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3 Parametric Cost Modeling of Space Missions Using the Develop New Projects (DNP) Implementation Process
Author(s) -
Rosenberg Leigh,
Hihn Jairus,
Roust Kevin,
Warfield Keith
Publication year - 1999
Publication title -
incose international symposium
Language(s) - English
Resource type - Journals
ISSN - 2334-5837
DOI - 10.1002/j.2334-5837.1999.tb00169.x
Subject(s) - process (computing) , cost estimate , key (lock) , computer science , parametric statistics , space (punctuation) , systems engineering , operations research , data science , industrial engineering , engineering , computer security , statistics , mathematics , operating system
This paper presents an overview of a parametric cost model that has been built at JPL to estimate costs of future, deep space, robotic science missions. Due to the recent dramatic changes in JPL business practices brought about by an internal re‐engineering effort known as develop new products (DNP), high‐level historic cost data is no longer considered analogous to future missions. Therefore, the historic data is of little value in forecasting costs for projects developed using the DNP process. This has lead to the development of an approach for obtaining expert opinion and also for combining actual data with expert opinion to provide a cost database for future missions. In addition, the DNP cost model has a maximum of objective cost drivers which reduces the likelihood of model input error. Version 2 is now under development which expands the model capabilities, links it more tightly with key design technical parameters, and is grounded in more rigorous statistical techniques. The challenges faced in building this model will be discussed, as well as it's background, development approach, status, validation, and future plans.