RE-ENGINEERING THE EUVE PAYLOAD OPERATIONS INFORMATION FLOW PROCESS TO SUPPORT AUTONOMOUS MONITORING OF PAYLOAD TELEMETRY

Abstract

The UC Berkeley Extreme Ultraviolet Explorer (EUVE) Science Operations Center (ESOC) is developing and implementing knowledge-based software to automate the monitoring of satellite payload telemetry. Formerly, EUVE science payload data were received, archived, interpreted, and responded to during round-the-clock monitoring by human operators. Now, knowledge-based software will support, augment, and supplement human intervention. In response to and as a result of this re-engineering project, the creation, storage, revision, and communication of information (the information flow process) within the ESOC has been redesigned. We review the information flow process within the ESOC before, during, and after the re-engineering of telemetry monitoring. We identify six fundamental challenges we face in modifying the information flow process. (These modifications are necessary because of the shift from continuous human monitoring to a knowledge-based autonomous monitoring system with intermittent human response.) We describe the innovations we have implemented in the ESOC information systems, including innovations in each part of the information flow process for short-term or dynamic information (which changes or updates within a week) as well as for long-term or static information (which is valid for more than a week). We discuss our phased approach to these innovations, in which modifications were made in small increments and the lessons learned at each step were incorporated into subsequent modifications. We analyze some mistakes and present lessons learned from our experience.