Managing instrumentation projects, large or small, involves a number of common challenges-defining what
is needed, desiging a system to provide it, producing it in an economical way, and putting it into service
expeditiously. Doing these things in a university environoment provides unique challenges and opportunities
not obtaining in the environment of large projects at NASA or national labs. I address this topic from the
viewpoint of knowledge of two such projects, the development of OAO-2 at the University of Wisconsin and the
relocation of Fairborn Observatory to the Patagonia Mountains in Arizona, as well as my own developemnt of
the Tennessee State 2-m Automatic Spectroscopic Telescope. For the university environment, I argue for a more
traditional management style that relies on more informal techniques than those used in large-scale projects
conducted by big bureaucratic institutions. This style identifies what tasks are really necessary and eliminates
as much wasteful overhead as possible. I discuss many of the formalities used in project management, such
as formal reviews (PDR, CDR, etc.) and Gantt charts, and propose other ways of acheving the same results
more effectively. The university environment acutely requires getting the right people to do the project, both
in terms of their individual personalities, motivation, and technical skills but also in terms of their ability to
get on with one another. Two critical challenges confronting those doing such projects in universities are 1)
keeping the contractors on task (the major challenge to anyone doing project management) and 2) dealing with
the purchasing systems in such institutions.
Tennessee State University is operating a 2-m automatic telescope for high-dispersion spectroscopy. The alt-azimuth telescope is fiber-coupled to a conventional echelle spectrograph with two resolutions (R=30,000 and 70,000). We control this instrument with four computers running linux and communicating over ethernet through the UDP protocol. A computer physically located on the telescope handles the acquisition and tracking of stars. We avoid the need for real-time programming in this application by periodically latching the positions of the axes in a commercial motion controller and the time in a GPS receiver. A second (spectrograph) computer sets up the spectrograph and runs its CCD, a third (roof) computer controls the roll-off roof and front flap of the telescope enclosure, and the fourth (executive) computer makes decisions about which stars to observe and when to close the observatory for bad weather. The only human intervention in the telescope's operation involves changing the observing program, copying data back to TSU, and running quality-control checks on the data. It has been running reliably in this completely automatic, unattended mode for more than a year with all day-to-day adminsitration carried out over the Internet. To support
automatic operation, we have written a number of useful tools to predict and analyze what the telescope does. These include a simulator that predicts roughly how the telescope will operate on a given night, a quality-control program to parse logfiles from the telescope and identify problems, and a rescheduling program that calculates new priorities to keep the frequency of observation for the various stars roughly as desired. We have also set up a database to keep track of the tens of thousands of spectra we expect to get each year.
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