The purpose of this research is to develop a decision support system that can assist in detecting partial failures in dynamic systems such as Fire Control System Tracking Radar (TR) onboard Naval Ships. Partial failures do not necessarily shut down the system immediately but cause degradation of operational performance. Previous work has shown that experts in the field of failure detection, test point insertion and Built-In-Test Equipment (BITE) can provide useful input in detecting partial failures. Partial failures affect operational system performance and support costs, which can be significant. Often, however, partial failure detection consists of the estimations and opinions of the experts. This has not been addressed adequately in the literature. It is postulated that the approach developed in this research could be applied to maintain and monitor partial failure. The development of such a testing aid is the thrust of this research effort. Markov chains, k-out-of-n: G: system and critical path tracing techniques, among others are employed. Appropriate survey questionnaires are used for validation of the resulting test model. Application of previous test point insertion techniques are applied as a part of system comparison and assessment.
","abstract_html":"<p>The purpose of this research is to develop a decision support system that can assist in detecting partial failures in dynamic systems such as Fire Control System Tracking Radar (TR) onboard Naval Ships. Partial failures do not necessarily shut down the system immediately but cause degradation of operational performance. Previous work has shown that experts in the field of failure detection, test point insertion and Built-In-Test Equipment (BITE) can provide useful input in detecting partial failures. Partial failures affect operational system performance and support costs, which can be significant. Often, however, partial failure detection consists of the estimations and opinions of the experts. This has not been addressed adequately in the literature. It is postulated that the approach developed in this research could be applied to maintain and monitor partial failure. The development of such a testing aid is the thrust of this research effort. Markov chains, k-out-of-n: G: system and critical path tracing techniques, among others are employed. Appropriate survey questionnaires are used for validation of the resulting test model. Application of previous test point insertion techniques are applied as a part of system comparison and assessment.</p>","abstract_has_math":false,"creators":["Al-jowder, Anwar A."],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Engineering Management & Systems Engineering","degree_department":null,"school":null,"contributors":["Resit Unal","Andres Sousa-Poza","Charles Keating","Bruce Conway"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2003,"date_issued":"2003-01-01T08:00:00Z","date_published":"2003-01-01T08:00:00Z","updated_at":"2026-07-24T03:34:18Z","subjects":["Failure","Partial failures","Tracking radar","Dynamics and Dynamical Systems","Electrical and Computer Engineering","Environmental Engineering","Systems Engineering"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://digitalcommons.odu.edu/emse_etds/39","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Resit Unal","Andres Sousa-Poza","Charles Keating","Bruce Conway"]},{"key":"dc:creator","label":"Author","values":["Al-jowder, Anwar A."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2019-03-13T07:00:00Z"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Engineering Management & Systems Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Doctor of Philosophy (PhD)"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Failure","Partial failures","Tracking radar","Dynamics and Dynamical Systems","Electrical and Computer Engineering","Environmental Engineering","Systems Engineering"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://digitalcommons.odu.edu/emse_etds/39"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The purpose of this research is to develop a decision support system that can assist in detecting partial failures in dynamic systems such as Fire Control System Tracking Radar (TR) onboard Naval Ships. Partial failures do not necessarily shut down the system immediately but cause degradation of operational performance. Previous work has shown that experts in the field of failure detection, test point insertion and Built-In-Test Equipment (BITE) can provide useful input in detecting partial failures. Partial failures affect operational system performance and support costs, which can be significant. Often, however, partial failure detection consists of the estimations and opinions of the experts. This has not been addressed adequately in the literature. It is postulated that the approach developed in this research could be applied to maintain and monitor partial failure. The development of such a testing aid is the thrust of this research effort. Markov chains, k-out-of-n: G: system and critical path tracing techniques, among others are employed. Appropriate survey questionnaires are used for validation of the resulting test model. Application of previous test point insertion techniques are applied as a part of system comparison and assessment.
"]},{"key":"dc:title","label":"Title","values":["Developing a Methodology to Detect Partial Failures for Dynamic Systems"]}]}],"canonical_facts":{"dc:contributor":["Resit Unal","Andres Sousa-Poza","Charles Keating","Bruce Conway"],"dc:creator":["Al-jowder, Anwar A."],"dc:date.available":["2019-03-13T07:00:00Z"],"dc:description.abstract":["The purpose of this research is to develop a decision support system that can assist in detecting partial failures in dynamic systems such as Fire Control System Tracking Radar (TR) onboard Naval Ships. Partial failures do not necessarily shut down the system immediately but cause degradation of operational performance. Previous work has shown that experts in the field of failure detection, test point insertion and Built-In-Test Equipment (BITE) can provide useful input in detecting partial failures. Partial failures affect operational system performance and support costs, which can be significant. Often, however, partial failure detection consists of the estimations and opinions of the experts. This has not been addressed adequately in the literature. It is postulated that the approach developed in this research could be applied to maintain and monitor partial failure. The development of such a testing aid is the thrust of this research effort. Markov chains, k-out-of-n: G: system and critical path tracing techniques, among others are employed. Appropriate survey questionnaires are used for validation of the resulting test model. Application of previous test point insertion techniques are applied as a part of system comparison and assessment.
"],"dc:identifier":["https://digitalcommons.odu.edu/emse_etds/39"],"dc:subject":["Failure","Partial failures","Tracking radar","Dynamics and Dynamical Systems","Electrical and Computer Engineering","Environmental Engineering","Systems Engineering"],"dc:title":["Developing a Methodology to Detect Partial Failures for Dynamic Systems"],"thesis:degree_discipline":["Engineering Management & Systems Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T03:34:18Z"}