http://hdl.handle.net/1957/16561 2013-06-19T05:57:13Z http://hdl.handle.net/1957/39535 Determination of cohesive parameters for aerospace adhesives Hortnagl, Josef G. The use of adhesives in demanding engineering applications is a very common occurrence in the modern world. These adhesives are taking the role of many traditional fasteners, especially in the area of fiber reinforced composites. As the use of these adhesives become more common place, better understanding of their mechanics and failure methods are needed. Adhesives typically do not behave like metals under extreme loading, and so traditional failure analysis methods are not adequate. New numerical methods that combined strength and energy fracture mechanics have shown to be better modeling tools for adhesives. Cohesive zone analysis is one of those methods. This method is limited by the adhesive constitutive parameters that dictate how the cohesive elements will behave in the finite element analysis. There has been a number of studies focused on experimental methods for collecting these parameters, but there exist no prevalent database of values that can be used. The current study will use several different methods to collect cohesive parameters for a group of aerospace adhesives. This will allow researchers to more accurately model structures that use these adhesives, as well as understand strengths and weaknesses between the different testing methods. The adhesives tested in this study were Araldite AV4600, 3M DP420, Locktite E120, Hysol E9359.3, and JB weld. A traction law device was used to investigate and calculate cohesive parameters in mode I and mode II loading. Additional test were used to collect individual cohesive parameters for the two loading modes. After testing was concluded traction laws were created and cohesive strength and toughness values generated. The different tests shows good agreement in most cases with some margin of error for different adhesives. The traction law device proved to be a capable tool for generating traction laws, but required special testing equipment and extensive post analysis. The process of collecting data with this device was time consuming and delicate. Due to these factors the results showed less agreement between test specimen groups and therefor carried less confidence in the parameters generated. The individual tests showed better agreement between test specimens and required less time for experiments and analysis. These however were not capable of generating full traction law curves. Graduation date: 2013 2013-06-10T00:00:00Z http://hdl.handle.net/1957/39281 Exploring the relationship between engineering design project characteristics and risk indicators Yim, Rachel L. Engineering design projects are implemented to accomplish a variety of goals in organizations. As the complexity of each project grows, the risk and uncertainty accompanying each project increases as well. As a result project managers must identify potential risks to projects and create plans to avoid realized risks leading to project failures. A risk indicator is a set of circumstances that are indicative of the strong likelihood of a risk event occurring during a project. This research was created to explore the relationship between risk indicators and various project characteristics, including project classification (the type of business goals the project was created to fill) and project type (whether the project was a first or a second attempt to solve an engineering design problem). The results of this research are applicable to engineering managers who are responsible for the successful completion of design projects. The research questions addressed in this study were: 1) Is there a difference in the frequency of occurrence between the 36 risk indicator codes? 2) If there is a difference, in the risk indicator frequencies, which risk indicator codes occur most often? 3) Which risk indicator codes are the most prevalent in association with certain project characteristics? These research questions were explored with the intent of discovering the risk indicators that are most important for project managers to consider in creating risk management plans based upon project characteristics. The goal of this research is to contribute to the project management body of knowledge and to provide insight into the nature of the relationship between various project characteristics and risk indicators. To achieve this objective, eleven medium-complexity engineering design projects were selected for study. Two interview protocols were developed to elicit information about critical events occurring during the life cycles of these engineering design projects. Employees from a variety of job functions, who were directly involved in the selected projects, were interviewed. Multiple researchers coded transcripts created from the interviews. Researchers used a code scheme, developed from the literature on project success factors. The text from interview transcripts was analyzed to identify similarities and differences in the frequencies of different risk indicator codes for different project characteristics. Frequently occurring risk indicators were noted and implications for project managers were identified. The projects were divided into groups with similar project characteristics. Differences in the rates of occurrence of risk indicators were used to identify risk indicators, based on these specific project characteristics. Similarities and differences in the rates of occurrence of risk indicators in the different groups of projects were analyzed for emergent themes. The results provided strong evidence for significant differences in the frequency of occurrence for risk indicators based on project characteristics. The most frequently occurring risk indicators differed for three project classifications (strategic, compliance, and operational). The most frequently occurring risk indicators also differed for original and rework projects. Nonparametric statistical tests were also applied to the data to test between significant differences across all risk indicators, using the same project characteristics. Communication challenges were prevalent for all types of projects. Research has shown that inadequate communication can cause time and cost overruns on projects and can lead to rework projects. The types of communication challenges that were the most frequent differed between project classifications. For compliance projects, the most predominant communication risk was between the organization and suppliers. Communication risks between the organization and the customers occurred most often in operational projects. Finally in strategic projects, the most frequently occurring risks to communication occurred internally, between different business and engineering groups within the organization. Another important theme was the need for standard procedures to provide adequate documentation to the different groups involved in projects. Risks associated with a lack of information provided to the different business and engineering groups working together on projects, were common among all projects. Many interviewees suggested the need for standard procedures to provide all necessary information to all groups assigned to each project, in order to facilitate the coordination of the work. A lack of up front planning was detrimental for both original and rework projects. A lack of up front planning in original projects, at times, resulted in project failure, thereby creating the need for a rework project. In rework projects, planning at the beginning of a project was sometimes rushed due to the urgency of the project, thereby causing additional risks to the success of rework projects later on in the project life cycle. Project managers can use the findings from this research to create more effective risk management plans tailored to the characteristics of a particular project. Knowledge of the risk indicators with the highest frequency of occurrence in each type of project can direct managers to the most effective use of risk management resources. The results of this research also add to the project management body of knowledge and provide a deeper understanding of the relationship between project characteristics and specific risk factors. The results also provide evidence that the project classification and project type are important determinants of the types of risks that will likely be faced in the course of a project. The approach used for this study can be applied to other industries and other types of projects to further extend the understanding of the relationship between project characteristics and risks. While there was evidence that some risks are typical to all design projects, a larger study is needed to generalize these findings beyond design projects and beyond the engineering organization studied. Graduation date: 2013 2013-05-14T00:00:00Z http://hdl.handle.net/1957/39194 A framework to model reliability and failures in complex systems during the early engineering design process O'Halloran, Bryan M. An open area of research in complex systems is to move reliability and failure assessments earlier in the engineering design process. When compared to later design, early decisions are cost effective and have a large impact on the system. Standard methods are limited by the availability of data and often rely on detailed representations of the system. This dissertation will focus on this need by developing an Early Design Reliability and Failure Modeling framework. This framework presents a suite of engineering design methods used to assess reliability and failure modes during the early design process. Several instances are provided to show how specialized data sets can be developed that are specific to early design applications. Specific importance in this dissertation will be placed on design theory and methodology to support decision making. Overall these methods address important early design considerations including the automated identification and mitigation of high-occurrence failure modes, the abstraction level of failure modes and mechanisms, quantifying uncertainty and functional reliability, a customer's risk of losing functionality, a system's risk to a set of failure modes, and the behavior modeling of important failure modes. Graduation date: 2013 2013-05-03T00:00:00Z http://hdl.handle.net/1957/38662 A multiagent approach to identifying innovation in design components Rebhuhn, Carrie M. Innovation is a key element for a product to achieve market success, but identifying it within product or even defining the term is a difficult task. Identifying innovation has been approached in many different ways. Experts in design engineering may identify innovative designs based on an analysis of a product's functions, and statistical techniques may be used to evaluate innovation within a set of products. While there are numerous ways to recognize innovation in a product, there is no straightforward way of identifying how much each component within a product contributes to its innovation. Multiagent systems face an analogous problem; though the performance of a system may be easily assessed, the complex interactions of the agents makes using this system performance to reward each agent ineffective. Difference rewards provide a mechanism for a multiagent system to better quantify the impact of an agent on the system's performance. We introduce the Creative Agents for Repository-Reliant Innovation Engineering (CARRIE) algorithm, which frames the problem of creating a design as supervised learning within a multiagent system. Agents simulate the design process by selecting components to create a product from their training data, and receive external evaluations based on the product-level innovation score. In order to propagate this score to the component selections, the CARRIE algorithm incorporates difference rewards to identify components that positively or negatively impact the overall innovation score within a set of products. Traditional application of the difference reward requires a way to calculate a system’s performance, and then a way to recalculate this performance when an agent is removed in simulation. This presents a problem when we only have the numerical evaluation of the innovation in a product to use as a system performance score, and no indication of how this innovation score was obtained. For this reason, the CARRIE algorithm uses a method by which we can calculate the system score based on the novelty scores of the components in a product. This enables the computation of the difference reward in this domain without actually having a mathematical formulation of an arbitrary system reward. Graduation date: 2013 2013-05-13T00:00:00Z