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Full-Text Articles in Mechanical Engineering

Encoding Invariances In Deep Generative Models, Viraj Shah, Ameya Joshi, Sambuddha Ghosal, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde Jun 2019

Encoding Invariances In Deep Generative Models, Viraj Shah, Ameya Joshi, Sambuddha Ghosal, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde

Baskar Ganapathysubramanian

Reliable training of generative adversarial networks (GANs) typically require massive datasets in order to model complicated distributions. However, in several applications, training samples obey invariances that are \textit{a priori} known; for example, in complex physics simulations, the training data obey universal laws encoded as well-defined mathematical equations. In this paper, we propose a new generative modeling approach, InvNet, that can efficiently model data spaces with known invariances. We devise an adversarial training algorithm to encode them into data distribution. We validate our framework in three experimental settings: generating images with fixed motifs; solving nonlinear partial differential equations (PDEs); and ...


Encoding Invariances In Deep Generative Models, Viraj Shah, Ameya Joshi, Sambuddha Ghosal, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde Jun 2019

Encoding Invariances In Deep Generative Models, Viraj Shah, Ameya Joshi, Sambuddha Ghosal, Balaji Pokuri, Soumik Sarkar, Baskar Ganapathysubramanian, Chinmay Hegde

Mechanical Engineering Publications

Reliable training of generative adversarial networks (GANs) typically require massive datasets in order to model complicated distributions. However, in several applications, training samples obey invariances that are \textit{a priori} known; for example, in complex physics simulations, the training data obey universal laws encoded as well-defined mathematical equations. In this paper, we propose a new generative modeling approach, InvNet, that can efficiently model data spaces with known invariances. We devise an adversarial training algorithm to encode them into data distribution. We validate our framework in three experimental settings: generating images with fixed motifs; solving nonlinear partial differential equations (PDEs); and ...


Fault Adaptive Workload Allocation For Complex Manufacturing Systems, Charlie B. Destefano May 2019

Fault Adaptive Workload Allocation For Complex Manufacturing Systems, Charlie B. Destefano

Theses and Dissertations

This research proposes novel fault adaptive workload allocation (FAWA) strategies for the health management of complex manufacturing systems. The primary goal of these strategies is to minimize maintenance costs and maximize production by strategically controlling when and where failures occur through condition-based workload allocation.

For complex systems that are capable of performing tasks a variety of different ways, such as an industrial robot arm that can move between locations using different joint angle configurations and path trajectories, each option, i.e. mission plan, will result in different degradation rates and life-expectancies. Consequently, this can make it difficult to predict when ...


Motor Control Systems Analysis, Design, And Optimization Strategies For A Lightweight Excavation Robot, Austin Jerold Crawford May 2019

Motor Control Systems Analysis, Design, And Optimization Strategies For A Lightweight Excavation Robot, Austin Jerold Crawford

Theses and Dissertations

This thesis entails motor control system analysis, design, and optimization for the University of Arkansas NASA Robotic Mining Competition robot. The open-loop system is to be modeled and simulated in order to achieve a desired rapid, yet smooth response to a change in input. The initial goal of this work is to find a repeatable, generalized step-by-step process that can be used to tune the gains of a PID controller for multiple different operating points. Then, sensors are to be modeled onto the robot within a feedback loop to develop an error signal and to make the control system self-corrective ...


Numerical Investigation Of Inclination On The Thermal Performance Of Porous Fin Heatsink Using Pseudospectral Collocation Method, George Oguntala, Gbeminiyi Sobamowo, Raed Abd-Alhameed, James Noras Mar 2019

Numerical Investigation Of Inclination On The Thermal Performance Of Porous Fin Heatsink Using Pseudospectral Collocation Method, George Oguntala, Gbeminiyi Sobamowo, Raed Abd-Alhameed, James Noras

Karbala International Journal of Modern Science

Numerical investigation of inclination effect on the thermal performance of a porous fin heat sink is presented. The developed thermal model is solved using pseudo-spectral collocation method (PSCM). Parametric studies are carried out using PSCM, and the thermal characterization of heat sink with the inclined porous fin of rectangular geometry is presented. Results show that heat sink of inclined porous fin exhibits higher thermal performance than heat sink of vertical porous fin operating under the same thermal conditions with the same geometrical configurations. Performance of inclined or tilted fin increases with decrease in length-thickness aspect ratio. However, increase in the ...


An Internet Based Intelligent Argumentation System For Collaborative Engineering Design, Xiaoqing Frank Liu, Samir Raorane, Man Zheng, Ming-Chuan Leu Jan 2019

An Internet Based Intelligent Argumentation System For Collaborative Engineering Design, Xiaoqing Frank Liu, Samir Raorane, Man Zheng, Ming-Chuan Leu

Ming C. Leu

Modern product design is a very complicated process which involves groups of designers, manufacturers, suppliers, and customer representatives. Conflicts are unavoidable in collaboration among multiple stakeholders, who have different objectives, requirements, and priorities. Unfortunately, current web-based collaborative engineering design systems do not support collaborative conflict resolution. In this paper, we will develop an intelligent computational argumentation model to enable management of a large scale argumentation network, and resolution of conflicts based on argumentation from many participants. A web-based intelligent argumentation tool is developed as a part of a web-based collaborative engineering design system based on the above model to resolve ...


Modeling Of Cloud-Based Digital Twins For Smart Manufacturing With Mt Connect, Liwen Hu, Ngoc-Tu Nguyen, Wenjin Tao, Ming-Chuan Leu, Xiaoqing Frank Liu, Rakib Shahriar, S M Nahian Al Sunny Jan 2019

Modeling Of Cloud-Based Digital Twins For Smart Manufacturing With Mt Connect, Liwen Hu, Ngoc-Tu Nguyen, Wenjin Tao, Ming-Chuan Leu, Xiaoqing Frank Liu, Rakib Shahriar, S M Nahian Al Sunny

Ming C. Leu

The common modeling of digital twins uses an information model to describe the physical machines. The integration of digital twins into productive cyber-physical cloud manufacturing (CPCM) systems imposes strong demands such as reducing overhead and saving resources. In this paper, we develop and investigate a new method for building cloud-based digital twins (CBDT), which can be adapted to the CPCM platform. Our method helps reduce computing resources in the information processing center for efficient interactions between human users and physical machines. We introduce a knowledge resource center (KRC) built on a cloud server for information intensive applications. An information model ...


Ir Motion Tracking Robotic Arm, Gavin Low, Andrew Doan, Avery Guillermo, Dayna Yoshimura Jan 2019

Ir Motion Tracking Robotic Arm, Gavin Low, Andrew Doan, Avery Guillermo, Dayna Yoshimura

Engineering E-Portfolios and Projects

The Motion Tracking Robot Arm is a senior Electrical Engineering Capstone project designed by Andrew Doan, Avery Guillermo, Gavin Low, and Dayna Yoshimura. The project serves as an exploration of alternative control methods for robotic arms. While standard robotic arms are often controlled with physical controllers or computer programs, this robotic arm will be controlled with a LEAP motion controller. The user will be able to control the robotic arm using his or her own arm; no extra control inputs will be necessary.


The Borrowbike, Martin Woodby, Grayson Taylor, Jesse Rubenstein, Aaron Leung, Jack Padon, Ryan Dehart Jan 2019

The Borrowbike, Martin Woodby, Grayson Taylor, Jesse Rubenstein, Aaron Leung, Jack Padon, Ryan Dehart

Engineering E-Portfolios and Projects

The BorrowBike is turning UP's bike rental system from an inconvenient process to a hassle-free swipe of a card. BorrowBike's smart lock and online web application streamlines the check-out process and allows bikes to be rented at any time of the day.


Standard And Inception-Based Encoder-Decoder Neural Networks For Predicting The Solution Convergence Of Design Optimization Algorithms, Nathanial James O'Neill Jan 2019

Standard And Inception-Based Encoder-Decoder Neural Networks For Predicting The Solution Convergence Of Design Optimization Algorithms, Nathanial James O'Neill

Aerospace Engineering Sciences Graduate Theses & Dissertations

The goal of this work is to investigate the ways in which the capabilities of machine learning algorithms, specifically those of neural networks, can be leveraged to enhance the performance of design optimization algorithms -- specifically those of topology optimization.

A recent boom of interest in design optimization has occurred, coinciding with the arrival and development of advanced manufacturing techniques (such as 3D printing and additive manufacturing) which are compatible with the designs generated by these algorithms. Neural networks have seen an even larger boom in interest and development for their ability to act as ``universal function generators;" in other words ...


Level-Set-Xfem-Density Topology Optimization Of Active Structures: Methods And Applications, Markus Josef Geiss Jan 2019

Level-Set-Xfem-Density Topology Optimization Of Active Structures: Methods And Applications, Markus Josef Geiss

Aerospace Engineering Sciences Graduate Theses & Dissertations

To unlock the potential of advanced manufacturing technologies like additive manufacturing, an inherent need for sophisticated design tools exists. In this thesis, a systematic approach for designing printed active structures using a combined level-set (LS) extended finite element (XFEM) density topology optimization (TO) scheme is developed. This combined scheme alleviates the downsides of both LS and density based TO approaches while building upon the advantages of either method. Thus, a superior design optimization approach is created, which, when coupled with the XFEM, yields a highly accurate physical modeling method. The unique capabilities of this combined approach include hole nucleation and ...


Direct Numerical Simulations Of The Compressible Low Atwood Rayleigh-Taylor Instability, Scott A. Wieland Jan 2019

Direct Numerical Simulations Of The Compressible Low Atwood Rayleigh-Taylor Instability, Scott A. Wieland

Mechanical Engineering Graduate Theses & Dissertations

Two fluids are considered Rayleigh-Taylor unstable when the more dense fluid is suspended above the less dense fluid in the presence of a gravitational like accelerative force. When a pertur- bation is applied to the interface between the two, they begin mixing as the light fluid rises and the heavy fluid drops. The extension of this to the compressible regime leads to the densities of the fluids to not be constant, but instead the molar mass is used to define the weights. At the interface, a density jump still occurs, but away from the interface the densities can vary in ...


Deep Learning For Monitoring Cyber-Physical Systems, Tryambak Gangopadhyay Jan 2019

Deep Learning For Monitoring Cyber-Physical Systems, Tryambak Gangopadhyay

Graduate Theses and Dissertations

Different cyber-physical systems involving sequential data require accurate frameworks for predicting the state of the system leading to effective monitoring. If the framework is explanatory, the insights provided by the explanations can improve scientific understanding of the system. Detecting the transition to an impending instability is important to initiate effective control in a combustion system. Building robust frameworks is important in this context.

As one of the early applications of characterizing instability in a combustion system using Deep Neural Networks, we train our proposed deep convolutional neural network (CNN) model on sequential image frames extracted from hi-speed flame videos by ...


Call For Abstracts - Resrb 2019, July 8-9, Wrocław, Poland, Wojciech M. Budzianowski Dec 2018

Call For Abstracts - Resrb 2019, July 8-9, Wrocław, Poland, Wojciech M. Budzianowski

Wojciech Budzianowski

No abstract provided.


Feasible Form Parameter Design Of Complex Ship Hull Form Geometry, Thomas L. Mcculloch Dec 2018

Feasible Form Parameter Design Of Complex Ship Hull Form Geometry, Thomas L. Mcculloch

University of New Orleans Theses and Dissertations

This thesis introduces a new methodology for robust form parameter design of complex hull form geometry via constraint programming, automatic differentiation, interval arithmetic, and truncated hierarchical B- splines. To date, there has been no clearly stated methodology for assuring consistency of general (equality and inequality) constraints across an entire geometric form parameter ship hull design space. In contrast, the method to be given here can be used to produce guaranteed narrowing of the design space, such that infeasible portions are eliminated. Furthermore, we can guarantee that any set of form parameters generated by our method will be self consistent. It ...


Variable Input Observer For Nonstationary High-Rate Dynamic Systems, Jonathan Hong, Simon Laflamme, Liang Cao, Jacob Dodson, Bryan Joyce Dec 2018

Variable Input Observer For Nonstationary High-Rate Dynamic Systems, Jonathan Hong, Simon Laflamme, Liang Cao, Jacob Dodson, Bryan Joyce

Civil, Construction and Environmental Engineering Publications

Engineering systems experiencing events of amplitudes higher than 100 gn for a duration under 100 ms, here termed high-rate dynamics, can undergo rapid damaging effects. If the structural health of such systems could be accurately estimated in a timely manner, preventative measures could be employed to minimize adverse effects. For complex high-rate problems, adaptive observers have shown promise due to their capability to deal with nonstationary, noisy, and uncertain systems. However, adaptive observers have slow convergence rates, which impede their applicability to the high-rate problems. To improve on the convergence rate, we propose a variable input space concept for ...


The Effect Of Incorporating End-User Customization Into Additive Manufacturing Designs, Jonathan D. Ashley Dec 2018

The Effect Of Incorporating End-User Customization Into Additive Manufacturing Designs, Jonathan D. Ashley

Theses and Dissertations

In the realm of additive manufacturing there is an increasing trend among makers to create designs that allow for end-users to alter them prior to printing an artifact. Online design repositories have tools that facilitate the creation of such artifacts. There are currently no rules for how to create a good customizable design or a way to measure the degree of customization within a design. This work defines three types of customizations found in additive manufacturing and presents three metrics to measure the degree of customization within designs based on the three types of customization. The goal of this work ...


A Data Set Of Bloodstain Patterns For Teaching And Research In Bloodstain Pattern Analysis: Gunshot Backspatters, Daniel Attinger, Yu Liu, Ricky Faflak, Yalin Rao, Bryce A. Struttman, Kris De Brabanter, Patrick M. Comiskey, Alex L. Yarin Nov 2018

A Data Set Of Bloodstain Patterns For Teaching And Research In Bloodstain Pattern Analysis: Gunshot Backspatters, Daniel Attinger, Yu Liu, Ricky Faflak, Yalin Rao, Bryce A. Struttman, Kris De Brabanter, Patrick M. Comiskey, Alex L. Yarin

Mechanical Engineering Publications

This is a data set of blood spatter patterns scanned at high resolution, generated in controlled experiments. The spatter patterns were generated with a rifle or a handgun, and different ammunitions. The resulting atomized blood droplets travelled opposite to the bullet direction, generating a gunshot backspatter on a poster board target sheet. Fresh blood with anticoagulants was used; its hematocrit and temperature were measured. Main parameters of the study were the bullet shape, size and speed, and the distance between the blood source and target sheet. Several other parameters were explored in a less systematic way. This new and original ...


A Novel Multirobot System For Plant Phenotyping, Tianshuang Gao, Hamid Emadi, Homagni Saha, Jiaoping Zhang, Alec Lofquist, Arti Singh, Baskar Ganapathysubramanian, Soumik Sarkar, Asheesh K. Singh, Sourabh Bhattacharya Sep 2018

A Novel Multirobot System For Plant Phenotyping, Tianshuang Gao, Hamid Emadi, Homagni Saha, Jiaoping Zhang, Alec Lofquist, Arti Singh, Baskar Ganapathysubramanian, Soumik Sarkar, Asheesh K. Singh, Sourabh Bhattacharya

Mechanical Engineering Publications

Phenotypic studies require large datasets for accurate inference and prediction. Collecting plant data in a farm can be very labor intensive and costly. This paper presents the design, architecture (hardware and software) and deployment of a multi-robot system for row crop field data collection. The proposed system has been deployed in a soybean research farm at Iowa State University.


Predict The Failure Of Hydraulic Pumps By Different Machine Learning Algorithms, Yifei Zhou, Monika Ivantysynova, Nathan Keller Aug 2018

Predict The Failure Of Hydraulic Pumps By Different Machine Learning Algorithms, Yifei Zhou, Monika Ivantysynova, Nathan Keller

The Summer Undergraduate Research Fellowship (SURF) Symposium

Pump failure is a general concerned problem in the hydraulic field. Once happening, it will cause a huge property loss and even the life loss. The common methods to prevent the occurrence of pump failure is by preventative maintenance and breakdown maintenance, however, both of them have significant drawbacks. This research focuses on the axial piston pump and provides a new solution by the prognostic of pump failure using the classification of machine learning. Different kinds of sensors (temperature, acceleration and etc.) were installed into a good condition pump and three different kinds of damaged pumps to measure 10 of ...


A Novel Multirobot System For Distributed Phenotyping, Tianshuang Gao, Homagni Saha, Hamid Emadi, Jiaoping Zhang, Alec Lofquist, Arti Singh, Baskar Ganapathysubramanian, Soumik Sarkar, Asheesh Singh, Sourabh Bhattacharya Jul 2018

A Novel Multirobot System For Distributed Phenotyping, Tianshuang Gao, Homagni Saha, Hamid Emadi, Jiaoping Zhang, Alec Lofquist, Arti Singh, Baskar Ganapathysubramanian, Soumik Sarkar, Asheesh Singh, Sourabh Bhattacharya

Mechanical Engineering Publications

Phenotypic studies require large datasets for accurate inference and prediction. Collecting plant data in a farm can be very labor intensive and costly. This paper presents the design, architecture (hardware and software) and deployment of a distributed modular agricultural multi-robot system for row crop field data collection. The proposed system has been deployed in a soybean research farm at Iowa State University.


Identification And Optimal Linear Tracking Control Of Odu Autonomous Surface Vehicle, Nadeem Khan Jul 2018

Identification And Optimal Linear Tracking Control Of Odu Autonomous Surface Vehicle, Nadeem Khan

Mechanical & Aerospace Engineering Theses & Dissertations

Autonomous surface vehicles (ASVs) are being used for diverse applications of civilian and military importance such as: military reconnaissance, sea patrol, bathymetry, environmental monitoring, and oceanographic research. Currently, these unmanned tasks can accurately be accomplished by ASVs due to recent advancements in computing, sensing, and actuating systems. For this reason, researchers around the world have been taking interest in ASVs for the last decade. Due to the ever-changing surface of water and stochastic disturbances such as wind and tidal currents that greatly affect the path-following ability of ASVs, identification of an accurate model of inherently nonlinear and stochastic ASV system ...


A Quantitative Analysis Of Shape Characteristics Of Marine Snow Particles With Interactive Visualization: Validation Of Assumptions In Coagulation Models, Palak P. Dave Jun 2018

A Quantitative Analysis Of Shape Characteristics Of Marine Snow Particles With Interactive Visualization: Validation Of Assumptions In Coagulation Models, Palak P. Dave

Graduate Theses and Dissertations

The Deepwater Horizon oil spill that started on April 20, 2010, in the Gulf of Mexico was the largest marine oil spill in the history of the petroleum industry. There was an unexpected and prolonged sedimentation event of oil-associated marine snow to the seafloor due to the oil spill. The sedimentation event occurred because of the coagulation process among oil associated marine particles. Marine scientists are developing models for the coagulation process of marine particles and oil, in order to estimate the amount of oil that may reach the seafloor along with marine particles. These models, used certain assumptions regarding ...


Worker Activity Recognition In Smart Manufacturing Using Imu And Semg Signals With Convolutional Neural Networks, Wenjin Tao, Ze-Hao Lai, Ming-Chuan Leu, Zhaozheng Yin Jun 2018

Worker Activity Recognition In Smart Manufacturing Using Imu And Semg Signals With Convolutional Neural Networks, Wenjin Tao, Ze-Hao Lai, Ming-Chuan Leu, Zhaozheng Yin

Mechanical and Aerospace Engineering Faculty Research & Creative Works

In a smart manufacturing system involving workers, recognition of the worker's activity can be used for quantification and evaluation of the worker's performance, as well as to provide onsite instructions with augmented reality. In this paper, we propose a method for activity recognition using Inertial Measurement Unit (IMU) and surface electromyography (sEMG) signals obtained from a Myo armband. The raw 10-channel IMU signals are stacked to form a signal image. This image is transformed into an activity image by applying Discrete Fourier Transformation (DFT) and then fed into a Convolutional Neural Network (CNN) for feature extraction, resulting in ...


Modeling Of Cloud-Based Digital Twins For Smart Manufacturing With Mt Connect, Liwen Hu, Ngoc-Tu Nguyen, Wenjin Tao, Ming-Chuan Leu, Xiaoqing Frank Liu, Rakib Shahriar, S M Nahian Al Sunny Jun 2018

Modeling Of Cloud-Based Digital Twins For Smart Manufacturing With Mt Connect, Liwen Hu, Ngoc-Tu Nguyen, Wenjin Tao, Ming-Chuan Leu, Xiaoqing Frank Liu, Rakib Shahriar, S M Nahian Al Sunny

Mechanical and Aerospace Engineering Faculty Research & Creative Works

The common modeling of digital twins uses an information model to describe the physical machines. The integration of digital twins into productive cyber-physical cloud manufacturing (CPCM) systems imposes strong demands such as reducing overhead and saving resources. In this paper, we develop and investigate a new method for building cloud-based digital twins (CBDT), which can be adapted to the CPCM platform. Our method helps reduce computing resources in the information processing center for efficient interactions between human users and physical machines. We introduce a knowledge resource center (KRC) built on a cloud server for information intensive applications. An information model ...


Analysis Of Dynamic Mode Decomposition, Archana Muniraju May 2018

Analysis Of Dynamic Mode Decomposition, Archana Muniraju

Theses and Dissertations

In this master thesis, a study was conducted on a method known as Dynamic mode decomposition(DMD), an equation-free technique which does not require to know the underlying governing equations of the complex data. As a result of massive datasets from various resources, like experiments, simulation, historical records, etc. has led to an increasing demand for an efficient method for data mining and analysis techniques. The main goals of data mining are the description and prediction. Description involves finding patterns in the data and prediction involves predicting the system dynamics. An important aspect when analyzing an algorithm is testing. In ...


A Contact Formulation Based On A Volumetric Potential: Application To Isogeometric Simulations Of Atrioventricular Valves, David Kamensky, Fei Xue, Chung-Hao Lee, Jinhui Yan, Yuri Bazilevs, Ming-Chen Hsu Mar 2018

A Contact Formulation Based On A Volumetric Potential: Application To Isogeometric Simulations Of Atrioventricular Valves, David Kamensky, Fei Xue, Chung-Hao Lee, Jinhui Yan, Yuri Bazilevs, Ming-Chen Hsu

Mechanical Engineering Publications

This work formulates frictionless contact between solid bodies in terms of a repulsive potential energy term and illustrates how numerical integration of the resulting forces is computationally similar to the “pinball algorithm” proposed and studied by Belytschko and collaborators in the 1990s. We thereby arrive at a numerical approach that has both the theoretical advantages of a potential-based formulation and the algorithmic simplicity, computational efficiency, and geometrical versatility of pinball contact. The singular nature of the contact potential requires a specialized nonlinear solver and an adaptive time stepping scheme to ensure reliable convergence of implicit dynamic calculations. We illustrate the ...


Pressure Measurements Inside Multiple Cavities Of A Torque Converter And Cfd Correlation, Edward De Jesus Rivera Jan 2018

Pressure Measurements Inside Multiple Cavities Of A Torque Converter And Cfd Correlation, Edward De Jesus Rivera

Dissertations, Master's Theses and Master's Reports

A torque converter was instrumented with 29 pressure transducers. The pressure transducers were located in multiple cavities. The instrumented cavities included, four transducers mounted on the impeller shell, on the channel between blades. Six transducers mounted on the pressure and suction sides on the middle streamline of a turbine blade. Another seven transducers mounted on the pressure and suction sides of the core, middle and shell streamlines of a stator blade. Seven transducers mounted on the torque converter clutch cavity. Finally, five on the cavity between the pressure plate and the turbine shell. The torque converter was part of a ...


Consuming Digital Debris In The Plasticene, Stephen R. Parks Jan 2018

Consuming Digital Debris In The Plasticene, Stephen R. Parks

Theses and Dissertations

Claims of customization and control by socio-technical industries are altering the role of consumer and producer. These narratives are often misleading attempts to engage consumers with new forms of technology. By addressing capitalist intent, material, and the reproduction limits of 3-D printed objects’, I observe the aspirational promise of becoming a producer of my own belongings through new networks of production. I am interested in gaining a better understanding of the data consumed that perpetuates hyper-consumptive tendencies for new technological apparatuses. My role as a designer focuses on the resolution of not only the surface of the object through 3-D ...


Smart Augmented Reality Instructional System For Mechanical Assembly, Ze-Hao Lai Jan 2018

Smart Augmented Reality Instructional System For Mechanical Assembly, Ze-Hao Lai

Masters Theses

"Quality and efficiency are pivotal indicators of a manufacturing company. Many companies are suffering from shortage of experienced workers across the production line to perform complex assembly tasks such as assembly of an aircraft engine. This could lead to a significant financial loss. In order to further reduce time and error in an assembly, a smart system consisting of multi-modal Augmented Reality (AR) instructions with the support of a deep learning network for tool detection is introduced. The multi-modal smart AR is designed to provide on-site information including various visual renderings with a fine-tuned Region-based Convolutional Neural Network, which is ...