bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Influence of Carbon Nanotubes and Reprocessing on the Morphology and Properties of High-Density Polyethylene/Carbon Nanotube Composites
Authors: Stan Felicia , Sandu Ionut-Laurentiu , Turcanu Adriana-Madalina , Stanciu Nicoleta-Violeta , Fetecau Catalin 
Published: August 2021

Abstract
This study investigates virgin and recycled high-density polyethylene/multi-walled carbon nanotube (HDPE/MWCNT) composites using thermo-physical and mechanical characterization techniques to generate knowledge and understand recyclability of these composites. Firstly, virgin samples with 0.1–5 wt.% of MWCNTs were prepared by injection molding. Then, the HDPE/MWCNT composite waste was mechanically recycled and consecutively reprocessed by injection molding. The experimental results show that, after the first mechanical recycling and reprocessing cycle, the thermal, rheological, mechanical, and electrical properties for the recycled and virgin HDPE/MWCNT composites with 0.1–3 wt.% were rather similar within the experimental error of the measurements. In contrast, the recycled HDPE/MWCNT composites with 5 wt.% showed a reduction in viscosity, mechanical and electrical properties with recycling. After four recycling and reprocessing cycles, degradation in the Young modulus (−35%), tensile strength (−25%), elongation at break (−60%) and electrical conductivity (−2 orders of magnitude) of the HDPE/MWCNT composite with 5 wt.% was observed as compared with the virgin composite.
From an industrial perspective, it is feasible to recycle HDPE/MWCNT composite waste by mechanical recycling and use it to manufacture products with favorable mechanical properties, covering insulating, antistatic and semiconducting ranges depending on the MWCNT loading, owing to the protective effect of carbon nanotubes against thermomechanical degradation.
Multi-Robotic Disassembly Line Balancing Using Deep Reinforcement Learning
Authors: Mei Kai , Fang Yilin 
Published: August 2021

Abstract
With the continuous development of society, the speed of product upgrades is getting faster and faster, and the recycling of EOL products has great benefits to environmental protection and resource utilization. In recent years, with the rapid development of artificial intelligence (AI), more and more scholars have begun to apply reinforcement learning (RL) and deep learning (DL) to solve practical problems. This paper focuses on the application of deep reinforcement learning (DRL) in the multi-robotic disassembly line balance problem (MRDLBP). In the MRDLBP problem, for each workstation, the cycle time (CT) is determined, and the robot resources that can be accommodated are optional. Multi-objective includes minimizing workstation idle time, priority disassembly of high-demand components and minimizing energy consumption. The input model is single, and robotic resources are variable. Firstly, we formulated the mathematical model of the problem and proposed a framework for MRDLBP using DRL. In addition, we modeled the DRL system with three DRL algorithms, including deep Q network (DQN), double DQN (D_DQN) and prioritized experience replay DQN (PRDQN), to solve the problem. Finally, we build different test cases by adjusting the type of input model and the number of robot resources to test the performance of the three algorithms under different complexity conditions.
4D Printing of Complex Ceramic Structures via Controlling Zirconia Contents and Patterns
Authors: Rong Zhicheng , Liu Chang , Hu Yingbin 
Published: August 2021

Abstract
In recent years, more and more attentions have been attracted on integrating three-dimensional (3D) printing with fields (such as magnetic field) or innovating new methods to reap the full potential of 3D printing in manufacturing high-quality parts and processing nano-scaled composites. Among all of newly innovated methods, four-dimensional (4D) printing has been proved to be an effective way of creating dynamic components from simple structures. Common feeding materials in 4D printing include shape memory hydrogels, shape memory polymers, and shape memory alloys. However, few attempts have been made on 4D printing of ceramic materials to shape ceramics into intricate structures, owing to ceramics’ inherent brittleness nature. Facing this problem, this investigation aims at filling the gap between 4D printing and fabrication of complex ceramic structures. Inspired by swelling-and-shrinking-induced self-folding, a 4D printing method is innovated to add an additional shape change of ceramic structures by controlling ZrO2 contents and patterns. Experimental results evidenced that by deliberately controlling ZrO2 contents and patterns, 3D-printed ceramic parts would undergo bending and twisting during the sintering process. To demonstrate the capabilities of this method, more complex structures (such as a flower-like structure) were fabricated. In addition, functional parts with magnetic behaviors were 4D-printed by incorporating iron into the PDMS-ZrO2 ink.
Collaborative Robot Risk of Passage Among Dynamic Obstacles
Authors: Flowers Jared T. , Wiens Gloria J. 
Published: August 2021

Abstract
Industry 4.0 projects ubiquitous collaborative robots in smart factories of the future, particularly in assembly and material handling. To ensure efficient and safe human-robot collaborative interactions, this paper presents a novel algorithm for estimating Risk of Passage (ROP) a robot incurs by passing between dynamic obstacles (humans, moving equipment, etc.). This paper posits that robot trajectory durations will be shorter and safer if the robot can react proactively to predicted collision between a robot and human worker before it occurs, compared to reacting when it is imminent. I.e., if the risk that obstacles may prohibit robot passage at a future time in the robot’s trajectory is greater than a user defined risk limit, then an Obstacle Pair Volume (OPV), encompassing the obstacles at that time, is added to the planning scene. Results found from simulation show that an ROP algorithm can be trained in ∼120 workcell cycles. Further, it is demonstrated that when a trained ROP algorithm introduces an OPV, trajectory durations are shorter compared to those avoiding obstacles without the introduction of an OPV. The use of ROP estimation with addition of OPV allows workcells to operate proactively smoother with shorter cycle times in the presence of unforeseen obstacles.
A Cloud Solution for Service Oriented Workshop Management
Authors: Li Xiaobin , Yin Chao 
Published: August 2021

Abstract
Cloud manufacturing is a state-of-art networked manufacturing model with the idea and technologies of cloud computing to transform traditional production-oriented manufacturing into service-oriented manufacturing. This emerging model can make manufacturing resources, in a manner similar to traditional utilities such as water, gas and electricity, available (offered) over the internet as convenient, scalable, on-demand services to enterprises. The aim is to improve the sharing efficiency of manufacturing resources and reduce manufacturing costs in industries. In this paper, the current research of cloud manufacturing is summarized, including relevant theories, technologies and applications. A cloud solution for workshop management is proposed from a service perspective, along with its architecture and business process. The methodologies, including manufacturing resource virtualization and workshop sensor network configuration are developed to support heterogeneous data integration and effective collaboration among services in cloud. A case study is demonstrated and discussed to validate the proposed cloud service system.
Closed-Loop Control of Silicone Extrusion-Based Additive Manufacturing Based on Machine Vision
Authors: Tian Xiaoqing , Li Yaling , Ma Dingyifei , Han Jiang , Xia Lian 
Published: August 2021

Abstract
In this paper, the control of strand width uniformity in extrusion-based additive manufacturing process based on machine vision is studied. Firstly, the images of the strand width are collected frame by frame by a CCD camera. Secondly, through a series of processes of images acquisition, images processing including images filtering, images binarization and information extraction, the useful information of strand width is obtained. Then, the theoretical relationship between the strand width and printing speed is obtained through experimental research, and a control model is obtained. Finally, by using the control model and the strand width obtained from images processing, the printing speed is adjusted to an appropriate value, which eventually led to the stabilization of the strand width. The uncontrolled and logarithmic controlled, are studied in this work. The results show that the logarithmic controlled strand width is more stable than the uncontrolled strand width. Therefore, the instability of strand width in material extrusion-based additive manufacturing process can be effectively solved by machine vision control.
Performance Evaluation of Robot Polishing in Macro-Micro System Based Polishing Robot
Authors: Koto Katsuki , Tsukada Takuhiro , Ogawa Shotaro , Kakinuma Yasuhiro 
Published: August 2021

Abstract
Polishing is an important process performed in the finishing and repair processes of mechanical parts and is still a manual work of skilled workers. However, in addition to the time and cost required for manual polishing, there are also problems such as a decrease in the number of workers and health hazards due to dust generated during polishing. From these problems, the demand for automatic polishing is increasing at manufacturing sites. To automate polishing process, a macro-micro system based polishing robot which consists of a functional end-effector and industrial robot has been proposed. Regarding end effectors, mechanical design aiming for high rigidity and motion control methods for keeping the contact force constant is being researched. Meanwhile, the tool rotation speed of the spindle is independently controlled typically. Therefore, in this research, a functional polishing module capable of polishing force control and tool rotation control according to the tool feed rate is developed as the end effector. For the polishing automation, the macro-micro system based polishing robot is constructed attaching the polishing module to the industrial robot. From the viewpoint of Preston’s law, the effectiveness of the robot polishing is investigated through polishing experiments and measuring the shape of the polished surface.
Advanced Modeling of Drilling – Realistic Process Mechanics Leading to Helical Chip Formation
Authors: Lortz Wolfgang , Pavel Radu 
Published: August 2021

Abstract
There is considerable interest in the “Industry 4.0 project”. Industry hopes that a general solution of the metal removal problem will be found through the use of highly automated manufacturing data. Scientists hope that the computer will provide better models based on artificial intelligence and machine learning. Initial attempts leveraging existing models did not result in satisfactory results yet — largely because of mathematical, physical and metallurgical reasons. This paper presents a new mathematical-physical model to describe the total process mechanics from volume conservation, to friction, to metal plasticity with self-hardening or softening effects and dynamic phenomena during metal plastic flow. The softening effects are created by high energy corresponding to high strain-rate resulting in high temperatures. Furthermore, the developed equations for strain-rate discontinuities as well as yield shear stress with body forces have an interdependent relationship and lead to plastic deformation with dynamic behavior in the total chip formation zone. This plastic deformation is the only parameter that will not disappear after completing the process. This leads to the opportunity to check the theoretically developed grid deformation and compare it with practical results of the same area. In this publication this new theory will be used to analyze the complex contact and friction conditions between the chip and tool edge of a twist drill during operation. It will be shown that the existing conditions are leading to high wear at the corner edge and flank wear at the tool cutting edge. In addition, the existing temperatures can be estimated and compared with practical measurements, and all these complex and difficult conditions create a helical spiral chip, which could be developed as it will be presented in this paper.
Characterizing the Conductivity of Aerosol Jet Printed Silver Features on Glass
Authors: Ratnayake Dilan , Curry Alexander Thomas , Qu Chuang , Usher John , Walsh Kevin 
Published: August 2021

Abstract
Aerosol Jet Printing shows a lot of promise for the future of printable electronics. It is compatible with a wide range of materials and can be printed on nearly any type of surface features because of its 3–5 mm standoff distance from the substrate. However, nearly all materials printed require some form of post-sintering processing to reduce the electrical resistance. Many companies develop these materials, but only provide a narrow range of post processing results to demonstrate the achievable conductivity values. In this paper, a design of experiment (DOE) is presented that demonstrates a way to characterize any material for Aerosol Jet Printing during and after post sintering processing by measuring conductivity with different time and temperature values. From these results, a linear regression model can be made to develop an equation that predicts conductivity at a given time-temperature value. This paper applies this method to Clariant Ag ink and sinters silver pads in an oven. A linear regression model is successfully developed that fits the data very well. From this model, an equation is derived to predict the conductivity of the Clariant Ag ink for any time-temperature value. Although only demonstrated with an oven and one type of ink, this method of experimentation and model development can be done with any material and any post processing method.
Conical Thermoplastic Composite Anisogrid Lattice Structure by Innovative Out-of-Autoclave Molding Process
Authors: Quadrini Fabrizio , Santoro Daniele , Iorio Leandro , Santo Loredana 
Published: August 2021

Abstract
A new manufacturing process for thermoplastic (TP) composite parts has been used to produce conical anisogrid composite lattice structure (ACLS). An out-of-autoclave (OOA) process has been prototyped by using the compaction exerted by a heat-shrink tube after its exposition to heat in oven. Narrow thermoplastic prepreg tapes have been wounded on a metallic conical patterned mold at room temperature; then, the conical structure has been inserted in the heat-shrink tube and heated. TP unidirectional prepreg tapes have been used with polypropylene matrix and glass fibers. After molding, the TP ACLS has been tested under axial and transverse compression. Conical adapters were used in the transverse loading condition to allow uniform application of the load. Density measurement has been also performed to assess the quality of the OOA process. Results of this study show that TP ACLS with complex shape may be produced with OOA solutions without affecting mechanical performance. In fact, porosity levels of the consolidate ACLS are comparable with the initial prepreg despite of the absence of vacuum during molding. Moreover, high compressive stiffness was measured along both directions without observing damages, buckling or cracks in multiple tests. In the future, this kind of technology could be used for larger ACLSs by substituting the heat-shrink tube with a narrow tape to be wound as well after lamination.
A Computational Study on Novel Runner Extension Designs via 3D Sand-Printing to Improve Casting Performance
Authors: Stebbins Ryan , King Philip , Manogharan Guha 
Published: August 2021

Abstract
3D sand-printing (3DSP) has become more popular in foundry applications due to its ability to create complex gating geometries. Since filling related defects, like entrained air and bi-films, are most commonly caused by high melt velocity and turbulence, recent 3DSP research has focused on designing gating systems to reduce melt velocity and turbulence. However, there have been no reported efforts on advancements in the design of runner extensions as a method to improve casting quality, despite its tremendous impact on the initial metal flow characteristics. The ability to fabricate 3DSP molds allow for unique runner extension designs that aid in improving casting quality. This paper is the first study known to the authors that investigates novel 3D runner extension designs to determine the most effective design for reducing sand casting defects. Based on literature review and design principles developed for 3D sprue geometries, six different runner extensions were studied using Computational Fluid Dynamics (CFD) modeling for foundry pouring conditions. The designs were evaluated on their ability to reduce defects like entrained air and bubbles, as well as to prevent backflow and reflected waves. An unweighted ranking matrix and comparison matrix against the control (straight runner extension) has been established based on air entrainment, tracer, voids, and extension volume. The results showed that the by-pass principal and surge control systems are effective at reducing reflective waves and controlling the ingate flow. The novel 3D duckbill trap extension proposed in this study had the best overall performance based on a 16% reduction in entrained air and a 71% reduction in void particles in the casting volume compared to the control extension design. These results provide a framework to further optimize runner extensions, utilize the advantages of 3D Sand-Printing technology to improve mechanical strength and reduce filling defects in sand-casting.
Development of Intertwined Infills to Improve Multi-Material Interfacial Bond Strength
Authors: Mustafa Irfan , Kwok Tsz-Ho 
Published: August 2021

Abstract
Recently the availability of various materials and ongoing research in developing advanced systems for multi-material additive manufacturing (MMAM) have opened doors for innovation in functional products. One major concern of MMAM is the strength at the interface between materials. This paper hypothesizes overlapping and interlacing materials to enhance the bonding strength. To test this hypothesis, we need a computer-aided manufacturing (CAM) tool that can process the overlapped material regions. However, existing computational tools lack key multi-material design processing features and have certain limitations in making full use of the material information, which restricts the testing of our hypothesis. Therefore, this research also develops a new MMAM slicing framework that efficiently identifies the boundaries for materials to develop different advanced features. By modifying a ray tracing technology, we develop layered depth material images (LDMI) to process the material information from computer-aided design (CAD) models for slicing and process planning. Each sample point in the LDMI has associated material and geometric properties that are used to identify the multi-material regions. Based on the material information in each slice, interlocking joint (T-Joint) and interlacing infill are generated in the regions with multiple materials. Tensile tests have been performed to verify the enhancement of mechanical properties by the use of overlapping and interlacing materials.
Study of Formability Limit Based on Ductile Damage Criteria of Incremental Sheet Forming of Titanium Grade 2 Sheet
Authors: Pal Mainak , Pandya Vandit , Agrawal Anupam 
Published: August 2021

Abstract
Incremental sheet forming (ISF) process is an alternative and advanced sheet metal forming technique, well-known due to its flexible and die-less method of forming compared to other traditional forming methods. It is a modern concept-based sheet forming technique adaptive to develop both simple and complicated shapes/components successfully. The clamped metal sheet undergoes small incremental deformations via layer by layer line movement of ball point type hemispherical tool with the help of numerically controlled (NC) user pre-defined definite toolpath. Numerical simulation is an effective method to study the forming process and predict the formability limit in ISF. In this paper, ductile damage failure criteria has been used to investigate the forming limit diagram (FLD) of commercially pure Titanium grade 2 (CP-Ti Gr2) sheet through finite element simulation in ABAQUS® software. Truncated conical shape geometry with three different incremental step depth (Δz) at constant wall angle has been formed. Simulation results of the FLD have been validated and compared with the experimental data from the literature. Finite element analysis (FEA) for predicting the sheet thickness variation along the forming depth and process forming forces also have been carried out. Higher step depth resulted in better formability of the titanium sheet with less sheet thickness reduction. Forming forces (Fz) with smaller step depth showed good results as compared to other two step depths.
Simulation and Characterization of Nanoparticle Thermal Conductivity for a Microscale Selective Laser Sintering System
Authors: Grose Joshua , Dibua Obehi G. , Behera Dipankar , Foong Chee S. , Cullinan Michael 
Published: August 2021

Abstract
Additive Manufacturing (AM) technologies are often restricted by the minimum feature size of parts they can repeatably build. The microscale selective laser sintering (μ-SLS) process, which is capable of producing single micron resolution parts, addresses this issue directly. However, the unwanted dissipation of heat within the powder bed of a μ-SLS device during laser sintering is a primary source of error that limits the minimum feature size of the producible parts. A particle scale thermal model is needed to characterize the thermal properties of the nanoparticles undergoing sintering and allow for the prediction of heat affected zones (HAZ) and the improvement of final part quality. Thus, this paper presents a method for the determination of the effective thermal conductivity of metal nanoparticle beds in a microscale selective laser sintering process using finite element simulations in ANSYS. CAD models of nanoparticle groups at various timesteps during sintering are developed from Phase Field Modeling (PFM) output data, and steady state thermal simulations are performed on each group. The complete simulation framework developed in this work is adaptable to particle groups of variable sizes and geometric arrangements. Results from the thermal models are used to estimate the thermal conductivity of the copper nanoparticles as a function of sintering duration.
Two-Dimensional Image Based Product Connector Recognition for Robotic Disassembly in Remanufacturing
Authors: Hu Yang , Wang Yalin , Xu Feng , Yao Bitao , Xu Wenjun , Feng Hao 
Published: August 2021

Abstract
Remanufacturing has received increasing attention for environmental protection and resource conservation considerations. Disassembly is a crucial step in remanufacturing, is always done manually which is inefficient while robotic disassembly can improve the efficiency of the disassembly. Aiming at the problem of product connector recognition during the robotic disassembly process, we analyze the template matching and feature matching principles based on two-dimensional images. To reduce the computational complexity of traditional template matching, a stepwise search strategy combining coarse and fine is proposed. Based on this a product connector recognition algorithm based on fast template matching and a product connector recognition algorithm based on feature matching is designed. Taking bolts and hexagon nuts as examples, the recognition effects of the two algorithms are compared and analyzed.