify the proposed method.
Multiphase Flow Distribution in MQL Drilling Using Optical Intensity Distribution Based Approach
Authors: Raval Jay K. , Hung Wayne N. P. , Tai Bruce L.
Published: November 2019

Oil flow distribution in Minimum Quantity Lubrication (MQL) plays an important role in the efficiency of machining processes, but it remains challenging to measure experimentally. This paper presents a new method to measure the oil flow distribution in through-channel drill bits based on the reflected light intensity. Measurements were conducted from multiple angles in order to map the flow distribution across the channel cross-sectional area. The method is applied to drill bits of a circular cross-section channel and two helix angles, 0° and 30°. The results show that, for the 0° helix angle channel, the oil concentrates near the periphery of the channel, while for 30° helix angle channel, the oil concentrates towards the center of the drill point. Furthermore, Computational Fluid Dynamics (CFD) simulation was conducted to compare with the measurement results, and it was observed that the oil distribution is correlated to the velocity field. Oil flow concentration is high in low velocity regions. Though preliminary, this study has concluded that the velocity field generated using single-phase CFD is a critical indicator for oil distribution in an MQL flow.
Development of a Multi-Directional Metal 3D Printing System Based on Direct Metal Deposition
Authors: Gao Shiming , Liao Wei-Hsin , Guo Ping
Published: November 2019

Process parameters, including deposition direction, are crucial in direct metal deposition (DMD) for microstructure formation and mechanical properties of the final part. Multi-directional deposition along with in-situ deposition control can minimize deposition anisotropy and improve dimensional accuracy. In this paper, a DMD system is developed to achieve multi-directional metal deposition by using 6 degree-of-freedom (DOF) motion of the workpiece platform rather the laser head for a highly compact design. An in-situ control strategy with two independent loops of laser focus and power is developed to control the printing process based on the feedback from real-time melt pool geometry and intensity. Experimental results have shown that the laser focus and power control can significantly improve geometrical accuracy and reduce heat accumulation. In addition, system kinematics are derived and verified for the 6-DOF hexapod to achieve multi-directional deposition. Oblique structures have been successfully printed to demonstrate the effect of optimized build direction.
A Novel Material Point Method Based Needle-Tissue Interaction Model
Authors: Li Murong , Lei Yong
Published: November 2019

Needle-tissue interaction model plays an important role in virtual surgery training, pre-intervention planning and intra-intervention guidance. Traditionally, finite element methods (FEM) had been a primary and popular way for simulation modeling. However, FEM, as a mesh-based numerical calculations, is likely to encounter numerical difficulties due to mesh distortion as needle insertion process includes damage, fracture and penetration. In this work, a novel material point method (MPM) based needle-tissue interaction model is proposed, which combines the advantages of Lagrangian and Euler methods. A simplified contact algorithm and friction model are integrated to calculate contact forces as well as the resultant tissue deformations. Both preliminary contact forces and deformation results are compared with test experiments, which show that the maximum and mean displacement errors are 0.9768mm and 0.5134mm, respectively while the mean relative errors of force is 14%. This preliminary result demonstrates that MPM has great potential in needle-tissue interaction modeling.
Modeling and Analysis of Multi-Product Manufacturing Systems With Two Machines and One Buffer
Authors: Huang Jing , Chang Qing , Arinez Jorge
Published: November 2019

The ability to process multiple product types is an important criterion for evaluating the flexibility of a manufacturing system. The system dynamics of a multi-product system is quite distinct from that of a single-product system. A modeling method for the multi-product system is proposed based on dynamic systems and flow conservation. Based on the model, this paper places its emphasis on the analysis of a two-machine-one-buffer system with two product variants. The system performance measure of a multi-product system is proposed based on production orders. The system performance of two-machine-one-buffer systems is discussed in full details. The conditions for the system achieving the best performance are derived. Finally, several numerical experiments are conducted to validate the propositions on two-machine-one-buffer system.
The Development of a Microscale Tube Hydroforming Test Bed and Novel Sealing System: A Work in Progress
Authors: Emblom William J. , Olayinka Ayotunde , Wagner Scott W.
Published: November 2019

A microscale/multiscale tube hydroforming system including tooling and controls is being designed and implemented at the University of Louisiana at Lafayette as part of a collaborative effort with Michigan Technological University. The sealing system demonstrates the evolution of the flared tube ends approach for tube end sealing to a spherical metal-on-metal sealing system. One of the features of the tooling is that while the tooling is capable of producing microscale hydroforming, the entire system can now be made using conventional CNC machining operations. Preliminary work has begun for implementing control of the hydroforming process using a PLC and a custom built continuous high pressure system capable of 415 MPa is described. Preliminary results for formed sample tubes are discussed.
Experimental Investigation of Stratasys J750 PolyJet Printer: Effects of Finish Type and Shore Hardness on Dimensional Accuracy
Authors: Wei Xingjian , Thakare Ketan , Zeng Li , Pei Zhijian
Published: November 2019

The J750 PolyJet printer is the newest model of full-color and multi-material 3D printer from Stratasys. Currently, limited information is available about the effects of control factors on dimensional accuracy of parts printed by this printer. In this study, the effects of two control factors, finish type and Shore hardness, on dimensional accuracy are investigated. The results suggest that both control factors significantly affect dimensional accuracy. Specifically, samples printed with glossy finish exhibit more accurate dimensions than those with matte finish, and larger Shore hardness value leads to better dimensional accuracy. These results would be valuable to researchers and practitioners who use the J750 3D printer.
Extrusion-Based 3D Printing of Porcelain: Feasible Regions
Authors: Bhardwaj Abhinav , Kalantar Negar , Molina Elmer , Zou Na , Pei Zhijian
Published: November 2019

3D printing processes have found several applications in automobile, aerospace, and biomedical industries. Recent development of large-scale 3D printing processes has fueled applications in the construction industry. Materials such as ceramic clay (porcelain) can now be used in additive manufacturing (AM). However, information regarding the effect of process parameters on part quality is limited. There is a need to study the effects of various parameters on the successful printing of samples for the construction industry. This paper presents an experimental study to determine the feasible parameter regions for extrusion-based 3D printing of porcelain using a Delta WASP 2040 Clay printer. The printing parameters studied are extruder height, layer thickness, print speed and air pressure. The effects of these parameters on the surface quality of the printed samples are examined. The identified feasible parameter regions from this study would provide preliminary insights on material extrusion-based 3D printing of porcelain.
Investigating Microstructural Changes and Phase Transformation During Slot Milling of Ti-6Al-4V in Dry, Flood Coolant and MQL Conditions
Authors: Khatri Ashutosh , Jahan Muhammad P. , Chen Xingbang , Ma Jianfeng
Published: November 2019

The objective of this study is to investigate the microstructural changes and phase transformation of chips and workpiece during slot milling on Ti-6Al-4V alloy in dry, flood coolant, and MQL conditions using uncoated carbide tools. The experiments were performed at varying feed rate and depth of cut with a fixed cutting speed of 50 m/min. The microstructures of the machined chips indicate that dry machining had the highest percentage of β-phase indicating higher phase transformation owing to higher tool temperature. The β-phase was found to be the least in MQL machining chips, which is very similar to the microstructural composition of un-machined surface. Although there were signs of phase transformation, there were very minimal changes in phases in the workpiece for all three machining conditions. In many cases, no change or slight decrease in β-phase was observed at the sub-surface, indicating thermal softening of the workpiece, especially in dry machining. The findings from this study confirm the fact that, high temperature close to beta transition temperature is generated during dry machining of titanium alloy, and most of heat is carried away by the chips resulting in phase transformation from alpha to beta phase in chips. However, no significant phase changes occurred into the microstructure of the workpiece in any condition, although minor thermal softening was found at the sub-surface of dry machined workpiece.
Nucleation and Boundary Layer Growth of Shear Bands in Machining
Authors: Yadav Shwetabh , Sagapuram Dinakar
Published: November 2019

An experimental study of shear band formation in cutting of metals is made using a low melting point Bi-based alloy as a model material system. High-speed imaging is used to capture the transition in the plastic flow, from laminar to shear banded flow, as a function of cutting speed. The dynamics of shear band nucleation is captured in situ and temporal evolution of localized plastic flow during shear band growth is quantitatively analyzed using an image correlation method, particle image velocimetry (PIV). The observations show that shear band nucleation is governed by a critical shear stress criterion, and accompanied by a large drop in the flow viscosity by several orders of magnitude, analogous to the phenomenon of yielding in yield-stress (Bingham) fluids. Likewise, the displacement field around a freshly nucleated shear band evolves in a manner resembling the boundary layer formation in planar flow of a Bingham fluid with a very small viscosity. Surprisingly, temperature has little influence on shear band nucleation or growth.
Experimental and Simulation Study of Single Point Incremental Forming of Polycarbonate
Authors: Rai Saurabh , Kumar Rakesh , Nirala Harish Kumar , Francis Kevin , Agrawal Anupam
Published: November 2019

Single point incremental forming (SPIF) is more accurate and economical than the conventional forming process for customized products. Majority of the work in SPIF has been carried out on metals. However, polymers are also required to shape. Polycarbonate has wide application in safety glass, bottles, automotive and aircraft industry due to its transparent as well as attractive processing and mechanical properties as compared to other polymeric plastics. In present work, the Polycarbonate (PC) sheet of thickness 1.8 mm is deformed to make a square cup at different angles. Tensile testing is done to analyze the effect of wall angle on the deformed cup. This work illustrates the effect of the SPIF process on material strength in a different directions (vertical and horizontal) of the final deformed product. Tool forces are evaluated using ABAQUS® simulation for SPIF. Numerical simulation approach is used to calculate the fracture energy, which utilizes the force-displacement curve of the specimen and is verified.
Towards Remote Teleoperation of a Semi-Autonomous Mobile Manipulator System in Machine Tending Tasks
Authors: Annem Vivek , Rajendran Pradeep , Thakar Shantanu , Gupta Satyandra K.
Published: November 2019

Increasing the level of automation in material handling tasks in small volume production operations can improve human productivity and overall manufacturing system performance. In this paper, we present a teleoperated mobile manipulator system that can be used for tending machines and transporting parts in manufacturing applications. The remotely located human operator can interact with the semi-autonomous mobile manipulator by giving it high level instructions. We have incorporated several sensors on the system to ensure safe teleoperation where the operator gives only high level motion goals to the mobile manipulator, such as waypoints for mobile base motion, and interactive marker poses for the manipulator motion. The point clouds from multiple depth cameras are used for mapping the environment. The robot plans for autonomous motions between the given way-points ensuring that the resulting motions are collision-free. We have conducted case studies with two different types of parts to be extracted from a 3D printer. The system is tested by multiple users. They were successful in completing tasks in a reasonable amount of time using our interface.
Challenges in Representing Manufacturing Processes for Systematic Sustainability Assessments: Workshop on June 21, 2018
Authors: Raman Arvind Shankar , Harper Dustin , Haapala Karl R. , Linke Barbara S. , Bernstein William Z. , Morris KC
Published: November 2019

A workshop on Challenges in Representing Manufacturing Processes for Systematic Sustainability Assessments, jointly sponsored by the U.S. National Science Foundation, the U.S. National Institute of Standards and Technology, ASTM International, the American Society of Mechanical Engineers, and the Society of Manufacturing Engineers, was held in College Station, Texas on June 21, 2018. The goals of the workshop were to identify research needs supporting manufacturing process characterization, define limitations in associated education practices, and emphasize on challenges to be pursued by the advanced manufacturing research community. An important aspect surrounded the introduction and development of reusable abstractions of manufacturing processes (RAMP), which are standard representations of unit manufacturing processes to support the development of metrics, methods, and tools for the analysis of manufacturing processes and systems. This paper reports on the workshop activities and findings, which span the improvement of engineering education, the understanding of process physics and the influence of novel materials and manufacturing processes on energy and environmental impacts, and approaches for optimization and decision-making in the design of manufacturing systems. A nominal group technique was used to identify metrics, methods, and tools critical to advanced manufacturing industry as well as highlight the associated research challenges and barriers. Workshop outcomes provide a number of research directions that can be pursued to address the identified challenges and barriers.
Design Rules and In-Situ Quality Monitoring of Thin-Wall Features Made Using Laser Powder Bed Fusion
Authors: Gaikwad Aniruddha , Imani Farhad , Rao Prahalad , Yang Hui , Reutzel Edward
Published: November 2019

The goal of this work is to quantify the link between the design features (geometry), in-situ process sensor signatures, and build quality of parts made using laser powder bed fusion (LPBF) additive manufacturing (AM) process. This knowledge is critical for establishing design rules for AM parts, and to detecting impending build failures using in-process sensor data. As a step towards this goal, the objectives of this work are two-fold:

1) Quantify the effect of the geometry and orientation on the build quality of thin-wall features. To explain further, the geometry-related factor is the ratio of the length of a thin-wall (l) to its thickness (t) defined as the aspect ratio (length-to-thickness ratio, l/t), and the angular orientation (θ) of the part, which is defined as the angle of the part in the X-Y plane relative to the re-coater blade of the LPBF machine.

2) Assess the thin-wall build quality by analyzing images of the part obtained at each layer from an in-situ optical camera using a convolutional neural network.

To realize these objectives, we designed a test part with a set of thin-wall features (fins) with varying aspect ratio from Titanium alloy (Ti-6Al-4V) material — the aspect ratio l/t of the thin-walls ranges from 36 to 183 (11 mm long (constant), and 0.06 mm to 0.3 mm in thickness). These thin-wall test parts were built under three angular orientations of 0°, 60°, and 90°. Further, the parts were examined offline using X-ray computed tomography (XCT). Through the offline XCT data, the build quality of the thin-wall features in terms of their geometric integrity is quantified as a function of the aspect ratio and orientation angle, which suggests a set of design guidelines for building thin-wall structures with LPBF. To monitor the quality of the thin-wall, in-process images of the top surface of the powder bed were acquired at each layer during the build process. The optical images are correlated with the post build quantitative measurements of the thin-wall through a deep learning convolutional neural network (CNN). The statistical correlation (Pearson coefficient, ρ) between the offline XCT measured thin-wall quality, and CNN predicted measurement ranges from 80% to 98%. Consequently, the impending poor quality of a thin-wall is captured from in-situ process data.
A New Micromechanical Model to Study Transformation Plasticity in High-Carbon Steels
Authors: Voothaluru Rohit , Bedekar Vikram , Pauskar Praveen
Published: November 2019

Hardened steels in engineering applications tend to have gradient microstructures with varying amounts of retained austenite alongside harder phases such as martensite or bainite. However, the metastable austenite can transform into martensite under mechanical loads, resulting in an inelastic strain within the material from the volumetric mismatch between FCC austenite and BCT martensite. In this work, a new constitutive formulation based upon the critical driving force for austenite transformation is presented. The model was implemented into a crystal plasticity formulation, and empirical data from in-situ neutron diffraction was used to determine the local micro-plasticity and transformation plasticity parameters. The results from finite element modeling also show that using a homogenized finite element approach could help to establish a material model that can capture the transformation plasticity within these materials with good accuracy.