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5.3.1 Training Systems Engineers for System Acquisition
Author(s) -
Fisher Jack,
Humel Paul F.,
Fisher Gerard H.
Publication year - 2003
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.2003.tb02634.x
Subject(s) - aerospace , class (philosophy) , engineering management , process (computing) , computer science , training system , engineering , artificial intelligence , economic growth , economics , aerospace engineering , operating system
An experiential systems engineering training program developed for a customer of the California Institute of Technology Industrial Relations Center (IRC) was described in a previous paper (Fisher 2001). This program was modified under the sponsorship of the IRC and the Aerospace Corporation's training organization, the Aerospace Institute, to provide systems engineering training for Air Force personnel from the Space and Missile Systems Command. The course now includes eight full‐day class meetings over a period of 14 weeks with an instructor‐defined class‐long exercise requiring the design of a satellite system. Two courses were conducted in parallel, offset by one week. Each class of 24 students was divided into two teams. The exercise requires each team to develop a system with a number of pre‐defined steps that are described by the instructor tutorials. The exercise originates with an instructor‐prepared system requirements document and culminates with a student‐prepared Preliminary Design Review, life cycle cost estimate and risk management plan. The tutorial material prepares the students for each step in the system development process. Each 8‐hour class meeting involves a tutorial by the faculty as well as student team reports describing their progress with the exercise. Modifications to the earlier program include the addition of a class meeting utilizing the facilities of the Aerospace Concept Design Center (CDC). The CDC provides the capability to derive space system characteristics with computer‐based mathematical models. This allows the students to conduct tradeoff analyses to select a system design concept from the possible alternatives.