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This research integrates a multi-attribute decision-support tool, the Analytic Hierarchy Process (AHP), with a customer-focused design methodology, Quality Function Deployment (QFD). The result is a hybrid methodology more complete than either of the two alone, involving synthesis, analysis, and evaluation activities necessary for completing conceptual system design. An indicator was developed for the overall performance of an organization's product and its competitors’ products using the information in a QFD matrix. In addition, a methodology was developed to determine if essential customer requirements and design-dependent parameters (DDPs) have been adequately identified in the QFD matrix. A mathematical relationship was developed which relates technical and competitive assessments in the QFD matrix and helps test for inconsistencies. Finally, an indicator was developed to assess a new product concept for viability in the marketplace and to be used for accomplishing trade-off analyses. Examples are presented throughout this document to further illustrate the concepts. This research is unique in its application. It adds to the body of knowledge for decision-making in the conceptual design phase of the systems engineering process. / Master of Science

Water heating in the United States has the largest energy consumption of any residential related use. It uses more energy than all other home appliances combined. They have also been implicated as the source of waterborne disease outbreaks. With such high stakes, it is recommended that a Decision Support Tool (DST) be used prior to selection of a water heater for new construction or replacement. Although there are numerous tools available, it is challenging to find a tool that takes into account all factors critical to the selection of water heaters, addresses gaps and barriers, provides adequate information to all stakeholders and finally, assists in rational decision making towards more sustainable choices. The purpose of this research is threefold: (a) to inventory, organize and characterize web-based existing water heater Decision Support Tools (eDSTs) to highlight gaps and/or shortcomings; (b) to develop a Decision Support Tool Skeleton (DSTS) containing a comprehensive list of sustainability capital, criteria and indicators based on Multi-Attribute Decision Making (MADM) approach; (c) to create a stakeholder map comprising supply chain, stakeholder system, decision making process during water heater selections as well as other market factors, using metasynthesis of collected documents. The findings of this research indicate that considerable gaps and shortcomings exist in the current pool of water heater DSTs. To address these barriers, information was captured from various documents in a process of qualitative data analysis called coding. The coding process generated attributes which were used to generate a comprehensive set of capital, criteria, subcriteria and indicators using MADM approach. This organizing structure developed on lines of sustainability assessment will serve as a starting point towards achieving global sustainability in real life. Importantly, information asymmetry between various stakeholders is evidence of the fact that the existing tools are not addressed in an equitable manner. This study will help determine the stakeholder system and the decision making process for selection of water heaters in the residential sector, so as to effectively implement new tools being created. / Master of Science

In what way does different stakeholders assess a decision and its consequences, and how do these assessments differ? When a company stands before a big decision, they need to consider aspects that are economic, ecologic and social. To make a good decision they need to consider the society and its different stakeholder groups. This study examined how different groups values and weights different criteria. The study has been done with the project Sundsvall logistics park as a case, with criteria related to that project. The goal of the study was to find a way to value and weight different criteria and then compare how the company and the stakeholders assesses these criteria. This has been done through interviews with relevant people that has got extra knowledge about the project Sundsvall logistics park, and through a survey that has been sent out to residents of Sundsvall. The informants and respondents got to assess values and weights to the criteria relative to an indirect alternative where the logistics park isn’t built. The data was then compiled using multi attribute utility theory as a tool to present the comparison. The result of the study suggests that the differences between the valuations and weightings of the criteria is partly due to an uncertainty in how the logistics park would affect the criteria, but that the biggest reason probably depends on what perspective the person is viewing the logistics park from. If the person is viewing the logistics park from an industrial perspective, the criteria related to industrial development is getting more important and is going to take up more room in the analysis. If the person is viewing the logistics park from an individual and social perspective, the criteria related to that is more important and takes up more room in the analysis. / På vilket sätt uppskattar olika intressenter ett beslut och dess konsekvenser, och hur skiljer sig dessa uppskattningar åt? När företag idag står inför stora beslut behöver de ta hänsyn till aspekter som är både ekonomiska, ekologiska och sociala. För att beslutet ska bli bra behöver de ta hänsyn till samhället och dess olika intressentgrupper. Denna studie är en undersökning av hur olika grupper värderar och viktar olika kriterier. Studien har utförts mot projektet Sundsvall Logistikpark med kriterier relaterade till projektet. Målet med studien har varit att hitta ett sätt att värdera och vikta olika kriterier för att sedan göra en jämförelse av hur företaget och intressenterna uppskattar dessa kriterier. För att göra detta har intervjuer utförts med personer som är extra insatta i projektet med Sundsvall logistikpark och en enkät skickats ut till boende i Sundsvall. Informanterna och respondenterna har fått uppskatta värden och vikter på kriterierna utifrån ett indirekt alternativ där logistikparken inte byggs. Datan har sedan sammanställts genom att använda multiattributsnyttoteori som verktyg för att presentera jämförelsen. Resultatet av undersökningen tyder på att de skillnader som finns i värderingar och viktningar av kriterierna dels beror på en viss osäkerhet angående hur logistikparken skulle kunna påverka de olika kriterierna och hur ett värde kan uppskattas på dessa, men att den största orsaken troligen beror på vilket perspektiv personen ser logistikparken på. Om personen ser på logistikparken från ett industriellt perspektiv blir kriterier som har med industriell utveckling att göra viktigare och tar större plats i analysen. Om personen ser på logistikparken från ett individuellt och socialt perspektiv blir sådana kriterier viktigare och tar större plats i analysen

Nuclear energy is a source of carbon free power. With many countries striving to make deep carbon cuts in their energy sectors, nuclear energy could be a large part of the solution. One of the main obstacles standing in the way of the use of nuclear energy is the issue of used nuclear fuel disposal. According to the NEI, the U.S. creates about 2000 metric tons of used nuclear fuel per year and has generated around 76,000 metric tons of used nuclear fuel over the last 4 decades. While there are technical problems that need to be solved, it is primarily the public and political opposition to the disposal of used nuclear fuel that stands in the way of progress in this area. This work addresses this issue through Multi-Criteria Decision Analysis (MCDA). To make a decision among ten different fuel cycles, we have brought together five stakeholders: Nuclear Scientists and Engineers, Environmental Scientists, Economists, Political Scientists, and The General Public. Using Multi-Attribute Value Theory (MAVT), we have been able to develop decision models for each stakeholder as well as a model that combines them all and came to the conclusion that of the ten fuel cycles considered, the best decision is to continue to use On Site Dry Cask Storage. This decision is made with small sample sizes but the methodology could be applied at much larger scales and can potentially be used to choose a fuel cycle that encounters much less political and social opposition to its implementation.

Seismic rehabilitation of structural systems is an effective approach for reducing potential seismic losses such as social and economic losses. However, little or no effort has been made to develop a framework for making decisions on seismic rehabilitation of structural systems that systematically incorporates conflicting multiple criteria and uncertainties inherent in the seismic hazard and in the systems themselves. This study develops a decision support framework for seismic rehabilitation of structural systems incorporating uncertainties inherent in both the system and the seismic hazard, and demonstrates its application with detailed examples. The decision support framework developed utilizes the HAZUS method for a quick and extensive estimation of seismic losses associated with structural systems. The decision support framework allows consideration of multiple decision attributes associated with seismic losses, and multiple alternative seismic rehabilitation schemes represented by the objective performance level. Three multi-criteria decision models (MCDM) that are known to be effective for decision problems under uncertainty are employed and their applicability for decision analyses in seismic rehabilitation is investigated. These models are Equivalent Cost Analysis (ECA), Multi-Attribute Utility Theory (MAUT), and Joint Probability Decision Making (JPDM). Guidelines for selection of a MCDM that is appropriate for a given decision problem are provided to establish a flexible decision support system. The resulting decision support framework is applied to a test bed system that consists of six hospitals located in the Memphis, Tennessee, area to demonstrate its capabilities.

The purpose of this study was to develop a decision model for early-stage breast cancer patients. This model provides an opportunity for comparing two main treatment options, mastectomy and lumpectomy, with respect to quality of life by making use of Decision Theoretic Techniques. A Markov chain was constructed to project the clinical history of breast carcinoma following surgery. Then, health states used in the model were characterized by transition probabilities and utilities for quality of life. A Multi Attribute Utility Model was developed for outcome evaluation. This study was performed on the sample population of female university students, and utilities were elicited from these healthy volunteers. The results yielded by Multi Attribute Utility Model were validated by using Von Neumann-Morgenstern Standard Gamble technique. Finally, Monte Carlo Simulation was utilized in Treeage-Pro 2006 Suit software program in order to solve model and calculate expected utility value generated by each treatment option. The results showed that lumpectomy is more favorable for people who participated in this study. Sensitivity analysis on transition probabilities to local recurrence and salvaged states was performed and two threshold values were observed. Additionally, sensitivity analysis on utilities showed that the model was more sensitive to no evidence of disease state / however, was not sensitive to utilities of local recurrence and salvaged states.

Decision making is necessary to provide a synthesis scheme to design activities and identify the most preferred design alternative. There exist several methods that address modeling designer preferences in a graphical manner to aid the decision making process. For instance, the Conjoint Analysis has been proven effective for various multi-attribute design problems by utilizing a ranking- or rating-based approach along with the graphical representation of the designer preference. However, the ranking or rating of design alternatives can be inconsistent from different users and it is often difficult to get customer responses in a timely fashion. The high number of alternative comparisons required for complex engineering problems can be exhausting for the decision maker. In addition, many design objectives can have interdependencies that can increase complexity and uncertainty throughout the decision making process. The uncertainties apparent in the attainment of subjective data as well as with system models can reduce the reliability of decision analysis results. To address these issues, the use of a new technique, the Improved Conjoint Analysis, is proposed to enable the modeling of designer preferences and trade-offs under the consideration of uncertainty. Specifically, a simulation-based ranking scheme is implemented and incorporated into the traditional process of the Conjoint Analysis. The proposed ranking scheme can reduce user fatigue and provide a better schematic decision support process. In addition, the incorporation of uncertainty in the design process provides the capability of producing robust or reliable products. The efficacy and applicability of the proposed framework are demonstrated with the design of a cantilever beam, a power-generating shock absorber, and a mesostructured hydrogen storage tank.

In open office settings, auditory distractions coming from surrounding work environment are shown to be a considerable source of indirect costs to an organization, such as performance costs, behavioral costs, and healthcare costs, to name a few. These costs are substantial to affect the net productivity of an organization, where productivity is equal to revenue minus the costs. This research argues that the costs of auditory distractions should be estimated when evaluating the value of a workspace for an organization. However, since organizational decisions are generally guided by cost-benefit analysis and a precise dollar figure cannot be attached to the stated indirect costs because these are subjective in nature; therefore, these are generally ignored. Costs that are critical to sustainability and development of a business and the fact that cost-benefit approach is no longer appropriate for these decisions, a more robust decision-based approach to workspace selection is proposed. Decision-based approach is seen as an organized approach to select between workspace options under uncertainty and risk wherein the selected workspace is maximized in terms of some expected utility. Here utility is defined as the measurement of strength or intensity of a person's preferences. Decision-based approach include consideration of a multitude of environmental decision variables, objective or subjective, in a single equation and processing of the same in a limited amount of time with rationality and consistency. A multi-attribute workspace choice utility decision model is developed with the intent to facilitate systematic understanding and analysis of workspace alternatives for an organization. This research shows how the decision-making approach to workspace selection simplifies the problem by providing a structure that is easily comprehensible, and allows simultaneous processing of both, qualitative and quantitative conflicting objectives, through a single decision-making model. In doing so, this research firmly establishes the importance of workspace's adaptability to auditory distractions for office workers, particularly knowledge workers, who are constantly undertaking a range of complex tasks. The study holistically and systematically addresses the fundamental issue prevalent in state-of-the-art North American open plan office settings of substantiality of two extremely contrasting requirements, concentration and collaboration, in the same workspace and work environment at a given time.

This research project aims to develop a framework to manage uncertainty in cloud manufacturing for small and medium enterprises (SMEs). The framework includes a cloud manufacturing taxonomy; guidance to deal with uncertainty in cloud manufacturing, by providing a process to identify uncertainties; a detailed step-by-step approach to managing the uncertainties; a list of uncertainties; and response strategies to security and privacy uncertainties in cloud manufacturing. Additionally, an online assessment tool has been developed to implement the uncertainty management framework into a real life context. To fulfil the aim and objectives of the research, a comprehensive literature review was performed in order to understand the research aspects. Next, an uncertainty management technique was applied to identify, assess, and control uncertainties in cloud manufacturing. Two well-known approaches were used in the evaluation of the uncertainties in this research: Simple Multi-Attribute Rating Technique (SMART) to prioritise uncertainties; and a fuzzy rule-based system to quantify security and privacy uncertainties. Finally, the framework was embedded into an online assessment tool and validated through expert opinion and case studies. Results from this research are useful for both academia and industry in understanding aspects of cloud manufacturing. The main contribution is a framework that offers new insights for decisions makers on how to deal with uncertainty at adoption and implementation stages of cloud manufacturing. The research also introduced a novel cloud manufacturing taxonomy, a list of uncertainty factors, an assessment process to prioritise uncertainties and quantify security and privacy related uncertainties, and a knowledge base for providing recommendations and solutions.