Matching Items (2)
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
Description
Nonregular designs for 9-14 factors in 16 runs are a vital alternative for to theregular minimum aberration resolution III fractional factorials. Because there is no complete aliasing between the main factor and two factor interactions, these designs are useful as potential confusion in results is avoided. However, there is another associated complication to this kind of design due to the complete confounding for some of the two- factors. In this research, the focus is on using three different of methods and compare the results. The methods are: Stepwise, least absolute shrinkage and selection operator (LASSO) and the Dantzig selector method. In a previous research, Metcalfe discuss the nonregular designs for 6-8 factors design and studies several analysis methods. She also develops a new method, The Aliased Informed Model Selection (AIMS), for those designs. This research builds upon that.
For this research, simulation is used to develop random models to analyze designs from the class of nonregular fractions with 9 – 14 factors in 16 runs using JMP scripting. Then, analyze the cases with the mentioned methods and find the success rate for each one. The model generations were random with only main factors, or main factors and two- factors interaction as active effects. Effect sizes of 2 and 3 standard deviations are studied. The nonregular design used in this research are 9 and 11-factors design.
Results shows that there is a clear consistency for the main factors only as active effects using all the methods. However, adding the interactions to the active effects degrade the success rate substantially for the Dantzig method. Moreover, as the active effects exceed approximately half of the degrees of freedom for the design the performance for all
i
the methods decreases. Finally, some recommendations are discussed for further research investigation such as AIMS, other variation methods and Augmentation.
ContributorsAlqarni, Hanan (Author) / Montgomery, Douglas (Thesis advisor) / Metcalfe, Carly (Committee member) / Pedrielli, Giulia (Committee member) / Arizona State University (Publisher)
Created2022