ASU Electronic Theses and Dissertations
This collection includes most of the ASU Theses and Dissertations from 2011 to present. ASU Theses and Dissertations are available in downloadable PDF format; however, a small percentage of items are under embargo. Information about the dissertations/theses includes degree information, committee members, an abstract, supporting data or media.
In addition to the electronic theses found in the ASU Digital Repository, ASU Theses and Dissertations can be found in the ASU Library Catalog.
Dissertations and Theses granted by Arizona State University are archived and made available through a joint effort of the ASU Graduate College and the ASU Libraries. For more information or questions about this collection contact or visit the Digital Repository ETD Library Guide or contact the ASU Graduate College at firstname.lastname@example.org.
- 2 English
- Industrial Engineering
- 1 Lead Time Variability
- 1 Port Competitiveness
- 1 Statistics
- 1 Supply Chain
- 1 Total Landed Costs
- 1 Transportation
- 1 generalized linear mixed models
- 1 generalized linear models
- 1 process improvement
- 1 quality and reliability engineering
- 1 semiconductor
- 1 yield modeling
Nowadays ports play a critic role in the supply chains of contemporary companies and global commerce. Since the ports' operational effectiveness is critical on the development of competitive supply chains, their contribution to regional economies is essential. With the globalization of markets, the traffic of containers flowing through the different ports has increased significantly in the last decades. In order to attract additional container traffic and improve their comparative advantages over the competition, ports serving same hinterlands explore ways to improve their operations to become more attractive to shippers. This research explores the hypothesis that lowering the variability of the …
- Meneses Preciado, Cesar Vladimir, Villalobos, Jesus R, Gel, Esma S, et al.
- Created Date
Yield is a key process performance characteristic in the capital-intensive semiconductor fabrication process. In an industry where machines cost millions of dollars and cycle times are a number of months, predicting and optimizing yield are critical to process improvement, customer satisfaction, and financial success. Semiconductor yield modeling is essential to identifying processing issues, improving quality, and meeting customer demand in the industry. However, the complicated fabrication process, the massive amount of data collected, and the number of models available make yield modeling a complex and challenging task. This work presents modeling strategies to forecast yield using generalized linear models (GLMs) …
- Krueger, Dana Cheree, Montgomery, Douglas C., Fowler, John, et al.
- Created Date