HCIL-2001-07, CS-TR-4243, UMIACS-TR-2001-29
This paper describes a learning historian to improve user-directed experimentation with discrete event simulation models of manufacturing systems. In user-directed experimentation, an analyst conducts simulation runs to estimate system performance. Then the analyst modifies the simulation model to evaluate other possibilities. An important characteristic is the ad hoc nature of the experimentation, as the analyst forms and runs new trials based on the results from previous trials. Through user-directed experimentation designers compare alternatives and students learn the relationships between input parameters and performance measures. Recording and reviewing previous trials while using simulation models enhances their benefits, transforming trial-and-error into learning. The learning historian combines a graphical user interface, a discrete event simulation model, and dynamic data visualization. Usability studies indicate that the learning historian is a usable and useful tool because it allows users to concentrate more on understanding system behavior than on operating simulation software.