The increased use of advanced composites in aerospace manufacturing has led to the development of new production processes and technology. The implementation of advanced composites manufacturing technology is poorly served by traditional cost accounting methods, which distort costs by using inappropriate volume-based allocations of overhead. Activity-based costing has emerged as a methodology which provides more accurate allocation of costs to products or activities by their usage of company resources. Better designs may also be produced if designers could evaluate the cost implications of their choices early in the design process. This research describes a methodology whereby companies can improve product cost estimation at the conceptual design phase, using intelligent searching and arrangement of existing accounting data to enable designers to access the activity cost information more readily. The concept has considerable scope for application in industry because it will allow companies to make better use of information that is already being recorded in their information systems, by providing it in a form which will enable designers to make better informed decisions during the design process. The design decision support framework is illustrated by applying it to a typical problem in aerospace composites manufacturing. Feasibility of the approach is demonstrated using a prototype software model of the Design Decision Support System, implemented using commercially available software. / Ph. D.

The goal of this dissertation is to study optimization models that integrate location, production, inventory and transportation decisions for industrial products and apply the knowledge gained to develop supply chains for agricultural products (biomass). We estimate unit cost for the whole biomass-to-biofuels’ supply chain which is the per gallon cost for biofuels up till it reaches the markets. The unit cost estimated is the summation of location, production, inventory holding, and transportation costs. In this dissertation, we focus on building mathematical models for designing and managing the biomass-to-biofuels’ supply chains. The computational complexity of the developed models makes it advisable to use heuristic solution procedures. We develop a Lagrangean decomposition heuristic. In our heuristic, we divide the problem into two sub-problems, sub-problem 1 is a transportation problem and sub-problem 2 is a combination of a capacitated facility location and production planning problem. Subproblem 2 is further divided by commodities. The algorithm is tested for a number of different scenarios. We also develop a decision support system (DSS) for the biomass-to-biofuels’ supply chain. In our DSS, the main problem is divided into four easy-to-solve supply chain problems. These problems were determined based on our knowledge of supply chain and discussions with the experts from the biomass and biofuels’ sector. The DSS is coded using visual basic applications (VBA) for Excel and has a simple user interface which assists the user in running different types of supply chain problems and provides results in form of reports which are easy to understand.

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Numeric groundwater modeling techniques can assist water resources regulators pursuing prudent and foresightful aquifer management decisions. Unfortunately, the amount of time and professional expertise required to wield modern groundwater models often exceeds the resources of regulating agencies – even for simple modeling tasks that are repetitive in nature. In an effort to increase the accessibility of groundwater modeling resources, a server-based automated well permitting decision support system was designed. The prototype system allows a user to 1) input properties for any number of candidate wells, 2) execute an associated MOFLOW model, and 3) view relevant results of the simulation on a map such as drawdown contours and regions of decreased spring flow. The system extends the existing concept of automated well permitting geoprocessing, which involves customizable tools built with ArcGIS and Arc Hydro Groundwater geoprocessing components, by moving the geoprocessing tool to a server and creating an interactive web interface built with the Google Earth plug-in. Several strategies to initiate the server-based geoprocessing tool were considered, with and without ArcGIS Server software. A realistic case study was included to demonstrate the system in action. Such server-based automated decision support systems have promising potential to increase the accessibility of groundwater models, facilitating professional management of crucial water resources.

Financially literate consumers are empowered with the knowledge and skills necessary to make sound financial decisions that ensure their long-term economic well-being. Within the context of the range of cognitive, psychological, and social factors that influence consumer behavior, simulations enhance financial literacy by developing consumers’ mental models for decision-making. Technical communicators leverage plain language and visual language techniques to communicate complex financial concepts in ways that consumers can relate to and understand. Simulations for financial education and decision support illustrate abstract financial concepts, provide a means of safe experimentation, and allow consumers to make informed choices based on a longitudinal comparison of decision outcomes. Technical communicators develop content based on best practices and conduct evaluations to ensure that simulations present information that is accessible, usable, and focused on the end-user. Potential simulation formats range from low- to high-fidelity. Low-fidelity simulations present static data in print or digital formats. Mid-fidelity simulations provide digital interactive decision support tools with dynamic user inputs. More complex high-fidelity simulations use narrative and dramatic elements to situate learning in applied contexts

Nuclear govemment-oversight-agency (GOA) managers face increasing numbers of strategic decisions with fewer people to support their strategic decision processes. There is an increasing need to find new means of strategic decision support for nuclear GOA managers. This exploratory research contributes toward meeting this need by: (1) developing a set of contextual models of strategic decision making that link mental activities with information needs; (2) deriving a methodology to study the characteristics of the information needed by nuclear GOA managers when formulating strategic problems; and (3) demonstrating the methodology's use in drawing implications for designing decision tools. The literature reviewed in the areas of management. strategic management, decision making, decision tools, and information characteristics formed the foundation for the development of three contextual models of individual, strategic decision making. The most detailed model. the Elementary Mental Activities Model, links the mental activities of strategic decision making with types of information, providing a perspective for strategic information. An experiment was designed to engage nuclear GOA managers in realistic, strategic decision situations. Concurrent verbalizations yielded verbal protocols. Units of information used were identified according to the types of information-entities, attributes, values. relationships. and operators-in the Elementary Mental Activities Model. Unique units of information were identified during coding. "Frequency of use" and "use" by subject and by exercise were calculated for each unit of information. The information characteristics source. level of detail, class, internal/external, and relationship complexity were assigned to entities, relationships. or operators. Thirteen analyses of the data demonstrated the methodology's value for research in strategic decision processes, in strategic information, and in decision tools. All but one of the results were supported in the literature on strategic decision processes. The research led to the following, overall conclusions. 1. The Elementary Mental Activities Model represents the information use of nuclear GOA managers engaged in strategic decision processes and characterizes their strategic decision processes in terms of information use. 2. The methodology developed is useful in measuring the information use of nuclear GOA managers engaged in strategic decision processes for the purposes of determining information needs for designing decision tools. / Ph. D.

Improved strategic location of an Emergency Medical Service (EMS) facility can significantly increase EMS efficiency. Urban planners need to consider a location that satisfies multiple criteria in order to make an informed decision about a future EMS facility site. Apart from basic criteria such as parcel value and size, decision-makers need to consider area and population coverage from potential parcels. Geographic Information Systems (GIS) provide an adequate analysis environment for EMS facility siting as many considered criteria are of a spatial nature. However, urban planners making decisions about an EMS facility site often lack the necessary expertise to make full use of challenging GIS tools. In order to help urban planners in the analysis process, this research developed a Spatial Decision Support System (SDSS) for EMS facility siting. The system was developed in ESRI ArcGIS (9.3) using the Visual Basic for Applications (VBA) programming environment. The objective of the system was to integrate spatial data, analysis, and visualization in a single system to help users evaluate a facility siting problem. The system's performance was tested using data for the Town of Blacksburg, VA. In addition, the system was evaluated by local planners and GIS staff with experience in EMS facility siting. Planners agreed the system enables more comprehensive and straightforward use of GIS for EMS facility siting analysis than other available siting tools. Potential improvements include a simpler user interface, synthesis of geoprocessing techniques, reduction of analysis time through automation, and better decision-making by improved visualization of results. / Master of Science

This study examines factors that influence the intent to use and actual use of decision support software (DSS) technology by emergency management officials to facilitate disaster response management. The unified theory of acceptance and use of technology popularized by scholars from the field of information sciences (IS) for the private sector is adapted and extended to examine technology use in the public sector, specifically by emergency managers. An e-survey was sent to 1, 452 city and county emergency management officials from FEMA region VI and complete responses obtained from 194 were analyzed. Findings suggest that social influence is the strongest predictor of intent to use DSS technology by emergency managers, unlike private sector studies where performance expectancy was the strongest predictor. Additionally, effort expectancy, collaboration, social vulnerability, professionalism, performance expectancy, and gender explained 40 percent of their intent to use DSS technology. Factors explaining actual use of technology were intent to use technology, having an in house GIS specialist, and age of the emergency manager. This research successfully closes the gap in IS and disaster literature by being the first to focus on factors influencing technology use by emergency managers for decision making in disaster response. It underscores the importance of collaboration not only for post-disaster activities but also as a precursor to better disaster preparedness planning that calls for information sharing and technology acceptance and adoption across partnering jurisdictions.