Advisor(s) - Committee Chair
Department of Computer Science
Master of Science
Asset management is fundamental to the success of any large enterprise. Organizations must make optimum use of their assets and monitor them in order to ensure that they are operating correctly, and will continue to operate effectively in the future. A wide variety of IT systems have been developed for asset management, and in particular, for Operations and Maintenance (O&M). However, in order to provide an effective asset management solution, each of the assets must be able to readily interchange information with other systems – a significant characteristic lacking in many current systems. This thesis describes the implementation of a condition-based asset maintenance system based on OSA-CBM Standard for aerospace applications. The technologies that underpin this framework encompasses research in such areas as, information extraction, data mining, decision support, information integration, and distributed software systems engineering, besides the management of domain knowledge in aeronautics.
The system permits just-in-time vehicle operational data to be automatically collected, and processed either on-board or off-board in order to determine the health or state of any equipment. The resulting and supporting data sets are sent to an integrated ground system for further processing and/or as maintenance system input. The system also improves the prediction and prevention of serious problems in assets (in this case, vehicles) by reporting on their health details using the collected data. Further, the system proactively offers suggestions on replacement of components, when necessary. The technologies that encompass the system can be applied to not only aerospace applications, but also many other condition-based maintenance systems including such areas as, oil and gas industries and rotating machinery management in shipping industry.
Computer Sciences | Physical Sciences and Mathematics
Ho, Hoa, "Implementation of the Foundational Three Layers of OSA-CBM" (2008). Masters Theses & Specialist Projects. Paper 3424.