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ContributorsDaval, Charles (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-26
Description
In the industry of manufacturing, each gas turbine engine component begins in a raw state such as bar stock and is routed through manufacturing processes to define its final form before being installed on the engine. What is the follow-up to this part? What happens when over time and usage it wears? Several factors have created a section of the manufacturing industry known as aftermarket to support the customer in their need for restoration and repair of their original product. Once a product has reached a wear factor or cycle limit that cannot be ignored, one of the options is to have it repaired to maintain use of the core. This research investigated the study into the creation and application of repair development methodology that can be utilized by current and new manufacturing engineers of the world. Those who have been in this field for some time will find the process thought provoking while the engineering students can develop a foundation of thinking to prepare for the common engineering problems they will be tasked to resolve. The examples, figures and tables are true issues of the industry though the data will have been changed due to proprietary factors. The results of the study reveals, under most scenarios, a solid process can be followed to proceed with the best options for repair based on the initial discrepancy. However, this methodology will not be a "catch-all" process but a guidance that will develop the proper thinking in evaluation of the repair options and the possible failure modes of each choice. As with any continuous improvement tool, further research is needed to test the applicability of this process in other fields.
ContributorsMoedano, Jesus A (Author) / Lewis, Sharon L (Thesis advisor) / Meitz, Robert (Committee member) / Georgeou, Trian (Committee member) / Arizona State University (Publisher)
Created2013
Description
This thesis contains the applications of the ASU mathematical model (Tolerance Maps, T-Maps) to the construction of T-Maps for patterns of line profiles. Previously, Tolerance Maps were developed for patterns of features such as holes, pins, slots and tabs to control their position. The T-Maps that are developed in this thesis are fully compatible with the ASME Y14.5 Standard. A pattern of square profiles, both linear and 2D, is used throughout this thesis to illustrate the idea of constructing the T-Maps for line profiles. The Standard defines two ways of tolerancing a pattern of profiles - Composite Tolerancing and Multiple Single Segment Tolerancing. Further, in the composite tolerancing scheme, there are two different ways to control the entire pattern - repeating a single datum or two datums in the secondary datum reference frame. T-Maps are constructed for all the different specifications. The Standard also describes a way to control the coplanarity of discontinuous surfaces using a profile tolerance and T-Maps have been developed. Since verification of manufactured parts relative to the tolerance specifications is crucial, a least squares fit approach, which was developed earlier for line profiles, has been extended to patterns of line profiles. For a pattern, two tolerances are specified, and the manufactured profile needs to lie within the tolerance zones established by both of these tolerances. An i-Map representation of the manufactured variation, located within the T-Map is also presented in this thesis.
ContributorsRao, Shyam Subramanya (Author) / Davidson, Joseph K. (Thesis advisor) / Arizona State University (Publisher)
Created2014
DescriptionThe purpose of this project is to explore the influence of folk music in guitar compositions by Manuel Ponce from 1923 to 1932. It focuses on his Tres canciones populares mexicanas and Tropico and Rumba.
ContributorsGarcia Santos, Arnoldo (Author) / Koonce, Frank (Thesis advisor) / Rogers, Rodney (Committee member) / Rotaru, Catalin (Committee member) / Arizona State University (Publisher)
Created2014
Description
A low temperature amorphous oxide thin film transistor (TFT) backplane technology for flexible organic light emitting diode (OLED) displays has been developed to create 4.1-in. diagonal backplanes. The critical steps in the evolution of the backplane process include the qualification and optimization of the low temperature (200 °C) metal oxide process, the stability of the devices under forward and reverse bias stress, the transfer of the process to flexible plastic substrates, and the fabrication of white organic light emitting diode (OLED) displays. Mixed oxide semiconductor thin film transistors (TFTs) on flexible plastic substrates typically suffer from performance and stability issues related to the maximum processing temperature limitation of the polymer. A novel device architecture based upon a dual active layer enables significant improvements in both the performance and stability. Devices are directly fabricated below 200 ºC on a polyethylene naphthalate (PEN) substrate using mixed metal oxides of either zinc indium oxide (ZIO) or indium gallium zinc oxide (IGZO) as the active semiconductor. The dual active layer architecture allows for adjustment in the saturation mobility and threshold voltage stability without the requirement of high temperature annealing, which is not compatible with flexible colorless plastic substrates like PEN. The device performance and stability is strongly dependent upon the composition of the mixed metal oxide; this dependency provides a simple route to improving the threshold voltage stability and drive performance. By switching from a single to a dual active layer, the saturation mobility increases from 1.2 cm2/V-s to 18.0 cm2/V-s, while the rate of the threshold voltage shift decreases by an order of magnitude. This approach could assist in enabling the production of devices on flexible substrates using amorphous oxide semiconductors.
ContributorsMarrs, Michael (Author) / Raupp, Gregory B (Thesis advisor) / Vogt, Bryan D (Thesis advisor) / Allee, David R. (Committee member) / Arizona State University (Publisher)
Created2011
Description
The demand for miniaturized components with feature sizes as small as tens of microns and tolerances as small as 0.1 microns is on the rise in the fields of aerospace, electronics, optics and biomedical engineering. Micromilling has proven to be a process capable of generating the required accuracy for these features and is an alternative to various non-mechanical micro-manufacturing processes which are limited in terms of cost and productivity, especially at the micro-meso scale. The micromilling process is on the surface, a miniaturized version of conventional milling, hence inheriting its benefits. However, the reduction in scale by a few magnitudes makes the process peculiar and unique; and the macro-scale theories have failed to successfully explain the micromilling process and its machining parameters. One such characteristic is the unpredictable nature of tool wear and breakage. There is a large cost benefit that can be realized by improving tool life. Workpiece rejection can also be reduced by successfully monitoring the condition of the tool to avoid issues. Many researchers have developed Tool Condition Monitoring and Tool Wear Modeling systems to address the issue of tool wear, and to obtain new knowledge. In this research, a tool wear modeling effort is undertaken with a new approach. A new tool wear signature is used for real-time data collection and modeling of tool wear. A theoretical correlation between the number of metal chips produced during machining and the condition of the tool is introduced. Experimentally, it is found that the number of chips produced drops with respect to the feedrate of the cutting process i.e. when the uncut chip thickness is below the theoretical minimum chip thickness.
ContributorsBajaj, Anuj Kishorkumar (Author) / SODEMANN, ANGELA A (Thesis advisor) / Bekki, Jeniffer (Committee member) / Hsu, Keng (Committee member) / Arizona State University (Publisher)
Created2015
ContributorsKotronakis, Dimitris (Performer) / ASU Library. Music Library (Publisher)
Created2018-03-01
Description
Company X is one of the world's largest semiconductor companies in the world, having a current market capitalization of 177.44 Billion USD, an enterprise value of 173.6 Billion USD, and generated 52.7 billion USD in revenue in fiscal year 2013. Recently, Company X has been looking to expand its Foundry business. The Foundry business in the semiconductor business is the actual process of making the chips. This process can be approached in several different ways by companies who need their chips built. A company, like TSMC, can be considered a pure-play company and only makes chips for other companies. A fabless company, like Apple, creates its own chip design and then allows another company to build them. It also uses other chip designs for its products, but outsources the building to another company. Lastly, the integrated device manufacturing companies like Samsung or Company X both design and build the chip. The foundry industry is a rather novel market for Company X because it owns less than 1 percent of the market. However, the industry itself is rather large, generating a total of 40 billion dollars in revenue annually, with expectations to have increasing year over year growth into the foreseeable future. The industry is fairly concentrated with TSMC being the top competitor, owning roughly 50 percent of the market with Samsung and Global Foundries lagging behind as notable competitors. It is a young industry and there is potential opportunity for companies that want to get into the business. For Company X, it is not only another market to get into, but also an added business segment to supplant their business segments that are forecasted to do poorly in the near future. This thesis will analyze the financial opportunity for Company X in the foundry space. Our final product is a series of P&L's which illustrate our findings. The results of our analysis were presented and defended in front of a panel of Company X managers and executives.
ContributorsJones, Trevor (Author) / Matiski, Matthew (Co-author) / Green, Alex (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Department of Finance (Contributor) / W. P. Carey School of Business (Contributor) / Barrett, The Honors College (Contributor)
Created2015-05
Description
Upon investigating the current state of the high scrap problem at Niagara Bottling's Phoenix manufacturing facility, it was found that 49% of the scrap was being generated at the bottling lines in the form of plastic bottles, and 39% of scrap took the form of preforms accumulated at either the bottling lines or the injection molding machines. The scope of this project includes all forms of polyethylene terephthalate (PET), but the large accumulation of scrap in these areas suggests a primary focus on the bottling lines and the injection molding machines. Further analysis of the bottling lines found that the filler at each line as well as the blower on line X1 were the biggest contributors to the scrap accumulation problem. Each of these machines was seeing over 0.4% of bottles rejected at the visual inspection units. Due to the underlying status and quality issues of the injection molding machines that were beyond the scope of this project, this process was only investigated for solutions involving the overall processes and people. Based on the data and process flow analysis there were several solutions proposed including a root-cause analysis of the highest faulting machines, the repair of the injection molding overhead conveyor systems, the creation of a low waste environment, and the implementation a scrap tracking and analysis process. Based on the current high variability in the scrap experience across all machines, it is recommended that Niagara Phoenix pursue the scrap tracking and analysis alternative. After the implementing the scrap tracking and analysis process, the initial results were encouraging and could potentially warrant the investment in a software platform that could automate the collection of data necessary for this process. Based on the initial results of the manual collection and analysis process, each individual line show signs of potential reduction in the scrap rate of over 50%. According to this improvement, purchasing the software platform would see a payoff period of only 36 days.
ContributorsSanchez, Thomas Camden (Author) / Kellso, James (Thesis director) / Lupe, Munoz (Committee member) / Barrett, The Honors College (Contributor) / School of International Letters and Cultures (Contributor) / Department of Supply Chain Management (Contributor)
Created2015-05
Description
Over the course of six months, we have worked in partnership with Arizona State University and a leading producer of semiconductor chips in the United States market (referred to as the "Company"), lending our skills in finance, statistics, model building, and external insight. We attempt to design models that help predict how much time it takes to implement a cost-saving project. These projects had previously been considered only on the merit of cost savings, but with an added dimension of time, we hope to forecast time according to a number of variables. With such a forecast, we can then apply it to an expense project prioritization model which relates time and cost savings together, compares many different projects simultaneously, and returns a series of present value calculations over different ranges of time. The goal is twofold: assist with an accurate prediction of a project's time to implementation, and provide a basis to compare different projects based on their present values, ultimately helping to reduce the Company's manufacturing costs and improve gross margins. We believe this approach, and the research found toward this goal, is most valuable for the Company. Two coaches from the Company have provided assistance and clarified our questions when necessary throughout our research. In this paper, we begin by defining the problem, setting an objective, and establishing a checklist to monitor our progress. Next, our attention shifts to the data: making observations, trimming the dataset, framing and scoping the variables to be used for the analysis portion of the paper. Before creating a hypothesis, we perform a preliminary statistical analysis of certain individual variables to enrich our variable selection process. After the hypothesis, we run multiple linear regressions with project duration as the dependent variable. After regression analysis and a test for robustness, we shift our focus to an intuitive model based on rules of thumb. We relate these models to an expense project prioritization tool developed using Microsoft Excel software. Our deliverables to the Company come in the form of (1) a rules of thumb intuitive model and (2) an expense project prioritization tool.
ContributorsAl-Assi, Hashim (Co-author) / Chiang, Robert (Co-author) / Liu, Andrew (Co-author) / Ludwick, David (Co-author) / Simonson, Mark (Thesis director) / Hertzel, Michael (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor) / Department of Finance (Contributor) / Department of Economics (Contributor) / Department of Supply Chain Management (Contributor) / School of Accountancy (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Mechanical and Aerospace Engineering Program (Contributor) / WPC Graduate Programs (Contributor)
Created2015-05