Date of Award

2013-01-01

Degree Name

Master of Science

Department

Industrial Engineering

Advisor(s)

Tzu-Liang (Bill) Tseng

Abstract

Foreign Object Debris/Damage (FOD) is a costly and high-risk problem that aeronautics industries such as Boeing, Lockheed Martin, among others are facing at their production lines every day. They spend an average of $350 thousand dollars per year fixing FOD problems. FOD can put pilots, passengers and other crews' lives into high-risk. FOD refers to any type of foreign object, particle, debris or agent in the manufacturing environment, which could contaminate/damage the product or otherwise undermine quality control standards. FOD can be in the form of any of the following categories: panstock, manufacturing debris, tools/shop aids, consumables and trash. Although aeronautics industries have put many prevention plans in place such as housekeeping and "clean as you go" philosophies, trainings, use of RFID for tooling control, etc. none of them has been able to completely eradicate the problem. This research presents a logistic regression statistical model approach to predict probability of FOD type under given specific circumstances such as workstation, month and aircraft/jet being built. FOD Quality Assurance Reports of the last three years were provided by an aeronautical industry for this study. By predicting type of FOD, custom reduction/elimination plans can be put in place and by such means being able to diminish the problem. Different aircrafts were analyzed and so different models developed through same methodology. Results of the study presented are predictions of FOD type for each aircraft and workstation throughout the year, which were obtained by applying proposed logistic regression models. This research would help aeronautic industries to address the FOD problem correctly, to be able to identify root causes and establish actual reduction/elimination plans.

Language

en

Provenance

Received from ProQuest

File Size

122 pages

File Format

application/pdf

Rights Holder

Natalia V. Espino

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