Matching Items (63)
Description
Accessible STEAM (Science, Technology, Engineering, Art, and Mathematics) education is imperative in creating the future innovators of the world. This business proposal is for a K-8 STEAM Museum to be built in the Novus Innovation Corridor on Arizona State University (ASU)’s Tempe campus. The museum will host dynamic spaces that are constantly growing and evolving as exhibits are built by interdisciplinary capstone student groups- creating an internal capstone project pipeline. The intention of the museum is to create an interactive environment that fosters curiosity and creativity while acting as supplemental learning material to Arizona K-8 curriculum. The space intends to serve the greater Phoenix area community and will cater to underrepresented audiences through the development of accessible education rooted in equality and inclusivity.
ContributorsPeters, Abigail J (Author) / McCarville, Daniel R. (Thesis director) / Juarez, Joseph (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Technology has managed to seamlessly grow into every industry fathomable without much resistance. This could be due to the fact that the majority of industries that have integrated technology have lacked insurmountable barriers which could hold back strategic innovations. Even with a wide array of industries applying technology to their framework, some haven’t managed to reach the true capability of technological advances. One industry that has both taken wide advantage of technology while also barely scraping the surface of the depth behind its potential has been politics. Electronic voting booths, targeted online marketing campaigns, and live streamed debates have been integral parts of our modern-day political environment, however, approval rating-based forecasting for elections has been an area that isn’t commonly referenced by both large political players.
In an age of information where data can be extracted just about anywhere and interpolated using extensive statistical processing, the fact that systems modeling isn’t a pillar of campaign efforts seems ludicrous. A field that is heavily dependent on pivoting concern based on lack of support would make sense to heavily depend on a modeling system that can accurately predict future points of interest.
This report aims to lay the foundation that can be built upon through providing pitfalls in potential modeling, importance of a modeling system, and a barebones skeleton model in AnyLogic with a scheme of how the model would work. I hope this report can serve political interests by providing context on which modeling can accurately provide insight.
ContributorsSchiazzano, John (Author) / McCarville, Daniel R. (Thesis director) / Juarez, Joseph (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Advancements in healthcare and the emergence of an aging population has led to an increase in the number of prosthetic joint procedures in the United States. According to Healthcare Cost and Utilization Project, 660,876 and 348,970 total hip and knee arthroplasties were performed in 2014[1].The percentage of total hip or knee procedures that are revised due to an infection is 1.23% and 1.21% respectively[3], [4]. Although the percent of infections may be small, an infection can have a tremendous burden on the patient and healthcare system. It is expected that prosthetic joint infections (PJIs) will cost the healthcare system an estimated $1.62 billion by 2020[5]. PJIs are often difficult to treat due to the formation of biofilm at the site of the infection. A large majority of PJIs are the result of a bacterial biofilm, but around 1% of PJIs are due to fungal infections[3]. The current method of treatment is to surgically remove all infected tissue at the site of infection through a process called debridement and then insert a medicated bone cement spacer[7], [10]–[12]. One such medication that is loaded into the bone cement is caspofungin, a member of the echinocandin class of compounds that inhibit the synthesis of 1,3-β-D-glucan which is a crucial element of the cell wall of the target fungi[13]–[15]. For the studies reported herein, the caspofungin-loaded bone cement samples were made at 5 dosage strengths according to standard operating room practices. The elution of the drug was analyzed using ultraviolet spectrophotometry. The elution profiles were analyzed for 19 days consecutively, during which the 70 mg, 1 g, and 5 g dosage groups showed a prolonged, sustained release of the caspofungin. The 70 mg and 1 g dosage cumulative mass release profiles were not statistically significant, but it is unlikely that the difference would not have a clinical significance especially in the treatment of a fungal biofilm infection. The determination of the elution profile for caspofungin from loaded-bone cement can provide clinicians with a basis for how the drug will release into the infected joint.
ContributorsMoore, Rex C. (Author) / Vernon, Brent (Thesis director) / Overstreet, Derek (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Harrington Bioengineering Program (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Rapid advancements in Artificial Intelligence (AI), Machine Learning, and Deep Learning technologies are widening the playing field for automated decision assistants in healthcare. The field of radiology offers a unique platform for this technology due to its repetitive work structure, ability to leverage large data sets, and high position for clinical and social impact. Several technologies in cancer screening, such as Computer Aided Detection (CAD), have broken the barrier of research into reality through successful outcomes with patient data (Morton, Whaley, Brandt, & Amrami, 2006; Patel et al, 2018). Technologies, such as the IBM Medical Sieve, are growing excitement with the potential for increased impact through the addition of medical record information ("Medical Sieve Radiology Grand Challenge", 2018). As the capabilities of automation increase and become a part of expert-decision-making jobs, however, the careful consideration of its integration into human systems is often overlooked. This paper aims to identify how healthcare professionals and system engineers implementing and interacting with automated decision-making aids in Radiology should take bureaucratic, legal, professional, and political accountability concerns into consideration. This Accountability Framework is modeled after Romzek and Dubnick’s (1987) public administration framework and expanded on through an analysis of literature on accountability definitions and examples in military, healthcare, and research sectors. A cohesive understanding of this framework and the human concerns it raises helps drive the questions that, if fully addressed, create the potential for a successful integration and adoption of AI in radiology and ultimately the care environment.
ContributorsGilmore, Emily Anne (Author) / Chiou, Erin (Thesis director) / Wu, Teresa (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Motorcycle fatalities have been increasing at a faster rate than the number of motorcycles being registered in the United States. There is limited analysis on the causes of fatal motorcycle crashes, specifically regarding different demographics, certain driver behavior, and various crash characteristics. It is important to be aware of how these factors relate to each other during a fatal motorcycle crash. This analysis focuses on these factors and explores potential steps to decrease motorcycle fatality rates using research and data from the Fatality Analysis Reporting System (FARS) from the National Highway Traffic Safety Administration (NHTSA), and data from the National Household Travel Survey (NHTS). Based on this data, there are noticeable trends between different genders and age groups. According to the analysis, males have a higher fatality rate than females, and their fatal crashes tend to involve multiple driver infractions such as drinking, speeding, not wearing a helmet, and driving without a license. Similarly, younger drivers have a higher fatality rate than older drivers, and their fatal crashes tend to involve multiple driver infractions. Although older drivers involved in fatal crashes usually drive more cautiously, they tend to be involved in single-vehicle crashes more often than younger drivers. Moving forward, implementing certain training programs directed towards particular demographics has the potential to decrease motorcycle rider fatalities.
ContributorsMoran, Sarah Elizabeth (Co-author) / Santilli, Amy (Co-author) / Pendyala, Ram (Thesis director) / Khoeini, Sara (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Woodland/Alloy Casting, Inc. is an aluminum foundry known for providing high-quality molds to their customers in industries such as aviation, electrical, defense, and nuclear power. However, as the company has grown larger during the past three years, they have begun to struggle with the on-time delivery of their orders. Woodland prides itself on their high-grade process that includes core processing, the molding process, cleaning process, and heat-treat process. To create each mold, it has to flow through each part of the system flawlessly. Throughout this process, significant bottlenecks occur that limit the number of molds leaving the system. To combat this issue, this project uses a simulation of the foundry to test how best to schedule their work to optimize the use of their resources. Simulation can be an effective tool when testing for improvements in systems where making changes to the physical system is too expensive. ARENA is a simulation tool that allows for manipulation of resources and process while also allowing both random and selected schedules to be run through the foundry’s production process. By using an ARENA simulation to test different scheduling techniques, the risk of missing production runs is minimized during the experimental period so that many different options can be tested to see how they will affect the production line. In this project, several feasible scheduling techniques are compared in simulation to determine which schedules allow for the highest number of molds to be completed.
ContributorsAdams, Danielle Renee (Author) / Pavlic, Theodore (Thesis director) / Montgomery, Douglas (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
The premise of this thesis developed from my personal interests and undergraduate educational experiences in both industrial engineering and design studies, particularly those related to product design. My education has stressed the differences in the ways that engineers and designers approach problem solving and creating solutions, but I am most interested in marrying the two mindsets of designers and engineers to better solve problems creatively and efficiently.
This thesis focuses on the recent appearance of generative design technology into the world of industrial design and engineering as it relates to product development. An introduction to generative design discusses the uses and benefits of this tool for both designers and engineers and also addresses the challenges of this technology. The relevance of generative design to the world of product development is discussed as well as the implications of how this technology will change the roles of designers and engineers, and especially their traditional design processes. The remainder of this paper is divided into two elements. The first serves as documentation of my own exploration of using generative design software to solve a product design challenge and my reflections on the benefits and challenges of using this tool. The second element addresses the need for employing quantitiative methodologies within the generative design process to aid designers in selecting the most advantageous design option when presented with generative outcomes. Both sections aim to provide more context to this new design process and seek to answer questions about some of the ambiguous processes of generative design.
This thesis focuses on the recent appearance of generative design technology into the world of industrial design and engineering as it relates to product development. An introduction to generative design discusses the uses and benefits of this tool for both designers and engineers and also addresses the challenges of this technology. The relevance of generative design to the world of product development is discussed as well as the implications of how this technology will change the roles of designers and engineers, and especially their traditional design processes. The remainder of this paper is divided into two elements. The first serves as documentation of my own exploration of using generative design software to solve a product design challenge and my reflections on the benefits and challenges of using this tool. The second element addresses the need for employing quantitiative methodologies within the generative design process to aid designers in selecting the most advantageous design option when presented with generative outcomes. Both sections aim to provide more context to this new design process and seek to answer questions about some of the ambiguous processes of generative design.
ContributorsElgin, Mariah Crystal (Author) / Bacalzo, Dean (Thesis director) / Gel, Esma (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Dean, Herberger Institute for Design and the Arts (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
Substance abuse has become a major problem in the USA in the past decade, with immense public health and societal consequences. Methamphetamine (meth) use has grown due to an increased number of meth production and distribution markets. Border states such as Arizona and California are especially concerned with Mexico’s production and distribution of meth to their residents. A mathematical model for meth use and markets was developed and then analyzed to track multiple types of drug markets and drug-related arrests for possession or distribution. The importance of social influences as a major causal factor in the onset of illicit drug use is explicitly incorporated. The model parameters are then estimated using meth-related data from California and Arizona. A parameter sensitivity analysis on the model output was carried out. The results suggest that law enforcement policy aimed at marketers will be significantly more effective than targeting current users. Moreover, local unorganized markets have a greater role in maintaining the endemic level of meth users. Whereas, global organized markets play a role in initiating meth use outbreaks. Some implications for interventions and health promotion for the two states are also discussed.
ContributorsChavez, Brianna (Author) / Mubayi, Anuj (Thesis director) / Shafer, Michael (Committee member) / Amol Thakur, Mugdha (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / School of Human Evolution & Social Change (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
This project evaluates the success that a Food Waste assignment had on reducing food waste by exploring factors that suggest waste minimization. Previous ASB 370/394: Ethics of Eating students were surveyed regarding their thoughts on their current food waste behavior and what food waste strategies they implemented to reduce their waste. The success of the assignment was determined using SPSS statistical software. Respondents reported that foods that they waste the most were vegetables, fruits, and bread and most respondents indicated that they threw away 1-2 cups of food per week, typically only when they clean out their fridge and/or pantry. Participants revealed the main reasons for their food waste were “I buy too much,” followed by “do not have time to prepare the food I buy,” and “my produce didn’t look appealing anymore.” Based on the results from the survey, over 60% of respondents indicated that they had changed their food waste behavior to produce less waste. The Food Waste Assignment was deemed a success in encouraging students to limit their food waste due to the majority of students indicating they change their behavior after completing the assignment. The three main tactics students implemented to reduce their food waste were: “eating more leftovers,” “proper food storage,” and, “meal planning.” While the Food Waste Assignment was successful, ways to improve the assignment were still identified. To help students address their food waste behavior, reading or videos on ways to prevent food waste or suggestions for students to improve their food waste could be provided.
ContributorsMicksch, Jessica Lee (Co-author, Co-author) / Stotts, Rhian (Thesis director) / Bidner, Laura (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Environmental and Resource Management (Contributor) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description
In March 2019, the United Nations Intergovernmental Panel on Climate Change (IPCC) released a report describing the critical importance of the next decade in mitigating the effects of climate change. From a consumer perspective, the most impactful method of reducing greenhouse gas emissions is by altering and/or reducing usage of personal and public transportation. Despite the significant technological advances in vehicle electrification, vehicle mileage, and hybrid technology, there is a gap in analysis performed about the relationship between oil prices and electric vehicle sales. This can be largely attributed to the large variation in oil and gas prices within the last decade and the short timeframe in which electric vehicles have been available to the average consumer. In addition to oil prices, significant driving factors of consumer electric vehicle purchases include battery range, availability and accessibly of charging infrastructure, and tax incentives. While consumers clearly have a significant role to play in driving electric vehicle sales, by virtue of the time commitment required to research and develop these emerging technologies, manufacturers have an arguably greater role in determining the market share EVs possess. The concept of “market disruption” versus “market replacement” is an intriguing explanation for the failure of electric vehicles, which as of early 2019 held a market share of less than 2%, to become the primary mode of transportation for most Americans, despite their wide-ranging financial and societal benefits, which will be a key challenge for the industry to overcome in the years to come.
ContributorsStout, Julia (Author) / Jennings, Cheryl (Thesis director) / Metcalfe, Carly (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05