Test and evaluation (T&E), a critical element of systems engineering, is a problem solving and knowledge accumulation process. By introducing methodologies capable of reducing and managing uncertainty, T&E’s role increases in value and progresses to becoming a critical component of the decision-making process. This webinar introduces digital engineering principles and Uncertainty Quantification (UQ) methodologies and their disruptive transformation of T&E from the traditional role of providing data or validating models towards the creation of knowledge for better decision making at critical milestones.
Typically, T&E’s value comes from the early identification of problems, cost avoidance, or reduction in rework, but these metrics cannot be defined or measured until after testing. Changing T&E’s value metric to the quantification and mitigation of technical uncertainty eliminates this issue. By using statistical techniques for UQ, technical uncertainty can be estimated in the development process and evaluated after testing. Technical uncertainty can be easily related to risk, and along with other parameters of interest such as cost and schedule, they can be related to stakeholder value and better support critical decisions.
This webinar will present a digital, model-based systems engineering approach to T&E enabled by uncertainty quantification. Key concepts include:
