Human -machine system design optimization for nondeterministic spacecraft anomaly determination/resolution

This research examines the dependence of knowledge on decision making with varying levels of uncertainty or non-deterministic situations. The work presented outlines a global approach that is not limited to a specific case study example, but can also be translated to other systems requiring operators, a degree of automation, time constraints, remote control, and high levels of personnel expertise. The specific objective of this study was to address the uncertainty inherent in satellite command and control and to assess and understand the role of human knowledge in the combined human-machine system unit. This research focused solely on the user component of complex human-machine systems. Machine technology level remained constant; no modifications or variations were made to the machine operating system. However, the user knowledge level was altered to examine the effect of this variation and resulting operator ability to troubleshoot and resolve system anomalies. The case study researched was the Defense Support Program (DSP) satellite constellation currently in use by Air Force Space Command for missile warning. Three different Types of tasks were defined, where the three Type categories (1, 2, and 3) represented the level of task difficulty (low, moderate and high). Each task consisted of resolving a unique satellite vehicle anomaly within pre-scripted scenarios. The role of human knowledge was examined and found to be significantly important. This result was more evident as the situation uncertainty or complexity of the task increased. This data may be useful to continue the optimization of both user and machine to create a human-machine system capable of adapting to the rapidly changing space environment and able to contribute more fully to tomorrow\u27s space control objectives