Matching Items (4)
Filtering by
- All Subjects: Modeling
- Creators: Fox, Peter
Description
The goal of this thesis was to provide in depth research into the semiconductor wet-etch market and create a supplier analysis tool that would allow Company X to identify the best supplier partnerships. Several models were used to analyze the wet etch market including Porter's Five Forces and SWOT analyses. These models were used to rate suppliers based on financial indicators, management history, market share, research and developments spend, and investment diversity. This research allowed for the removal of one of the four companies in question due to a discovered conflict of interest. Once the initial research was complete a dynamic excel model was created that would allow Company X to continually compare costs and factors of the supplier's products. Many cost factors were analyzed such as initial capital investment, power and chemical usage, warranty costs, and spares parts usage. Other factors that required comparison across suppliers included wafer throughput, number of layers the tool could process, the number of chambers the tool has, and the amount of space the tool requires. The demand needed for the tool was estimated by Company X in order to determine how each supplier's tool set would handle the required usage. The final feature that was added to the model was the ability to run a sensitivity analysis on each tool set. This allows Company X to quickly and accurately forecast how certain changes to costs or tool capacities would affect total cost of ownership. This could be heavily utilized during Company X's negotiations with suppliers. The initial research as well the model lead to the final recommendation of Supplier A as they had the most cost effective tool given the required demand. However, this recommendation is subject to change as demand fluctuates or if changes can be made during negotiations.
ContributorsSchmitt, Connor (Co-author) / Rickets, Dawson (Co-author) / Castiglione, Maia (Co-author) / Witten, Forrest (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / Department of Economics (Contributor) / Department of Information Systems (Contributor) / Department of Supply Chain Management (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / School of Accountancy (Contributor) / WPC Graduate Programs (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
This report analyzes the potential for accumulation of boron in direct potable reuse. Direct potable reuse treats water through desalination processes such as reverse osmosis or nanofiltration which can achieve rejection rates of salts sometimes above 90%. However, boron achieves much lower rejection rates near 40%. Because of this low rejection rate, there is potential for boron to accumulate in the system to levels that are not recommended for potable human consumption of water. To analyze this issue a code was created that runs a steady state system that tracks the internal concentration, permeate concentration, wastewater concentration and reject concentration at various rejection rates, as well as all the flows. A series of flow and mass balances were performed through five different control volumes that denoted different stages in the water use. First was mixing of clean water with permeate; second, consumptive uses; third, addition of contaminant; fourth, wastewater treatment; fifth, advanced water treatments. The system cycled through each of these a number of times until steady state was reached. Utilities or cities considering employing direct potable reuse could utilize this model by estimating their consumption levels and input of contamination, and then seeing what percent rejection or inflow of makeup water they would need to obtain to keep boron levels at a low enough concentration to be fit for consumption. This code also provides options for analyzing spikes and recovery in the system due to spills, and evaporative uses such as cooling towers and their impact on the system.
ContributorsDoidge, Sydney (Author) / Fox, Peter (Thesis director) / Perreault, Francois (Committee member) / Civil, Environmental and Sustainable Engineering Program (Contributor) / School of International Letters and Cultures (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
C.C. Cragin Reservoir’s location in the Coconino National Forest, Arizona makes it prone to wild fire. This study focused on the potential impacts of such a wild fire on the reservoir’s annual thermal stratification cycle impacts and water quality. The annual thermal stratification cycle impacted the reservoir’s water quality by increasing hypolimnion concentrations of magnesium, iron, turbidity, and specific ultraviolet absorbance (SUVA) values, as well as resulting in the hypolimnion having decreased dissolved oxygen concentrations during stratified months. The scarification process did not affect the dissolved organic carbon (DOC) concentrations in the reservoir or the total/dissolved nitrogen and phosphorous concentrations. Some general water quality trends that emerged were that phosphorous was the limiting nutrient, secchi disk depth and chlorophyll a concentration are inversely related, and no metals were found to be in concentrations that would violate an EPA drinking water maximum contaminant level (MCL). A carbon mass model was developed and parameterized using DOC measurements, and then using historic reservoir storage and weather data, the model simulated DOC concentrations in the reservoir following four hypothetical wild fire events. The model simulated varying initial reservoir storage volumes, initial flush volumes, and flush DOC concentrations, resulting in reservoir DOC concentrations varying from 17.41 mg/L to 8.82 mg/L.
ContributorsFlatebo, Theodore (Author) / Westerhoff, Paul K (Thesis advisor) / Fox, Peter (Committee member) / Perreault, Francois (Committee member) / Arizona State University (Publisher)
Created2018
Description
One of the two objectives of this dissertation is an investigation into the possible correlation between rainfall events and increased levels of E. coli and Mycobacterium using an existing data set. The literature states that levels of microbial concentrations do increase after rainfall events, but there are no studies to indicate this correlation applies in any Arizona water systems. The data analyzed for the bacterial concentrations project suggested the possibility of a correlation along one river but it is not conclusive to state that any correlation exists between rainfall events and the microbial concentration for many other sites included in the analysis. This is most likely due to the highly engineered water delivery systems that are not directly impacted.
The secondary objective was to determine if there are environmental variables collected from an ongoing project which would be a good candidate for making predictions about any of the project data parameters. Of the 79 possible opportunities for the model to accurately predict the dependent variable, it showed strong statistical favorability as well as experimentally favorable results towards Dissolved Organic Carbon as the best dependent variable from the data set, resulting in an accuracy of 41%. This is relevant since Dissolved Organic Carbon is one of the most important water quality parameters of concern for drinking water treatment plants where disinfection by-products are a limiting factor. The need for further analysis and additional data collection is an obvious result from both studies. The use of hydrograph data instead of rainfall would be a logical new direction for the heavily engineered water delivery systems.
The secondary objective was to determine if there are environmental variables collected from an ongoing project which would be a good candidate for making predictions about any of the project data parameters. Of the 79 possible opportunities for the model to accurately predict the dependent variable, it showed strong statistical favorability as well as experimentally favorable results towards Dissolved Organic Carbon as the best dependent variable from the data set, resulting in an accuracy of 41%. This is relevant since Dissolved Organic Carbon is one of the most important water quality parameters of concern for drinking water treatment plants where disinfection by-products are a limiting factor. The need for further analysis and additional data collection is an obvious result from both studies. The use of hydrograph data instead of rainfall would be a logical new direction for the heavily engineered water delivery systems.
ContributorsBuell, Andrew (Author) / Fox, Peter (Thesis advisor) / Abbaszadegan, Morteza (Thesis advisor) / Alum, Absar (Committee member) / Arizona State University (Publisher)
Created2018