The design and development cycle for complex systems is full of uncertainty, commonly recognized as the main source of risk in organizations engaged in design and development. One of the challenges for such organizations is assessing how much risk (cost, schedule, scope) they can take on and still remain competitive. The risk associated with the design of complex systems is fundamentally tied to uncertainty, which may lead to suboptimal performance or failure if unmanaged. By understanding the sources of uncertainty in all stages of complex system design, decision-makers can make more informed choices and identify “hotspots” for reducing risks due to uncertainty by reallocating resources, adding safeguards, etc. There are two major categories of uncertainty (certain uncertainty) classification in the design of complex systems: Knowledge/epistemic uncertainty and Variability/Aleatory uncertainty. The intersection of these two sets is ambiguity uncertainty and the outside is what we don’t know we don’t know (uncertain uncertainty). By setting detailed definitions, we can reduce the ambiguity uncertainty. Furthermore, we can subdivide knowledge uncertainty into model, ambiguity and behavioral uncertainty, and subdivide variability uncertainty into natural randomness, ambiguity and behavioral uncertainty. We can go further and find subcategories for model and behavioral uncertainty. Using this classification for uncertainty, this paper proposes the “Capture, Assessment and Communication Tool for Uncertainty Simulation” (CACTUS) for assessing, capturing, and communicating risks due to uncertainty during complex system design. CACTUS has columns to identify sources, location, severity and importance of uncertainty in stages of design. By applying CACTUS, decision-makers will be able to find answers to the following questions for each type of uncertainty included in the design process: 1 - Where is uncertainty from? (i.e., Sources); 2 - In which stages of design does uncertainty appear? (i.e., Location); 3 - What is its severity?; and, 4 - What is its importance? The hypothesis of this research is that, by using CACTUS, design organizations can capture, assess, and efficiently and effectively communicate uncertainty through their design processes, and as a result, improve their capacity for delivering complex systems that meet cost, schedule, and performance objectives. The fundamental steps of the methodology are illustrated by using a concurrent design case study from NASA’s Project Design Center.

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