Date of Award

3-24-2016

Document Type

Thesis

Degree Name

Master of Science in Engineering Management

Department

Department of Systems Engineering and Management

First Advisor

Vhance V. Valencia, PhD.

Abstract

The United States Air Force (USAF) owns a total of 30.9 million linear feet (LF) of storm sewer pipes valued at approximately $2.3B in its vast portfolio of built infrastructure. Current inventory records reveal that 78% of the inventory (24.1 million LF) is over 50 years old and will soon exceed its estimated service life. Additionally, the USAF depends on contract support while its business processes undervalue in-service evaluations from long-term funding plans. Ultimately, this disconnect negatively impacts infrastructure performance and overall strategic success, and the USAF risks making uninformed decisions in a fiscally constrained environment.

This research presents a proof of concept effort to automate storm sewer evaluations for the USAF using unmanned ground vehicles and computer vision technology for autonomous defect detection. The results conceptually show that a low-cost autonomous system can be developed using commercial off the shelf (COTS) hardware and open-source software to quantify the condition of underground storm sewer pipes with an efficiency of 36%. While the results show that the prototype developed for this research is not sufficient for operational use, it does demonstrate that the USAF can leverage COTS systems in future AM strategies to improve asset visibility at a significantly lower cost..

AFIT Designator

AFIT-ENV-MS-16-M-167

DTIC Accession Number

AD1054112

Download

Share

COinS