Matching Items (75)
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Description
Nowadays product reliability becomes the top concern of the manufacturers and customers always prefer the products with good performances under long period. In order to estimate the lifetime of the product, accelerated life testing (ALT) is introduced because most of the products can last years even decades. Much research has

Nowadays product reliability becomes the top concern of the manufacturers and customers always prefer the products with good performances under long period. In order to estimate the lifetime of the product, accelerated life testing (ALT) is introduced because most of the products can last years even decades. Much research has been done in the ALT area and optimal design for ALT is a major topic. This dissertation consists of three main studies. First, a methodology of finding optimal design for ALT with right censoring and interval censoring have been developed and it employs the proportional hazard (PH) model and generalized linear model (GLM) to simplify the computational process. A sensitivity study is also given to show the effects brought by parameters to the designs. Second, an extended version of I-optimal design for ALT is discussed and then a dual-objective design criterion is defined and showed with several examples. Also in order to evaluate different candidate designs, several graphical tools are developed. Finally, when there are more than one models available, different model checking designs are discussed.
ContributorsYang, Tao (Author) / Pan, Rong (Thesis advisor) / Montgomery, Douglas C. (Committee member) / Borror, Connie (Committee member) / Rigdon, Steve (Committee member) / Arizona State University (Publisher)
Created2013
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During the initial stages of experimentation, there are usually a large number of factors to be investigated. Fractional factorial (2^(k-p)) designs are particularly useful during this initial phase of experimental work. These experiments often referred to as screening experiments help reduce the large number of factors to a smaller set.

During the initial stages of experimentation, there are usually a large number of factors to be investigated. Fractional factorial (2^(k-p)) designs are particularly useful during this initial phase of experimental work. These experiments often referred to as screening experiments help reduce the large number of factors to a smaller set. The 16 run regular fractional factorial designs for six, seven and eight factors are in common usage. These designs allow clear estimation of all main effects when the three-factor and higher order interactions are negligible, but all two-factor interactions are aliased with each other making estimation of these effects problematic without additional runs. Alternatively, certain nonregular designs called no-confounding (NC) designs by Jones and Montgomery (Jones & Montgomery, Alternatives to resolution IV screening designs in 16 runs, 2010) partially confound the main effects with the two-factor interactions but do not completely confound any two-factor interactions with each other. The NC designs are useful for independently estimating main effects and two-factor interactions without additional runs. While several methods have been suggested for the analysis of data from nonregular designs, stepwise regression is familiar to practitioners, available in commercial software, and is widely used in practice. Given that an NC design has been run, the performance of stepwise regression for model selection is unknown. In this dissertation I present a comprehensive simulation study evaluating stepwise regression for analyzing both regular fractional factorial and NC designs. Next, the projection properties of the six, seven and eight factor NC designs are studied. Studying the projection properties of these designs allows the development of analysis methods to analyze these designs. Lastly the designs and projection properties of 9 to 14 factor NC designs onto three and four factors are presented. Certain recommendations are made on analysis methods for these designs as well.
ContributorsShinde, Shilpa (Author) / Montgomery, Douglas C. (Thesis advisor) / Borror, Connie (Committee member) / Fowler, John (Committee member) / Jones, Bradley (Committee member) / Arizona State University (Publisher)
Created2012
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Description
A P-value based method is proposed for statistical monitoring of various types of profiles in phase II. The performance of the proposed method is evaluated by the average run length criterion under various shifts in the intercept, slope and error standard deviation of the model. In our proposed approach, P-values

A P-value based method is proposed for statistical monitoring of various types of profiles in phase II. The performance of the proposed method is evaluated by the average run length criterion under various shifts in the intercept, slope and error standard deviation of the model. In our proposed approach, P-values are computed at each level within a sample. If at least one of the P-values is less than a pre-specified significance level, the chart signals out-of-control. The primary advantage of our approach is that only one control chart is required to monitor several parameters simultaneously: the intercept, slope(s), and the error standard deviation. A comprehensive comparison of the proposed method and the existing KMW-Shewhart method for monitoring linear profiles is conducted. In addition, the effect that the number of observations within a sample has on the performance of the proposed method is investigated. The proposed method was also compared to the T^2 method discussed in Kang and Albin (2000) for multivariate, polynomial, and nonlinear profiles. A simulation study shows that overall the proposed P-value method performs satisfactorily for different profile types.
ContributorsAdibi, Azadeh (Author) / Montgomery, Douglas C. (Thesis advisor) / Borror, Connie (Thesis advisor) / Li, Jing (Committee member) / Zhang, Muhong (Committee member) / Arizona State University (Publisher)
Created2013
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Description
The ever-changing economic landscape has forced many companies to re-examine their supply chains. Global resourcing and outsourcing of processes has been a strategy many organizations have adopted to reduce cost and to increase their global footprint. This has, however, resulted in increased process complexity and reduced customer satisfaction. In order

The ever-changing economic landscape has forced many companies to re-examine their supply chains. Global resourcing and outsourcing of processes has been a strategy many organizations have adopted to reduce cost and to increase their global footprint. This has, however, resulted in increased process complexity and reduced customer satisfaction. In order to meet and exceed customer expectations, many companies are forced to improve quality and on-time delivery, and have looked towards Lean Six Sigma as an approach to enable process improvement. The Lean Six Sigma literature is rich in deployment strategies; however, there is a general lack of a mathematical approach to deploy Lean Six Sigma in a global enterprise. This includes both project identification and prioritization. The research presented here is two-fold. Firstly, a process characterization framework is presented to evaluate processes based on eight characteristics. An unsupervised learning technique, using clustering algorithms, is then utilized to group processes that are Lean Six Sigma conducive. The approach helps Lean Six Sigma deployment champions to identify key areas within the business to focus a Lean Six Sigma deployment. A case study is presented and 33% of the processes were found to be Lean Six Sigma conducive. Secondly, having identified parts of the business that are lean Six Sigma conducive, the next steps are to formulate and prioritize a portfolio of projects. Very often the deployment champion is faced with the decision of selecting a portfolio of Lean Six Sigma projects that meet multiple objectives which could include: maximizing productivity, customer satisfaction or return on investment, while meeting certain budgetary constraints. A multi-period 0-1 knapsack problem is presented that maximizes the expected net savings of the Lean Six Sigma portfolio over the life cycle of the deployment. Finally, a case study is presented that demonstrates the application of the model in a large multinational company. Traditionally, Lean Six Sigma found its roots in manufacturing. The research presented in this dissertation also emphasizes the applicability of the methodology to the non-manufacturing space. Additionally, a comparison is conducted between manufacturing and non-manufacturing processes to highlight the challenges in deploying the methodology in both spaces.
ContributorsDuarte, Brett Marc (Author) / Fowler, John W (Thesis advisor) / Montgomery, Douglas C. (Thesis advisor) / Shunk, Dan (Committee member) / Borror, Connie (Committee member) / Konopka, John (Committee member) / Arizona State University (Publisher)
Created2011
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Description
This dissertation presents methods for the evaluation of ocular surface protection during natural blink function. The evaluation of ocular surface protection is especially important in the diagnosis of dry eye and the evaluation of dry eye severity in clinical trials. Dry eye is a highly prevalent disease affecting vast numbers

This dissertation presents methods for the evaluation of ocular surface protection during natural blink function. The evaluation of ocular surface protection is especially important in the diagnosis of dry eye and the evaluation of dry eye severity in clinical trials. Dry eye is a highly prevalent disease affecting vast numbers (between 11% and 22%) of an aging population. There is only one approved therapy with limited efficacy, which results in a huge unmet need. The reason so few drugs have reached approval is a lack of a recognized therapeutic pathway with reproducible endpoints. While the interplay between blink function and ocular surface protection has long been recognized, all currently used evaluation techniques have addressed blink function in isolation from tear film stability, the gold standard of which is Tear Film Break-Up Time (TFBUT). In the first part of this research a manual technique of calculating ocular surface protection during natural blink function through the use of video analysis is developed and evaluated for it's ability to differentiate between dry eye and normal subjects, the results are compared with that of TFBUT. In the second part of this research the technique is improved in precision and automated through the use of video analysis algorithms. This software, called the OPI 2.0 System, is evaluated for accuracy and precision, and comparisons are made between the OPI 2.0 System and other currently recognized dry eye diagnostic techniques (e.g. TFBUT). In the third part of this research the OPI 2.0 System is deployed for use in the evaluation of subjects before, immediately after and 30 minutes after exposure to a controlled adverse environment (CAE), once again the results are compared and contrasted against commonly used dry eye endpoints. The results demonstrate that the evaluation of ocular surface protection using the OPI 2.0 System offers superior accuracy to the current standard, TFBUT.
ContributorsAbelson, Richard (Author) / Montgomery, Douglas C. (Thesis advisor) / Borror, Connie (Committee member) / Shunk, Dan (Committee member) / Pan, Rong (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Along with the number of technologies that have been introduced over a few years ago, gesture-based human-computer interactions are becoming the new phase in encompassing the creativity and abilities for users to communicate and interact with devices. Because of how the nature of defining free-space gestures influence user's preference and

Along with the number of technologies that have been introduced over a few years ago, gesture-based human-computer interactions are becoming the new phase in encompassing the creativity and abilities for users to communicate and interact with devices. Because of how the nature of defining free-space gestures influence user's preference and the length of usability of gesture-driven devices, defined low-stress and intuitive gestures for users to interact with gesture recognition systems are necessary to consider. To measure stress, a Galvanic Skin Response instrument was used as a primary indicator, which provided evidence of the relationship between stress and intuitive gestures, as well as user preferences towards certain tasks and gestures during performance. Fifteen participants engaged in creating and performing their own gestures for specified tasks that would be required during the use of free-space gesture-driven devices. The tasks include "activation of the display," scroll, page, selection, undo, and "return to main menu." They were also asked to repeat their gestures for around ten seconds each, which would give them time and further insight of how their gestures would be appropriate or not for them and any given task. Surveys were given at different time to the users: one after they had defined their gestures and another after they had repeated their gestures. In the surveys, they ranked their gestures based on comfort, intuition, and the ease of communication. Out of those user-ranked gestures, health-efficient gestures, given that the participants' rankings were based on comfort and intuition, were chosen in regards to the highest ranked gestures.
ContributorsLam, Christine (Author) / Walker, Erin (Thesis director) / Danielescu, Andreea (Committee member) / Barrett, The Honors College (Contributor) / Ira A. Fulton School of Engineering (Contributor) / School of Arts, Media and Engineering (Contributor) / Department of English (Contributor) / Computing and Informatics Program (Contributor)
Created2015-05
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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
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G3Box's 2013 Marketing Plan outlines a strategic plan and short term operational strategies for the company. The document includes a discussion of the company's decision to enter the market for healthcare facilities in developing counties, and a situation assessment of the market conditions. G3Box is targeting small and large NGOs

G3Box's 2013 Marketing Plan outlines a strategic plan and short term operational strategies for the company. The document includes a discussion of the company's decision to enter the market for healthcare facilities in developing counties, and a situation assessment of the market conditions. G3Box is targeting small and large NGOs that currently provide healthcare facilities in developing countries. The market size for healthcare aid in developing countries is estimated to be $1.7 billion. The plan also analyses the customer's value chain and buying cycle by using voice of the customer data. The strategic position analysis profiles G3Box's competition and discusses the company's differential advantage versus other options for healthcare facilities in developing countries. Next the document discusses G3Box's market strategy and implementation, along with outlining a value proposition for the company. G3Box has two objectives for 2013: 1) Increase sales revenue to $1.3 million and 2) increase market presence to 25%. In order to reach these objectives, G3Box has developed a primary and secondary strategic focus for each objective. The primary strategies are relationship selling and online marketing. The secondary strategies are developing additional value-added activities and public relations.
ContributorsWalters, John (Author) / Denning, Michael (Thesis director) / Ostrom, Lonnie (Committee member) / Carroll, James (Committee member) / Barrett, The Honors College (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2012-12
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Description
The majority of the 52 photovoltaic installations at ASU are governed by power purchase agreements (PPA) that set a fixed per kilowatt-hour rate at which ASU buys power from the system owner over the period of 15-20 years. PPAs require accurate predictions of the system output to determine the financial

The majority of the 52 photovoltaic installations at ASU are governed by power purchase agreements (PPA) that set a fixed per kilowatt-hour rate at which ASU buys power from the system owner over the period of 15-20 years. PPAs require accurate predictions of the system output to determine the financial viability of the system installations as well as the purchase price. The research was conducted using PPAs and historical solar power production data from the ASU's Energy Information System (EIS). The results indicate that most PPAs slightly underestimate the annual energy yield. However, the modeled power output from PVsyst indicates that higher energy outputs are possible with better system monitoring.
ContributorsVulic, Natasa (Author) / Bowden, Stuart (Thesis director) / Bryan, Harvey (Committee member) / Sharma, Vivek (Committee member) / Barrett, The Honors College (Contributor) / School of Sustainability (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2012-12
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Description
The 21st century engineer will face a diverse set of challenges spread out along a broad spectrum of disciplines. Among others, the fields of energy, healthcare, cyberspace, virtual reality, and neuroscience require monumental efforts by the new generation of engineers to meet the demands of a growing society. However the

The 21st century engineer will face a diverse set of challenges spread out along a broad spectrum of disciplines. Among others, the fields of energy, healthcare, cyberspace, virtual reality, and neuroscience require monumental efforts by the new generation of engineers to meet the demands of a growing society. However the most important, and likely the most under recognized, challenge lies in developing advanced personalized learning. It is the core foundation from which the rest of the challenges can be accomplished. Without an effective method of teaching engineering students how to realize these grand challenges, the knowledge pool from which to draw new innovations and discoveries will be greatly diminished. This paper introduces the Inventors Workshop (IW), a hands-on, passion-based approach to personalized learning. It is intended to serve as a manual that will inform the next generation of student leaders and inventioneers about the core concepts the Inventors Workshop was built upon, and how to continue improvement into the future. Due to the inherent complexities in the grand challenge of personalized learning, the IW has developed a multifaceted solution that is difficult to explain in a single phrase. To enable comprehension of the IW's full vision, the process undergone to date of establishing and expanding the IW is described. In addition, research has been conducted to determine a variety of paths the Inventors Workshop may utilize in future expansion. Each of these options is explored and related to the core foundations of the IW to assist future leaders and partners in effectively improving personalized learning at ASU and beyond.
ContributorsEngelhoven, V. Logan (Author) / Burleson, Winslow (Thesis director) / Peck, Sidnee (Committee member) / Fortun, A. L. Cecil (Committee member) / Barrett, The Honors College (Contributor) / Ira A. Fulton School of Engineering (Contributor)
Created2012-12