Date of Award

3-2023

Document Type

Thesis

Degree Name

Master of Science in Cost Analysis

Department

Department of Systems Engineering and Management

First Advisor

Jonathan D. Ritschel, PhD

Abstract

Across the Department of Defense (DoD), a wide variety of analytical tools are employed by cost analysts to estimate weapon system costs. One of the techniques widely employed by practitioners is the learning curve (LC). Although learning curves have been widely studied, using rate-adjustments or production rate effects (PRE), their usage have only intermittently been evaluated in place of using the traditional learning curve. Previous studies analyzing production rate found mixed results. This research aims to examine aircraft production data to determine if production rate model is preferrable in United States Air Force programs. Additionally, this PRE research seeks to determine if there exists a minimum production size necessary for using rate. Once a minimum size, or conditions, is determined, this thesis then maps that information to show where PRE occurs within the acquisition process timeline. The results of the study find the PRE models to have less error than the traditional learning curves. Additionally, the minimum rate size for production was found based on specific model constraints. Finally, tracking for when PRE occurs relative to Initial Operational Capability (IOC) shows a statistical significance of occurrence after IOC.

AFIT Designator

AFIT-ENV-MS-23-M-159

Comments

A 12-month embargo was observed for this thesis posting.

Approved for Public Release, Distribution A, PA Case Number on file.

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