Matching Items (7)
133125-Thumbnail Image.png
Description

Project management is the crucial component for managing and mitigating the inherent risks associated with changes in technology and innovation. The procedures to track the schedule, budget, and scope of various projects in the standard worlds of engineering, manufacturing, construction, etc., are essential elements to the success of the project.

Project management is the crucial component for managing and mitigating the inherent risks associated with changes in technology and innovation. The procedures to track the schedule, budget, and scope of various projects in the standard worlds of engineering, manufacturing, construction, etc., are essential elements to the success of the project. Cost overruns, schedule changes, and other natural risks must be managed effectively. But what happens when a project manager is tasked with delivering an attraction that needs to withstand harsh weather conditions, and millions of people enjoying it every year, for a company with arguably the highest standards for quality and guest satisfaction? This would describe the project managers at Walt Disney Imagineering (WDI) and the projects they oversee have tight budgets, aggressive schedules and require a bit more pixie dust than other engineering projects. However, the universal truth is that no matter the size or the scope of the endeavor, project management processes are absolutely essential to ensuring that every team member can effectively collaborate to deliver the best product.

ContributorsBaker, Molly (Author) / McCarville, Daniel R. (Thesis director) / Juarez, Joseph (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
127956-Thumbnail Image.png
Description

In this study, a low-cycle fatigue experiment was conducted on printed wiring boards (PWB). The Weibull regression model and computational Bayesian analysis method were applied to analyze failure time data and to identify important factors that influence the PWB lifetime. The analysis shows that both shape parameter and scale parameter

In this study, a low-cycle fatigue experiment was conducted on printed wiring boards (PWB). The Weibull regression model and computational Bayesian analysis method were applied to analyze failure time data and to identify important factors that influence the PWB lifetime. The analysis shows that both shape parameter and scale parameter of Weibull distribution are affected by the supplier factor and preconditioning methods Based on the energy equivalence approach, a 6-cycle reflow precondition can be replaced by a 5-cycle IST precondition, thus the total testing time can be greatly reduced. This conclusion was validated by the likelihood ratio test of two datasets collected under two different preconditioning methods Therefore, the Weibull regression modeling approach is an effective approach for accounting for the variation of experimental setting in the PWB lifetime prediction.

ContributorsPan, Rong (Author) / Xu, Xinyue (Author) / Juarez, Joseph (Author) / Ira A. Fulton Schools of Engineering (Contributor)
Created2016-11-12
Description
In the past, Industrial Engineering/Engineering Management Capstone groups have not provided adequate documentation of their project data, results, and conclusions to both the course instructor and their project sponsors. The goal of this project is to mitigate these issues by instituting a knowledge management system with one of ASU’s cloud

In the past, Industrial Engineering/Engineering Management Capstone groups have not provided adequate documentation of their project data, results, and conclusions to both the course instructor and their project sponsors. The goal of this project is to mitigate these issues by instituting a knowledge management system with one of ASU’s cloud storage tools, OSF, and by updating course rubrics to reflect knowledge sharing best practices. This project used existing research to employ tactics that promote the long-term use of this system. In addition, data specialists from ASU Library’s Research and Data Management department were involved.
ContributorsWade, Alexis Nicole (Author) / Juarez, Joseph (Thesis director) / Gel, Esma (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
131705-Thumbnail Image.png
Description
The retail cost of video games has remained fairly consistent over the decades as the industry has grown so significantly. Emerging alternatives to buying individual games, such as subscription services, attempt to provide a better deal than the current options. Examining the various attributes that all video games possess, regression

The retail cost of video games has remained fairly consistent over the decades as the industry has grown so significantly. Emerging alternatives to buying individual games, such as subscription services, attempt to provide a better deal than the current options. Examining the various attributes that all video games possess, regression analysis can be performed to look for what factors may impact the retail cost of a game. After performing the analysis, however, the low adjusted R-square values indicate that the analysis only accounts for a small percentage of the retail cost variability. This suggests that the chosen attributes are not reliable in estimating retail cost with a regression analysis.
ContributorsKeller, Caden Matthew (Author) / Michael, Clough (Thesis director) / Juarez, Joseph (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor) / Dean, W.P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
131553-Thumbnail Image.png
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

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
131563-Thumbnail Image.png
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

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
130926-Thumbnail Image.png
Description
The outbreak of the coronavirus has impacted retailers and the food industry after they were forced to switch to delivery services due to social distancing measures. During these times, online sales and local deliveries started to see an increase in their demand - making these methods the new way of

The outbreak of the coronavirus has impacted retailers and the food industry after they were forced to switch to delivery services due to social distancing measures. During these times, online sales and local deliveries started to see an increase in their demand - making these methods the new way of staying in business. For this reason, this research seeks to identify strategies that could be implemented by delivery service companies to improve their operations by comparing two types of p-median models (node-based and edge-based). To simulate demand, geographical data will be analyzed for the cities of San Diego and Paris. The usage of districting models will allow the determination on how balance and compact the service regions are within the districts. After analyzing the variability of each demand simulation run, conclusions will be made on whether one model is better than the other.
ContributorsAguilar, Sarbith Anabella (Author) / Escobedo, Adolfo (Thesis director) / Juarez, Joseph (Committee member) / Industrial, Systems & Operations Engineering Prgm (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2020-12