The ASU COVID-19 testing lab process was developed to operate as the primary testing site for all ASU staff, students, and specified external individuals. Tests are collected at various collection sites, including a walk-in site at the SDFC and various drive-up sites on campus; analysis is conducted on ASU campus and results are distributed virtually to all patients via the Health Services patient portal. The following is a literature review on past implementations of various process improvement techniques and how they can be applied to the ABCTL testing process to achieve laboratory goals. (abstract)

Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.

Our thesis is a cross collaboration between international relations and industrial engineering. We used a combination of database logic, programming, and Microsoft Visual Studio to organize and analyze Middle Eastern politics. Not only does the final product show raw data entry, but it also can answer complex questions about Middle Eastern relations- queries so complex that Google can’t answer them. We organized and analyzed geopolitical data to make it more accessible and easy, hopefully you enjoy!

Arizona State course enrollment regularly reaches triple digits. Despite the large enrollment numbers, the level of communication among students remain relatively low. Students often create Discord servers to keep in touch with classmates, but this requires each individual student to track down the invite link. The purpose of this project is to create an inviting chat service for students with minimal barriers of entry. This website, https://gibbl.io, offers a chat room for every class at ASU, making it simple for students to maintain communication.

Covid-19 is unlike any coronavirus we have seen before, characterized mostly by the ease with which it spreads. This analysis utilizes an SEIR model built to accommodate various populations to understand how different testing and infection rates may affect hospitalization and death. This analysis finds that infection rates have a significant impact on Covid-19 impact regardless of the population whereas the impact that testing rates have in this simulation is not as pronounced. Thus, policy-makers should focus on decreasing infection rates through targeted lockdowns and vaccine rollout to contain the virus, and decrease its spread.

The product our team is commercializing is a NASA designed technology designed to store waste in space. This product works on Earth as well and has applicable multi-use capabilities. Throughout the last several months, the team has identified different markets to determine which of them would experience the most value from this product. The team conducted 25 interviews to grasp the landscape of the different markets related to this product. After a thorough analysis, it was found that vendors who support the disposal of different types of waste and sludge would be the best fit for this product. Vendors like Waste Management, Sharps, Stericycle, Sludge USA, etc.,” have large contracts with hospitals, biotech firms, labs, and cities to manage a wide spectrum of waste. The companies bring value to their clients by making a difficult process easier. However, the process is not seamless and, with certain types of waste, there are significant costs associated with not following an exact process. Throughout this process and interviews with companies like Sludge USA and Waste Management, the team identified a niche market in supporting sludge processes. Caked: Sludge Management is designed to bring value to this market by making their waste disposal process seamless, and saving these institutions significant costs in the long run, while creating additional value.

The purpose of this study is to create and establish an efficient and cost-effective solution to decrease the effects of sedentarism in pregnant women. Our team was given a propelling question, from which we had to narrow down our scope and conduct primary and secondary research to determine our ideal customers. The design of our study intends to imitate the development of a startup where ideas are created from scratch and the final deliverable is a business model plan that shows some sort of traction. Our first major finding is that a sedentary lifestyle can be treated without major challenges in low-risk pregnancies. We determined that uncertainty and lack of concise and clear information is one of the main causes of an increased level of sedentary behavior in low-risk pregnancies. A significant driver for women to do some sort of activity or exercise stems from feeling supported, which doesn’t necessarily come from their partner or couple, but instead from other women that are going to a similar process as them. There are apps in the market that intend to serve pregnant women; however, there is not one that incorporates a social aspect to achieve their goal. In conclusion, there is opportunity in the market for a socially integrated pregnancy fitness app. The Gleam concept has been consciously developed to decrease sedentary behavior through concise, clear, and reliable information and by encouraging women through a socialization platform.

The academic environment has historically been somewhat slow to implement and adopt new technologies. However, developments in video games have created an opportunity for students to learn new skills and topics through nontraditional mediums of education. The disruption caused by the COVID-19 pandemic further highlighted the need for flexible learning opportunities. Joystick Education is our approach to addressing this need. Through online, game-based tutoring and a database of video games with high educational value, Joystick Education creates a learning environment that is effective, fun, and engaging for students. We analyzed popular, mainstream video games for educational content and selected nine games that teach concepts like history, biology, or physics while playing the game. Through promotion on social media, we generated buzz around our website which led to 103 unique visitors over our first month online and two customers requesting to book our tutoring service. We are confident that given more time to grow, Joystick Education can generate profit and become a successful business.

This thesis was conducted to study and analyze the fund allocation process adopted by different states in the United States to reduce the impact of the Covid-19 virus. Seven different states and their funding methodologies were compared against the case count within the state. The study also focused on development of a physical distancing index based on three significant attributes. This index was then compared to the expenditure and case counts to support decision making.
A regression model was developed to analyze and compare how different states case counts played out against the regression model and the risk index.

Time studies are an effective tool to analyze current production systems and propose improvements. The problem that motivated the project was that conducting time studies and observing the progression of components across the factory floor is a manual process. Four Industrial Engineering students worked with a manufacturing company to develop Computer Vision technology that would automate the data collection process for time studies. The team worked in an Agile environment to complete over 120 classification sets, create 8 strategy documents, and utilize Root Cause Analysis techniques to audit and validate the performance of the trained Computer Vision data models. In the future, there is an opportunity to continue developing this product and expand the team’s work scope to apply more engineering skills on the data collected to drive factory improvements.