Cybermanufacturing

2021 Cohorts

Institute: Texas A & M International University

TAMU Mentor: Dr. Chao Ma

Graduate Student Mentor: Mohammadamin Moghadasi

Research Project: Binder Jetting Additive Manufacturing of Ceramics: Improvement of Part Quality

Description:

This study investigated possible improvements that can be made in the quality of ceramic parts using binder jetting additive manufacturing techniques with a particular focus on flexural strength and density. The purpose of the research was to test out how the final samples might be affected by different compaction thicknesses and layer thicknesses to discover improvements that can be made to the final parts. By examining the quality of the samples printed, made from Thethonite High Alumina (96% Alumina), using the ExOne Innovent+ binder jetting 3D printer, adjustments on the compaction thickness and layer thickness were made before printing the samples. For printing, the parameters were adjusted to improve the quality of the powder bed. For post-processing, curing, depowdering, debinding, and sintering techniques were used. After completing the steps of ceramic binder jetting (feedstock preparation, printing, curing, debinding, and sintering), the lapping technique was used to prepare the surface of the printed samples. Finally, the density and mechanical behavior of the final samples were investigated through the Archimedes’ and the flexural strength methods, respectively. Other results suggest that having a high compaction thickness on only the upper and bottom half of the ceramic samples did not improve the mechanical behavior.

Institute: The University of Texas at San Antonio

TAMU Mentor: Dr. Amarnath Banerjee

Graduate Student Mentor: Harshini Jayabal

Research Project:  Industry 4.0

Description:

Industry 4.0 is considered as the integration of cyber learning systems with a mechanical device or system of devices to create a digital twin and collect relevant system data in real-time. This can be used to create predictive maintenance plans for machinery and improve existing designs by identifying and removing slow processes in a manufacturing environment

Institute: Cornell University

TAMU Mentor: Dr. Yu Ding

Graduate Student Mentor: Adaiyibo E. Kio

Research Project: Environmental Factor Predictions and Power Forecasting for Wind Turbines

Description:

The power production of wind turbines depends heavily on the ever-changing environmental factors, especially wind speed.  Accurate power production forecasts will substantially benefit wind energy providers.  Wind energy providers will be able to accurately determine whether they can supply the energy to the grid for which they are contracted.  If a wind farm does not produce enough power, they must purchase the power from somewhere else, and if they have a surplus, they can sell it off.  Having accurate predictions allows wind energy producers to have the time to buy and sell power without resorting to paying exorbitant prices or wasting their surplus.  This research aims to achieve this goal by examining trends in real data instead of using complex physics.  We will consider several environmental factors that affect power production.  Lastly, many wind farms make their own predictions, usually every hour for the upcoming twenty-four hours.  We want to determine how accurate these predictions are based on the real data and develop improved models for predicting power.

Institute: Arizona State University-Tempe

TAMU Mentor: Dr. Shiren Wang

Graduate Student Mentor: Jared Gibson

Research Project: Voxel Bio-Printing

Description:

Create the hardware and software for a computed axial lithography (CAL) 3D printer to be used in studying radial carbon nanotube alignment in viscous resin. We will continue to use this 3D printer to study resin biomaterials and how they can be used to create 3D printed anatomical body parts.

Institute: Arizona State University-Tempe

TAMU Mentor: Dr. Ranjana Mehta and Dr. Prabhakar Pagilla

Graduate Student Mentor: Yinsu Zhang

Research Project: Identifying Cyber intrusions through human-robot interaction metrics

Description:

The goal is to assess cyber intrusions by focusing on monitoring human-robot interaction metrics. We will be harnessing human data (eye-tracking, brain imaging, physiological responses) and external sensor data (camera feed) to detect cyber intrusion manifestations (i.e., unreliable robot behaviors).

Institute: University of California-Merced

TAMU Mentor: Dr. ChaBum Lee

Graduate Student Mentor: Heebum Chun

Research Project: Preliminary Understanding of Li-Ion Battery Charging and Discharging Dynamic Behavior by Stethoscopy

Description:

The goal of this project is to monitor the movement of ions in a battery by using a frequency sensor and 3D surface reconstruction by using stereoscopic imaging.

Institute: The University of Texas at El Paso

TAMU Mentor: Dr. Heng Pan

Graduate Student Mentor: Xiangtao Gong

Research Project: Flexible electronics manufacturing by aerosol printing

Description:

With aerosol jet printing, the future of manufacturing flexible electronics is promising. In this project, we explore a method of printing layers of polyimide (insulator) with a layer of processed silver nanoink (conductive material). This specimen is then transferred to a stretchable surface. Optimizing the method of transfer and making the process inexpensive and scalable is the goal of this project. This implies making, or finding another substrate that is accessible, since it cannot be any arbitrary substrate.

Institute: North Carolina State University

TAMU Mentor: Dr. Hong Liang

Graduate Student Mentor: Ajinkya Raut

Research Project: Fabrication of Nanocomposite membranes for water filtration

Description:

Wastewater treatment by membrane filtration is a widely used technique. The goal is to design and fabricate membranes to filter water, both to understand how these membranes work and create better ones. These membranes will be made from many different polymers, with multiple kinds of nanoparticles suspended in them.

Institute: University of Maryland-College Park

TAMU Mentor: Dr. Dinakar Sagapuram

Graduate Student Mentor: Harshit Chawla

Research Project: An Open Source Toolbox for Determining Constitutive Material Parameters

Description:

Using Constitutive Laws and approximation methods to estimate the properties of materials in the plastic region

Institute: Eastern Connecticut State University

TAMU Mentor: Dr. Arun Srinivasa

Graduate Student Mentor: Naveen Thomas

Research Project: Comparison of damage in shape-memory polymer due to milling and laser cutting

Description:

Compare different manufacturing processes in shape-memory polymers by taking samples and carefully cutting them

Institute: Oregon State University

TAMU Mentor: Dr. Amir Asadi

Graduate Student Mentor: Ozge Kaynan

Research Project: Predicting the Mechanical Properties of Carbon Fiber Reinforced Polymers from Scanning Electron Microscope Images with Machine Learning.

Description:

The goal is to be able to predict the mechanical properties of composite materials with SEM images. For that we will write the respective code to take in SEM images and crop them. The images have to be saved and output multiple different orientations for machine learning. This will also lead to eliminating the need to make composites, characterizing them, etc.

Institute: The University of Texas at El Paso

TAMU Mentor: Dr. Sarah Wolff

Graduate Student Mentor: Mahsa Valizadeh

Research Project: Machine Learning of Metals in Additive Manufacturing Process

Description:

Over time, technology has advanced in an extraordinary way, as well as the different additive manufacturing processes of the different materials, however it is not 100% viable, due to the porosity caused by the laser in the different types of metals. The project consists of the analysis of data, both x-rays and thermal images of the additive manufacturing process with different types of metals. The images obtained, which are captured every 20 microseconds, will go through a cleaning and labeling process. Subsequently, it is possible to predict what will happen to the material when it is subjected to this process.

Institute: College of William and Mary

TAMU Mentor: Dr. Satish Bukkapatnam/ Dr. Bimal Nepal

Graduate Student Mentor: Parth Dave

Research Project: Sensor fusion and analysis for smart manufacturing

Description:

Different tasks in manufacturing equipment produce different sensor readings. By capturing real-time data from the equipment, we can analyze it to determine what the equipment is currently doing. We can also look for signs that the equipment is behaving abnormally and stop it to reduce wasted time and materials.