Using Design of Experiments to Improve Analyses, Simulations, and Cost
(Room 320C)
04 Dec 19
2:00 PM
-
2:30 PM
Tracks:
Full Schedule, Wednesday Schedule
The Department of Defense (DoD) is evaluating ways to accelerate acquisition and test and evaluation (T&E) programs in order to field more effective weapon and training systems sooner. Nations that were near-peers are fast becoming peers, with capabilities in some areas outpacing those of the United States. We can regain our advantages in several ways, including improving weapon system’s effectiveness and improving combat training. For weapon systems, we can accelerate the model-test-model process and provide early system prototypes for warfighter use in simulation and gaming environments. For combat training, we can improve validation of key training models. An analysis and modeling method called Design of Experiments (DOE) has shown great promise to quickly model early prototype weapon systems, enable modeling for tradespace and requirements analyses, and pinpoint designs that are precisely on target. DOE is now, by policy, used wherever possible in DOD operational testing to assist in the evaluation of weapon systems and to improve the precision of these weapons. Researchers in DoD and in the Department of Homeland Security (DHS) are using DOE to augment Cyber Security teams evaluating system vulnerabilities in order to fully cover the threat landscape with fewer personnel. Also, for key models in virtual and constructive training and analysis simulations, DOE is used to conduct validation of the models compared to live testing results. This first known paper on DOE at I/ITSEC will discuss the methods used to develop DOE models and simulation of those models. A current example of model validation and the value of using DOE will be discussed. Several examples of DOE modeling will be presented, including an example of a Navy radar that was tested originally without DOE and then tested years later by the same Test Director using DOE with 10% of the resources – very high cost avoidance.