Cost Estimating Relationships for Avionics Recurring Production Box Costs

Author

Carla J. Cisneros

Date of Award

3-2024

Document Type

Thesis

Degree Name

Master of Science in Cost Analysis

Department

Department of Systems Engineering and Management

First Advisor

Edward D. White III, PhD

Abstract

This research investigates a dataset of 286 Department of Defense (DoD) avionics boxes, employing regression methods to establish seven cost estimation relationships (CERs) for predicting avionics recurring production box costs. Not confined to T100 costs, three baseline models use Ordinary Least Squares (OLS) T100 cost, explaining 83%, 86%, and 83% of dataset variation. Additionally, four robust models depict mean and median, T100 OLS, and T100 non-linear learning curves, explaining 67%, 65%, 97%, and 87% of the variation. These models strike a balance between simple baseline and overly complex computational models. Identified cost drivers include weight, year of first flight, volume, and the subfunctions radio and voice. This study represents the most extensive regression analysis of avionics box costs for recurrent production expenses, serving as a valuable reference for cost analysts in validating early estimations.

AFIT Designator

AFIT-ENV-MS-24-M-113

Comments

A 12-month embargo was observed for posting this work on AFIT Scholar.

Distribution Statement A, Approved for Public Release. PA case number on file.

Recommended Citation

Cisneros, Carla J., "Cost Estimating Relationships for Avionics Recurring Production Box Costs" (2024). Theses and Dissertations. 7741.
https://scholar.afit.edu/etd/7741