Learning Curve Analysis in Department of Defense Acquisition Programs
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Authors
Elshaw, John
Badiru, Adedeji
Harris, Sharif
Subjects
Advisors
Date of Issue
2017-11
Date
2017-11
Publisher
Monterey, California. Naval Postgraduate School
Language
Abstract
Learning curves are used to describe and estimate the cost performance of a serial production process. There are numerous models and methods; however, it is not precisely known which model and method is preferred for a particular situation. The primary objective of this research is to compare performance of the more common learning curve models. The research goals are to improve understanding of the systemic cost drivers of a production process, to clarify the relationship of these drivers to cost, and to present modeling methods. We use qualitative analysis combined with statistical regression modeling to assess fit. The research identified that preference for one function or another depended upon the shape of the data and how well a model formulation could be made to fit that shape. This was reliant upon the modelﾒs basic shape and the available parameters to alter its appearance. The typical learning curve model assumes that cost is a function of time but commonly omits factors such as production process resources changes (capital and labor) and the impact it has on cost. A learning curve model that includes the effects of resource changes would likely provide higher estimative utility given that the model establishes a systemic relationship to the underlying production process.
Type
Report
Description
Series/Report No
Department
Organization
Identifiers
NPS Report Number
AFIT-CE-18-008
Sponsors
Naval Postgraduate School Acquisition Research Program
Funder
Format
Citation
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.