Collaborative Research: Visual Analytics for Creation of Value Functions in Complex Systems Design Under Uncertainty

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Value-driven design represents a new way of designing large scale complex engineered systems, such as those found in automobile, aerospace, and energy industries. In value-driven design, a value function is created that captures the preferences of the stakeholders. The value function comprises all the attributes that are important for the system being designed, such as weight, performance characteristics, and manufacturing concerns, amongst others. The value function is then used by all the participants in the design process to aid in their decision making, so that all participants use the same basis for their design decisions. This is extremely different from the present systems engineering process in which requirements are used to force design decisions among subsystems and components, leading to suboptimal designs. The creation of a value function, however, is very challenging for complex systems, particularly in light of the uncertainties that exist in the design variables, attributes, and ultimately, the value of the system itself. This award supports fundamental research to provide needed knowledge for the creation of value functions when designing complex systems under uncertainty. A key component of this research focuses on enabling the easy understanding of the complex relationships between design variables, attributes, and value functions using visualization tools. Results from this research will benefit the U.S. economy as well as the national defense, given the extensive reliance on large-scale systems by both military and commercial applications. This research is inherently multidisciplinary, not only providing a way to design in a multidisciplinary environment, but also through using multiple disciplines to address the fundamental issues related to value function creation for complex systems. The multidisciplinary nature of the research will lend itself to broadening participation of under-represented groups in this research.The value-driven design approach can overcome numerous limitations associated with present systems engineering processes. In the present systems engineering approach, requirements are developed in an attempt to capture the preferences of stakeholders. These requirements are then decomposed and passed to lower-level groups who then design subsystems and ultimately the components in the system. Problematically, these requirements over-restrict the design space, create difficulties in incorporating uncertainty, and provide little to no guidance in terms of what is actually desired by the stakeholders. While value-driven design has the potential to overcome these barriers, knowledge gaps exist. This research will address the knowledge gap related to formation of the value function under uncertainty. The research team will identify the impact of uncertainty in design variables and attributes on value functions. The team will develop a structured approach for forming a value function to ensure appropriate rank ordering of alternative solutions according to the preference of the stakeholder. The impact of risk preference (i.e., risk seeking, risk neutral, and risk averse) will be explored to determine relationships between risk preference and value-function formation. Visualization tools will be developed to aid in the understanding of relationships between attributes and the value function and to provide designers with decision aids for using value functions. The research team will also work with industrial partners to validate the methods and tools developed.