bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comparison of Conventional and Ultrasonic Drilling on Cutting Force in Porcine and Human Femur
Authors: Singh Ravinder Pal , Pandey Pulak Mohan 
Published: January 2021

Abstract
Bone fractures are common in human beings, and the surgical operation performed to repair the fractured bone includes the drilling process. Axial cutting force during drilling plays an important role for success in osteosynthesis. Many processes like water jet machining, laser drilling, ultrasonic drilling, two phase drilling and rotary ultrasonic bone drilling (RUBD), have been developed to minimize the cutting force during orthopedic drilling. In the present work, a novel operation theatre compatible ultrasonic assisted rotary bone drilling machine prototype have been designed and fabricated in an attempt to reduce the cutting forces produced during orthopedic drilling. The experimental test were performed on fresh porcine bone and human femur. A comparative study was carried out between RUBD and Conventional drilling (CD), to find out the influence of rotational speed, drilling tool feed rate and drill diameter, on the cutting force produced during the drilling. The study of chip produced in RUBD and CD was also carried out with the help of scanning electron microscopy images. The result obtained by the developed machine showed that the cutting force obtained in human femur was greater (20–25 %) than porcine femur due to its greater hardness and RUBD process produced lower cutting force (20–30 %) than CD for both types of bone. The experimental results showed the increase in cutting force with decreasing rotational speed and increasing feed rate and drill diameter.
A Novel Approach to Determine the Cutting Temperature Under Consideration of the Tool Wear
Authors: Bergs Thomas , Peng Bingxiao , Schraknepper Daniel , Augspurger Thorsten 
Published: January 2021

Abstract
In metal cutting process, modeling and predicting the tool wear development has been researched for decades. Many efforts have been made to study the cutting temperature as an indicator for the tool wear behavior. However, the determination of the cutting temperature in the critical contact area in process is still a challenge.
In order to build temperature-dependent tool wear models, the temperature distribution of the workpiece was captured in this paper by an infrared thermography in orthogonal cutting of Direct Aged Inconel 718 with cemented carbide cutting tool WC-15Co. Instead of studying the temperature in critical cutting zone directly, the workpiece temperature distribution around the flank wear surface was determined inversely with the analytical Jaeger-solution based on the experimental data. The determined maximum cutting temperature on the flank wear surface has been successfully verified by FEM chip formation simulations. By means of this inverse approach, the cutting temperature on the flank surface can be determined as a function of tool wear VB. The experimental results showed that the cutting temperature increased with the increase of the tool wear VB. By means of this method, the temperature on the flank wear surface can be used as an important physical indicator to model and predict the tool wear development in future work.
Fabrication of Optical Fiber Sensors Based on Femtosecond Laser Micro Machining
Authors: Zhou Fengfeng , Jo Seunghwan , Fu Xingyu , Jun Martin Byung-Guk , Tsai Jung-Ting 
Published: January 2021

Abstract
In this research, we proposed fabrication process of optical fiber sensors using femtosecond laser and their applications. A beam of femtosecond laser was focused by an objective lens on the optical fiber. By testing different conditions, a group of machining parameters was found that achieve a minimum machining resolution of 3.2 μm. To ablate the core of the optical fiber, which is buried deep inside the cladding, precisely, part of the cladding was removed to expose the core as close as possible to the air. By making a complex pattern to modify the optical path of the laser inside an optical fiber, a sensitivity of 942.8 to 1015.6 nm/RIU was obtained for liquid refractive index sensing. For another sensor, a sensitivity of 1.38 × 105 nm/RIU was obtained which is high enough to detect small amount of refractive index change of air. It is known to be the first time that we fabricated a complex microstructure in an optical fiber to modify the propagation of the light using femtosecond laser. This research shows the possibility of a complex modification of light in an optical fiber using laser machining.
Understanding and Evaluating Naive Diagnostics Algorithms Applicable in Multistage Manufacturing From a Risk Management Perspective
Authors: Dadfarnia Mehdi , Sharp Michael , Sprock Timothy 
Published: January 2021

Abstract
The world has entered a state of unprecedented access to machine intelligence algorithms, where the ease of deployment has created a scenario where nearly every facet of life and industry has been affected by AI. Especially within industry, where the options for enacting AI systems are wide and varied, the choice of which system will work best for a given application can be daunting. Understanding when, where, and why to apply a particular algorithm can provide competitive advantage on effectiveness as well as greater trust and justification when using the algorithms’ outputs. This paper examines multistage manufacturing processes, where system complexity can greatly influence the burden of creating custom tailored monitoring solutions. Such barriers have encouraged many manufacturing small and medium enterprises (SME) to look towards generic ‘black box’ commercial software solutions, although they may lack the sufficient expertise to objectively determine which product best meets their requirements. Some of the considerations faced by SMEs are identifying tools that can successfully be deployed alongside a potential lack of sensor coverage and/or the desire for rapid system reconfiguration to accommodate smaller custom batch production sizes. In these environments, detailed analytics-based solutions are often not feasible for production equipment monitoring. This paper provides a procedure for assessing the suitability of various tools or algorithms used to evaluate production process performance based on product quality output. This paper also presents a preliminary comparative example study of several algorithms to demonstrate this process and evaluate the selected algorithms.
Class Incremental Fault Detection and Diagnosis With Unlabeled Condition Monitoring Data
Authors: Peng Xiaomeng , Jin Xiaoning , Duan Shiming , Sankavaram Chaitanya 
Published: January 2021

Abstract
Data-driven methods for fault detection and diagnostics (FDD) require a large amount of labeled data and knowledge about complete failure modes set to train a reliable classifier as well as require the same label space in an online testing phase. Typical supervised classifiers in FDD can only predict precedented faults, limiting their performance in identifying unprecedented failure modes in on-line testing data. In addition, in most applications, it may be expensive and time-consuming to obtain sufficient labeled samples. This study focuses on fault detection and diagnosis without sufficient labels or prior knowledge of the complete set of failure modes. This paper proposes a novel FDD framework using active learning and semi-supervised learning to detect both precedented and unprecedented failures with minimum labeling effort. The effectiveness of proposed approach is demonstrated and validated using a synthetic condition monitoring dataset.
Thermal Modeling in Metal Additive Manufacturing Using Graph Theory: Experimental Validation With In-Situ Infrared Thermography Data From Laser Powder Bed Fusion
Authors: Yavari Reza , Williams Richard , Cole Kevin , Hooper Paul , Rao Prahalad 
Published: January 2021

Abstract
The objective of this work is to provide experimental validation of the graph theory approach for predicting the thermal history in additively manufactured parts that was recently published in the ASME transactions. In the present paper the graph theory approach is validated with in-situ infrared thermography data in the context of the laser powder bed fusion (LPBF) additive manufacturing process. We realize this objective through the following three tasks. First, two types of test parts (stainless steel) are made in two corresponding build cycles on a Renishaw AM250 LPBF machine. The intent of both builds is to influence the thermal history of the part by changing the cooling time between melting of successive layers, called interlayer cooling time. Second, layer-wise thermal images of the top surface of the part are acquired using an in-situ a priori calibrated infrared camera. Third, the thermal imaging data obtained during the two builds were used to validate the graph theory-predicted surface temperature trends. Furthermore, the surface temperature trends predicted using graph theory are compared with results from finite element analysis. As an example, for one the builds, the graph theory approach accurately predicted the surface temperature trends to within 6% mean absolute percentage error, and approximately 14 Kelvin root mean squared error of the experimental data. Moreover, using the graph theory approach the temperature trends were predicted in less than 26 minutes which is well within the actual build time of 171 minutes.
MSEC: A Quantitative Retrospective
Authors: Sexton Thurston , Brundage Michael P. , Dima Alden , Sharp Michael 
Published: January 2021

Abstract
The ASME 2020 Manufacturing Science and Engineering Conference (MSEC) is the 15th annual meeting organized by the Manufacturing Engineering Division (MED) of ASME. MED and ASME MSEC focuses on manufacturing sciences, technology, and applications, including machining, materials processing, sensing, robotics, manufacturing system dynamics, and production optimization. As the conference has grown and evolved from its inception, it can be difficult to intuitively visualize and discuss the broad range of research topics covered by the MSEC community or to intuitively ascertain their evolution throughout time. This paper discusses a methodology to quantitatively model research communities within bodies of literature — specifically, the relative change of relevant topics within AMSE MSEC conference papers through time, from 2006 through 2018. The goal of this work is to not only present how research in MSEC has shifted over time, but in a broader sense to provide a discussion on how others can interpret results so that similar analysis can be produced within other research communities. This methodology can be used to identify overlap of communities, monitor growth or stagnation within the communities, to aid in developing new symposiums and communities of interest, or even to dictate future standards needs by looking at research trends and subsequent standard development.
Discrete Element Modeling of Scraping Process and Quantification of Powder Bed Quality for SLM
Authors: Mandloi Kuldeep , Amrapurkar Parth , Cherukuri Harish P. 
Published: January 2021

Abstract
In selective laser melting (SLM) and selective laser sintering (SLS) additive manufacturing techniques, the powder spreading process plays a key role in the quality of the manufactured parts. Some of the important parameters that influence the quality of the powder bed are the powder particle size distribution, spreader-type (roller or blade), spreader speed, size and shape of the particles. In this work, we use the discrete element method to study the effect of these parameters on the quality of the powder bed. The interactions between the particles is modeled using Hertz-Mindlin contact model as well as Hertz-Mindlin with JKR contact model with the latter being used for studies of the effect of cohesiveness of particles on powder bed quality. The Dynamic Repose Angle (DRA) is used for validating the numerical models. Our studies differ from the previous studies in that we have introduced quantitative measures for powder bed quality in the form of Discretized Volume Fraction (DVF) and Particle Flow Rate (PFR) for the layering process. With the help of these quantities, we studied various factors that affect powder bed quality: cohesiveness of the particles, spreader shape, particle size and shape, and the distribution of particle sizes. Our results indicate that as DVF and PFR decrease and DRA increases, the potential for cavities and shifting defects increases due to increase in cohesiveness. Use of fixed particle size in the simulations leads to higher DRA than when a normal distribution of particle sizes is considered. Our results show that the roller geometry provides better bed quality as compared to the blade type geometry.
A Vibration-Assisted Separation Method for Constrained-Surface-Based Stereolithography
Authors: Xu Yang , Zhu Yizhen , Sun Yifeng , Jin Jie , Chen Yong 
Published: January 2021

Abstract
For the bottom-up based stereolithography (SL) process, a separation process is required to detach the newly cured layer from the constrained surface in order to accomplish the fabrication of the current layer. Excessive separation force will cause damage to the built layers and the constrained surface. Different surface coatings, platform motions including tilting and sliding, and the utilization of oxygen-permeable films have been proposed to address the separation-related problems. Among these approaches, there is a limited study on the vibration-assisted (VA) separation method to reduce the separation force. The underlying mechanism of the VA-separation-based method remains unexplored for the SL-related additive manufacturing, and the best way to use VA separation in the bottom-up based SL process is still unclear. In this paper, a new VA separation design for the bottom-up SL process is presented. A prototype system has been built to study the VA separation mechanism in SL. Experiments on the separation performance under different parameters including vibration frequency, pre-stress level, and exposure area were conducted. Based on the collected separation force data, an analytical model based on the mechanics of fatigue fracture was built. The separation behaviors related to different shape sizes and topologies were also studied and compared. The results showed that the separation force in SL was significantly reduced using the VA-separation-based method. Furthermore, the relationship between the separation force and the separation time conforms to the stress-based fatigue model well. This study provides insights on how to choose process parameters by considering the trade-offs between separation force and building efficiency.
Nano-Scale Hardness and Abrasion Resistance of Directed Energy Deposited Co-Cr-Mo Biomedical Alloy
Authors: Liu Michael , Kuttolamadom Mathew 
Published: January 2021

Abstract
The objective of this work is to investigate the hardness and abrasion resistance of a cobalt-chromium-molybdenum (Co-Cr-Mo) alloy fabricated via directed energy deposition (DED) additive manufacturing. Being a bio-compatible alloy, Co-Cr-Mo is commonly used in biomedical implants. Hence, its small-scale tribological behavior needs to be characterized, especially when fabricated via a newer process such as DED; thus the focus at nano scale. For this, a design of experiments was utilized to investigate the relevant process parameter design space for the laser engineered net shaping (LENS) process, with an objective to manufacture structurally-integral samples. Further, the effects of these process parameters were correlated with the resulting material properties at the nanoscale (viz., hardness modulus, and abrasion resistance). Results showed certain samples with competitively-high corresponding properties when compared to traditional made Co-Cr-Mo alloys, but with a large spread in properties, as is typical for such manufacturing processes. Also, microstructural characteristics were in line with traits observed when fabricating via traditional methods. Especially worth noting is the formation of metal carbides at the boundaries of cell-shaped grains; this causes a depletion of carbon at the center of the grain and thin carbides at the boundaries, thus significantly affecting the composite properties of the material. Altogether, this work shows the promise of using LENS to fabricate tailored structurally-integral Co-Cr-Mo alloys.
Design and Evaluation of Human-Machine Interface for NEXUS: A Custom Microassembly System
Authors: Wei Danming , Hall Mariah B. , Sherehiy Andriy , Kumar Das Sumit , Popa Dan O. 
Published: January 2021

Abstract
Microassembly systems utilizing precision robotics have long been used for realizing 3-dimensional microstructures such as microrobots. Prior to assembly, such components are fabricated using Micro-Electro-Mechanical-System (MEMS) technology. The microassembly system then directs a microgripper through automated or human-controlled pick-and-place operations. In this paper, we describe a novel custom microassembly system, named NEXUS. The NEXUS integrates multi-degree of freedom (DOF) precision positioners, microscope computer vision, and micro-scale process tools such as a microgripper and vacuum tip. A semi-autonomous human-machine interface (HMI) is programmed by NI LabVIEW® to allow the operator to interact with the microassembly system. The NEXUS human-machine interface includes multiple functions, such as positioning, target detection, visual servoing, and inspection. The microassembly system’s HMI was used by operators to assemble various 3-dimensional microrobots such as the Solarpede, a novel light-powered stick-and-slip mobile microcrawler. Experimental results are reported in this paper that evaluate the system’s semi-autonomous capabilities in terms of assembly rate and yield and compare them to purely teleoperated assembly performance. Results show that the semi-automated capabilities of the microassembly system’s HMI offer a more consistent assembly rate of microrobot components.
Laser Sharpening of Carbon Fiber Microelectrode Arrays for Brain Recording
Authors: Dong Tianshu , Chen Lei , Shih Albert 
Published: January 2021

Abstract
Microwire microelectrode arrays (MEAs) are implanted in the brain for recording neuron activities to study the brain functioning mechanism. Among various microwire materials that had been applied, carbon fiber is outstanding due to its small footprint (6–7 μm), relatively high Young’s modulus, and low electrical resistance. Tips of microwire in MEAs are often sharpened to reduce insertion force. Currently, carbon fiber MEAs are sharpened with either torch burning, which can only give a uniform length of wires in an array, or electrical discharge machining (EDM), which requires circuit connection with each single carbon fiber. The sharp tip results from intense burning induced by a flame or spark, leading to poor repeatability and controllability of the sharp tip geometry. In this paper, a laser-based, non-contact carbon fiber sharpening method is proposed, which enables controllable and repeatable production of carbon fiber MEAs of custom electrode lengths, insulation stripping lengths, and sharpened tips. Path of laser movement is designed according to desired array pattern. Variation in tip geometry can be accomplished by changing laser output power and moving speed. Test with different laser parameters (output power and moving speed) were conducted. Tip sharpening results were evaluated and analyzed in terms of tip geometry and insulation stripping length. Results showed that to achieve the desired MEA with sharper tip and shorter insulation stripping length, a higher laser power with faster moving speed is preferred.
A Robotic Cell for Embedding Prefabricated Components in Extrusion-Based Additive Manufacturing
Authors: Yoon Yeo Jung , Almeida Oswin G. , Shembekar Aniruddha V. , Gupta Satyandra K. 
Published: January 2021

Abstract
By attaching a material extrusion system to a robotic arm, we can deposit materials onto complex surfaces. Robotic manipulators can also maximize the task utility by performing other tasks such as assembly or surface polishing when they are not in use for the AM process. We present a robotic cell for embedding prefabricated components in extrusion-based AM. The robotic cell consists of two 6 degrees of freedom (DOF) robots, an extrusion system, and a gripper. One robot is used for printing a part, and the other robot takes a support role to pick and place the prefabricated component and embed it into the part being printed. After the component is embedded, AM process resumes, and the material is deposited onto the prefabricated components and previously printed layers. We illustrate the capabilities of the system by fabricating three objects.
Top-Down Processing Towards Ångström-Thin Two-Dimensional (2D) Elemental Metals
Authors: Rubayat-E Tanjil Md , Agbakansi Stanley , Suero Keegan Phayden , Douglas Ossie , Jeong Yunjo , Yin Zhewen , Panaccione Wyatt , Wang Michael Cai 
Published: January 2021

Abstract
Two-dimensional (2D) materials have recently garnered significant interest due to their novel and emergent properties. A plethora of 2D materials have been discovered and intensively studied, such as graphene, hexagonal boron nitride, transitionmetal dichalcogenides (TMDCs), and other metallic compound MXenes (nitrides, phosphides, and hydroxides), as well as elemental 2D materials (borophene, germanene, phosphorene, silicene, etc.). Considering the widespread interest in conventional van der Waals 2D materials, two-dimensional metallic nanosheets (2DMNS), a recent addition to the 2D materials family, have exhibited diverse potential spanning optics, electronics, magnetics, catalysis, etc. However, the close-packed, non-layered structure and non-directional, isotropic bonding of metallic materials make it difficult to access metals in their 2D forms, unlike 2D van der Waals materials, which have intrinsically layered structure (strong in-plane bonding in addition to the weak interlayer interaction). Until now, conventional top-down and bottom-up synthesis schemes of these 2DMNS have encountered various limitations such as precursor availability, substrate incompatibility, difficulty of control over thickness and stoichiometry, limited thermal budget, etc. To overcome these manufacturing limitations of 2DMNS, here we report a facile, rapid, large-scale, and cost-effective fabrication technique of nanometer-scale copper (Cu) 2DMNS via iterative rolling, folding, and calendering (RFC) that is readily generalizable to other conventional elemental metallic materials. Overall, we successfully show a scalable fabrication technique of 2DMNS.