Matching Items (6)
Filtering by

Clear all filters

137487-Thumbnail Image.png
Description
The current Enterprise Requirements and Acquisition Model (ERAM), a discrete event simulation of the major tasks and decisions within the DoD acquisition system, identifies several what-if intervention strategies to improve program completion time. However, processes that contribute to the program acquisition completion time were not explicitly identified in the simulation

The current Enterprise Requirements and Acquisition Model (ERAM), a discrete event simulation of the major tasks and decisions within the DoD acquisition system, identifies several what-if intervention strategies to improve program completion time. However, processes that contribute to the program acquisition completion time were not explicitly identified in the simulation study. This research seeks to determine the acquisition processes that contribute significantly to total simulated program time in the acquisition system for all programs reaching Milestone C. Specifically, this research examines the effect of increased scope management, technology maturity, and decreased variation and mean process times in post-Design Readiness Review contractor activities by performing additional simulation analyses. Potential policies are formulated from the results to further improve program acquisition completion time.
ContributorsWorger, Danielle Marie (Author) / Wu, Teresa (Thesis director) / Shunk, Dan (Committee member) / Wirthlin, J. Robert (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2013-05
Description
In this study, the implementation of educational technology and its effect on learning and user experience is measured. A demographic survey, pretest/posttest, and educational experience survey was used to collect data on the control and experimental groups. The experimental group was subjected to different learning material than the control grou

In this study, the implementation of educational technology and its effect on learning and user experience is measured. A demographic survey, pretest/posttest, and educational experience survey was used to collect data on the control and experimental groups. The experimental group was subjected to different learning material than the control group with the use of the Elements 4D mobile application by Daqri to learn basic chemical elements and compounds. The control group learning material provided all the exact information as the application, but in the 2D form of a printed packet. It was expected the experimental group would outperform the control group and have a more enjoyable experience and higher performance. After data analysis, it was concluded that the control group outperformed the experimental group on performance and both groups has similar experiences in contradiction to the hypothesis. Once the factors that contribute to the limitations of different study duration, learning the application beforehand, and only-memorization questions are addressed, the study can be conducted again. Application improvements may also alter the future results of the study and hopefully lead to full implementation into a curriculum.
ContributorsApplegate, Garrett Charles (Author) / Atkinson, Robert (Thesis director) / Chavez-Echeagaray, Maria Elena (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
134361-Thumbnail Image.png
Description

Based on findings of previous studies, there was speculation that two well-known experimental design software packages, JMP and Design Expert, produced varying power outputs given the same design and user inputs. For context and scope, another popular experimental design software package, Minitab® Statistical Software version 17, was added to the

Based on findings of previous studies, there was speculation that two well-known experimental design software packages, JMP and Design Expert, produced varying power outputs given the same design and user inputs. For context and scope, another popular experimental design software package, Minitab® Statistical Software version 17, was added to the comparison. The study compared multiple test cases run on the three software packages with a focus on 2k and 3K factorial design and adjusting the standard deviation effect size, number of categorical factors, levels, number of factors, and replicates. All six cases were run on all three programs and were attempted to be run at one, two, and three replicates each. There was an issue at the one replicate stage, however—Minitab does not allow for only one replicate full factorial designs and Design Expert will not provide power outputs for only one replicate unless there are three or more factors. From the analysis of these results, it was concluded that the differences between JMP 13 and Design Expert 10 were well within the margin of error and likely caused by rounding. The differences between JMP 13, Design Expert 10, and Minitab 17 on the other hand indicated a fundamental difference in the way Minitab addressed power calculation compared to the latest versions of JMP and Design Expert. This was found to be likely a cause of Minitab’s dummy variable coding as its default instead of the orthogonal coding default of the other two. Although dummy variable and orthogonal coding for factorial designs do not show a difference in results, the methods affect the overall power calculations. All three programs can be adjusted to use either method of coding, but the exact instructions for how are difficult to find and thus a follow-up guide on changing the coding for factorial variables would improve this issue.

ContributorsArmstrong, Julia Robin (Author) / McCarville, Daniel R. (Thesis director) / Montgomery, Douglas (Committee member) / Industrial, Systems (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
135127-Thumbnail Image.png
Description
Access to clean drinking water has been identified by the National Academy of Engineering as one of the Grand Challenges of the 21st century. This thesis investigated clean drinking water access in the greater Phoenix area, specifically with regards to drinking water quality standards and management strategies. This research report

Access to clean drinking water has been identified by the National Academy of Engineering as one of the Grand Challenges of the 21st century. This thesis investigated clean drinking water access in the greater Phoenix area, specifically with regards to drinking water quality standards and management strategies. This research report provides an introduction to water quality, treatment, and management; a background on the Salt River Project; and an analysis on source water mix and drinking water quality indicators for water delivered to Tempe, Arizona water treatment facilities.
ContributorsMercer, Rebecca Nicole (Author) / Ganesh, Tirupalavanam (Thesis director) / Trowbridge, Amy (Committee member) / Industrial, Systems (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
137647-Thumbnail Image.png
Description
The widespread use of statistical analysis in sports-particularly Baseball- has made it increasingly necessary for small and mid-market teams to find ways to maintain their analytical advantages over large market clubs. In baseball, an opportunity for exists for teams with limited financial resources to sign players under team control to

The widespread use of statistical analysis in sports-particularly Baseball- has made it increasingly necessary for small and mid-market teams to find ways to maintain their analytical advantages over large market clubs. In baseball, an opportunity for exists for teams with limited financial resources to sign players under team control to long-term contracts before other teams can bid for their services in free agency. If small and mid-market clubs can successfully identify talented players early, clubs can save money, achieve cost certainty and remain competitive for longer periods of time. These deals are also advantageous to players since they receive job security and greater financial dividends earlier in their career. The objective of this paper is to develop a regression-based predictive model that teams can use to forecast the performance of young baseball players with limited Major League experience. There were several tasks conducted to achieve this goal: (1) Data was obtained from Major League Baseball and Lahman's Baseball Database and sorted using Excel macros for easier analysis. (2) Players were separated into three positional groups depending on similar fielding requirements and offensive profiles: Group I was comprised of first and third basemen, Group II contains second basemen, shortstops, and center fielders and Group III contains left and right fielders. (3) Based on the context of baseball and the nature of offensive performance metrics, only players who achieve greater than 200 plate appearances within the first two years of their major league debut are included in this analysis. (4) The statistical software package JMP was used to create regression models of each group and analyze the residuals for any irregularities or normality violations. Once the models were developed, slight adjustments were made to improve the accuracy of the forecasts and identify opportunities for future work. It was discovered that Group I and Group III were the easiest player groupings to forecast while Group II required several attempts to improve the model.
ContributorsJack, Nathan Scott (Author) / Shunk, Dan (Thesis director) / Montgomery, Douglas (Committee member) / Borror, Connie (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2013-05
Description
In 2010, for the first time in human history, more than half of the world's total population lived in cities; this number is expected to increase to 60% or more by 2050. The goal of this research effort is to create a comprehensive model and modelling framework for megacities, middleweight

In 2010, for the first time in human history, more than half of the world's total population lived in cities; this number is expected to increase to 60% or more by 2050. The goal of this research effort is to create a comprehensive model and modelling framework for megacities, middleweight cities, and urban agglomerations, collectively referred to as dense urban areas. The motivation for this project comes from the United States Army's desire for readiness in all operating environments including dense urban areas. Though there is valuable insight in research to support Army operational behaviors, megacities are of unique interest to nearly every societal sector imaginable. A novel application for determining both main effects and interactive effects between factors within a dense urban area is a Design of Experiments- providing insight on factor causations. Regression Modelling can also be employed for analysis of dense urban areas, providing wide ranging insights into correlations between factors and their interactions. Past studies involving megacities concern themselves with general trend of cities and their operation. This study is unique in its efforts to model a singular megacity to enable decision support for military operational planning, as well as potential decision support to city planners to increase the sustainability of these dense urban areas and megacities.
ContributorsMathesen, Logan Michael (Author) / Zenzen, Frances (Thesis director) / Jennings, Cheryl (Committee member) / Industrial, Systems (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05