Defining the "trade space" for CAIV optimization using a cost model derived from linear regression of NASA project data

Joseph F Krupa, Paul J. Componation

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In 1995, Dr. Paul Kaminski, then Defense Undersecretary for Defense for Acquisition and Technology, established the principles of CAIV-"Cost as an Independent Variable"-to take advantage of aerospace's experience using Target Cost to battle the escalating cost of defense systems in a time of declining procurement and development dollars. One of the key tenets of CAIV is to limit Key Performance Parameters (KPP) to the critical few, to establish thresholds and desired levels of performance, and to trade off performance, cost and schedule. This trade arena is called the "Trade Space". Although a number of authors have proposed methodologies for performance, cost and schedule trades, a clear process has not emerged. One difficulty that emerged from study was how to use existing cost estimating systems to perform "Trade Space" optimizations. This paper presents the use of a cost model derived from log linear regression analysis of data from eighty-six NASA projects, the Analytic Hierarchy process, and non-linear optimization to show how CAIV "Trade Space" can be developed from cost data.

Original languageEnglish (US)
Title of host publication16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006
Pages17-32
Number of pages16
StatePublished - Dec 1 2006
Event16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006 - Orlando, FL, United States
Duration: Jul 10 2006Jul 13 2006

Publication series

Name16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006
Volume1

Other

Other16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006
CountryUnited States
CityOrlando, FL
Period7/10/067/13/06

Fingerprint

Linear regression
NASA
Costs
Cost estimating
Analytic hierarchy process
Regression analysis

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Krupa, J. F., & Componation, P. J. (2006). Defining the "trade space" for CAIV optimization using a cost model derived from linear regression of NASA project data. In 16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006 (pp. 17-32). (16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006; Vol. 1).

Defining the "trade space" for CAIV optimization using a cost model derived from linear regression of NASA project data. / Krupa, Joseph F; Componation, Paul J.

16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006. 2006. p. 17-32 (16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006; Vol. 1).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Krupa, JF & Componation, PJ 2006, Defining the "trade space" for CAIV optimization using a cost model derived from linear regression of NASA project data. in 16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006. 16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006, vol. 1, pp. 17-32, 16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006, Orlando, FL, United States, 7/10/06.
Krupa JF, Componation PJ. Defining the "trade space" for CAIV optimization using a cost model derived from linear regression of NASA project data. In 16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006. 2006. p. 17-32. (16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006).
Krupa, Joseph F ; Componation, Paul J. / Defining the "trade space" for CAIV optimization using a cost model derived from linear regression of NASA project data. 16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006. 2006. pp. 17-32 (16th Annual International Symposium of the International Council on Systems Engineering, INCOSE 2006).
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