A goal-oriented, inverse decision-based design method to find satisficing solutions for multiple football helmet components that all work together to achieve a set of conflicting goals is presented. The efficacy of the method is illustrated with the design of the top region of an American football helmet. The prototype helmet was first constructed and tested with a twin-wire drop tower to study the different components effect on the system response. The inverse design method is used to design the foam liner to dissipate the maximum impact energy, and then the composite shell is designed to reduce the weight. The Concept Exploration Framework and the compromise Decision Support Problem are used to find satisficing solutions to the system-level performance goals under uncertainty. The proposed goal-oriented, inverse decision-based design method is generic and will be used to design additional components, the complete helmet, and ultimately helmets for other sports.

From the decision-based design perspective, decision making is the critical element of the design process. All practical decision making occurs under some degree of uncertainty. Subjective expected utility theory is a well-established method for decision making under uncertainty; however, it assumes that the DM can express his or her beliefs as precise probability distributions. For many reasons, both practical and theoretical, it can be beneficial to relax this assumption of precision. One possible means for avoiding this assumption is the use of imprecise probabilities. Imprecise probabilities are more expressive of uncertainty than precise probabilities, but they are also more computationally cumbersome. Probability Bounds Analysis (PBA) is a compromise between the expressivity of imprecise probabilities and the computational ease of modeling beliefs with precise probabilities. In order for PBA to be implemented in engineering design, it is necessary to develop appropriate computational methods for propagating probability boxes (p-boxes) through black box engineering models. This thesis examines the range of applicability of current methods for p-box propagation and proposes three alternative methods. These methods are applied towards the solution of three successively complex numerical examples.

This study identifies how content specialists, instructors, and instructional designers made decisions about what content to teach in person and what to teach online for a second year Portuguese university course. Qualitative vignettes around three course design participants highlight emergent themes and course artifacts from their interviews that show how they made decisions about what learning opportunities to do online and what to leave in person. The blended language course involved Canvas learning management system with two additional main technology tools used in development: GoReact and H5P. The results are subdivided to reflect the views of the instructional designer, the content specialist, and the instructor.

Along with knowledge of the interactions unique to microscale devices, designers of microelectromechanical systems (MEMS) require information about complex fabrication and packaging techniques in order to fully complete a successful design. To that end, the successful design of MEMS requires the collaboration of experts and designers in a variety of engineering fields. From the decision-based design perspective, MEMS designers require a means to sort the input and information generated in a collaborative design process. While the potential for the use of languages and part libraries have been addressed in the literature as a means to solve this problem, a means to embody these principles has not been addressed. The use of modular, executable, decision-centric templates to rapidly compose, solve, archive, and reuse compromise Decision Support Problems (cDSP) for specific design problems has been proposed in the literature. The result of this work is a means of separating procedural design knowledge from declarative knowledge and parsing the cDSP into a set of computer-interpretable templates. A stated need in this work is the extension of the templates to accommodate the coupled solution of two cDSPs utilizing game theoretic principles. In this thesis, the theoretical structures of decision-centric templates are applied to the needs of MEMS designers. Computer interpretable, decision-centric templates, used to save, reuse, and aid in design decisions, are extended to permit MEMS designers and fabricators to collaborate via coupled cDSPs, using game theoretic principles of cooperative, noncooperative, and leader-follower games. This approach is illustrated through its application to the design and prototype fabrication of microscale gas chromatography separation channels. The outcome of this work is twofold: first, MEMS designers and fabricators will have a means to compose, collaboratively solve, archive, and reuse compromise Decision Support Problems in a computer interpretable manner, and second, decision templates will be extended through the use of game theoretic principles.

In this thesis, a decision model for examining prescribed risk management practices in engineering design is presented. The decision model explicitly considers the effects that design decisions under uncertainty have on the overall utility of the design process. These effects are important to consider because, according to Utility Theory, the designer should make decisions such that the expected utility is maximized. However, a significant portion of the literature neglects the costs of the design process, and focuses only on the quality of the design artifact, or at best includes its manufacture when determining the utility of an alternative. When designers neglect the costs of the design process, they cannot make tradeoffs between the costs of the design process and the quality of the artifact. As compared to previous work in this area, the decision model presented includes the effects of temporally degrading product utility on design decisions. The decision model is used to investigate the impacts of degrading product utilities in products that launch later as a result of the duration of design actions performed. In this thesis, the decision model is leveraged to investigate two key trends in engineering design resulting from increasing temporally-based costs. To support the conclusions in this thesis, quantitative evaluations of the decision model are investigated for two case studies. The conclusions are additionally supported through evaluations of the decision model in boundary plots that visualize prescribed behavior for designers over varying model parameters.

While design theories provide a foundation for representing and reasoning about design methods, existing design theories do not explicitly include uncertainty considerations or recognize tradeoffs between the design artifact and the design process. These limitations prevent the existing theories from adequately describing and explaining observed or proposed design methods. In this thesis, Rational Design Theory is introduced as a normative theoretical framework for evaluating prescriptive design methods. This new theory is based on a two-level perspective of design decisions in which the interactions between the artifact and the design process decisions are considered. Rational Design Theory consists of normative decision theory applied to design process decisions, and is complemented by a decision-theory-inspired conceptual model of design. The application of decision analysis to design process decisions provides a structured framework for the qualitative and quantitative evaluation of design methods. The qualitative evaluation capabilities are demonstrated in a review of the systematic design method of Pahl and Beitz. The quantitative evaluation capabilities are demonstrated in two example problems. In these two quantitative examples, Value of Information analysis is investigated as a strategy for deciding when to perform an analysis to gather additional information in support of a choice between two design concepts. Both quantitative examples demonstrate that Value of Information achieves very good results when compared to a more comprehensive decision analysis that allows for a sequence of analyses to be performed.

Model development decisions are an important feature of engineering design. The quality of simulation models often dictates the quality of design decisions, seeing as models guide decision makers (DM) in choosing design decisions. A quality model accurately represents the modeled system and is helpful for exploring what-if scenarios, optimizing design parameters, estimating design performance, and predicting the effect of design changes. However, obtaining a quality model comes at a cost in terms of model development--in experimentation, labor, model development time, and simulation time. Thus, DMs must make appropriate trade-offs when considering model development decisions. The primary challenge in model development is making decisions under significant uncertainty. This thesis addresses model development in the conceptual design phase where uncertainty levels are high. In the conceptual design phase, there are many information constraints which may include an incomplete requirements list, unclear design goals, and/or undefined resource constrains. During the embodiment design phase, the overall objective of the design is more clearly defined, and model development decisions can be made with respect to an overall objective function. For example, the objective may be to maximize profit, where the profit is a known function of the model output. In the conceptual design phase, this level of clarity is not always present, so the DM must make decisions under significant model uncertainty and objective uncertainty. In this thesis, conjoint analysis is employed to solicit the preferences of the decision maker for various model attributes, and the preferences are used to formulate a quasi-objective function during the conceptual design phase--where the overall design goals are vague. Epistemic uncertainty (i.e., imprecision) in model attributes is represented as intervals and propagated through the proposed model development framework. The model development framework is used to evaluate the best course of action (i.e., model development decision) for a real-world packaging design problem. The optimization of medical product packaging is assessed via mass spring damper models which predict contact forces experienced during shipping and handling. Novel testing techniques are employed to gather information from drop tests, and preliminary models are developed based on limited information. Imprecision in preliminary test results are quantified, and multiple model options are considered. Ultimately, this thesis presents a model development framework in which decision makers have systematic guidance for choosing optimal model development decisions.

Researchers have paid relatively little attention to the fact that most design activities are actually more like redesign. These activities are characterized by an attempt to leverage experience, knowledge, and the capital that a company has already invested into existing engineering systems. In this dissertation, it is proposed that an approach be developed to aid designers in making decisions in redesign problems when there exist systems to be leveraged and multiple new systems to be created. In addition, strategy is introduced to the problem through the consideration that new systems may not be offered all at once, as is often assumed in product family design research. In this dissertation, the aim of the designer is assumed to be a creation, through redesign, of a series of new systems with desirable and distinct performance levels. In addition, a plan is required to involve as little redesign effort throughout the life of the family of systems as possible The proposed approach is based upon the concepts of Constructal Theory and previous work to create methods for the design of mass customized families of products. The existing methods are abstracted and heavily modified through the infusion of the compromise Decision Support Problems at all stages of the decision-making process. In addition, two indices are developed to represent considerations unique to redesign as opposed to original design. These indices for redesign effort and commonality value are utilized in the overall objective formulation for the approach. Through a thorough validation process and a large number of redesign scenarios, it is shown that the overall approach proposed can lead the designer towards promising redesign plans involving leveraging of existing systems, but that the constructal-inspired approach in and of itself has certain limitations when applied to redesign.

The broad aim of this research is to contribute knowledge that enables improvements in how designers model decision alternatives at the systems level—i.e., how they model different system configurations and concepts. There are three principal complications: (1) design concepts and systems configurations are partially-defined solutions to a problem that correspond to a large set of possible design implementations, (2) each concept or configuration may operate on different physical principles, and (3) decisions typically involve tradeoffs between multiple competing objectives that can include "non-engineering" considerations such as production costs and profits. This research is an investigation of a data-driven approach to modeling partially-defined system alternatives that addresses these issues. The approach is based on compositional strategy in which designers model a system alternative using abstract models of its components. The component models are representations of the rational tradeoffs available to designers when implementing the components. Using these models, designers can predict key properties of the final implementation of each system alternative. A new construct, called a parameterized efficient set, is introduced as the decision-theoretic basis for generating the component-level tradeoff models. Appropriate efficiency criteria are defined for the cases of deterministic and uncertain data. It is shown that the model composition procedure is mathematically sound under reasonable assumptions for the case of deterministic data. This research also introduces an approach for describing the valid domain of a data-driven model based on the use of support-vector machines. Engineering examples include performing requirements allocation for a hydraulic log splitter and architecture selection for a hybrid vehicle.

Problem: Engineering design decisions require the integration of information from multiple and disparate sources. However, this information is often independently created, limited to a single perspective, and not formally represented, thus making it difficult to formulate decisions. Hence, the primary challenge is the development of computational representations that facilitate the exchange of information for decision support. Approach: First, the scope of this research is limited to representing design decisions as compromise decision support problems (cDSP). To address this challenge, the primary hypothesis is that a formal language will enable the semantics of cDSP to be captured, thus providing a digital interface through which design information can be exchanged. The primary hypothesis is answered through the development of a description logic (DL) based formal language. The primary research question is addressed in four sub-questions. The first two research questions relate to the development of a vocabulary for representing the semantics of the cDSP. The first hypothesis used to answer this question is that formal information modeling techniques can be used to explicitly capture the semantics and structure of the cDSP. The second research question is focused on the realization of a computer-processible representation. The hypothesis used to answer this question is that DL can be used for developing computational-based representations. The third research question is related to the organization and retrieval of decision information. The hypothesis used to answer this question is DL reasoning algorithms can be used to support organization and retrieval. Validation: The formal language developed in this dissertation is theoretically and empirically validated using the validation square approach. Validation of the hypotheses is achieved by systematically building confidence through example problems. Examples include the cDSP construct, analysis support models, the design of a cantilever beam, and design of a structural fin array heat sink. Contributions: The primary contribution from this dissertation is a formal language for capturing the semantics of cDSPs and analysis support models comprised of: (1) a systematic methodology for decision formulation, (2) a cDSP vocabulary, (3) a graphical information model, and (4) a DL-based representation. The components, collectively, provide a means for exchanging cDSP information.