Manufacturer and industry recommendations vary considerably for maintenance and tests of emergency diesel-electric generator sets in emergency standby duty. There is little consistency among generator sets of similar technology, and manufacturers and their representatives often provide contradictory guidance. As a result, periodicity of emergency diesel-electric generator set maintenance and tests varies considerably in practice. Utilizing the framework proposed and tested by Fehr (2014), this research developed a parametric regression survival model of the reliability of modern diesel-electric generator sets in emergency standby duty as a function of maintenance, age, and cumulative run hours. A survival regression technique leveraging Cox’s (1972) methods was developed to combine multiple exponential and Weibull (1951) distributions into a single model to represent emergency diesel-electric generator sets and other complex machinery exhibiting multiple independent failure distributions. A generalized model and reliability tables derived from that model are presented along with maintenance and test recommendations to assist managers in determining the optimal maintenance program for a diesel-electric generator set.
","abstract_html":"<p>Manufacturer and industry recommendations vary considerably for maintenance and tests of emergency diesel-electric generator sets in emergency standby duty. There is little consistency among generator sets of similar technology, and manufacturers and their representatives often provide contradictory guidance. As a result, periodicity of emergency diesel-electric generator set maintenance and tests varies considerably in practice. Utilizing the framework proposed and tested by Fehr (2014), this research developed a parametric regression survival model of the reliability of modern diesel-electric generator sets in emergency standby duty as a function of maintenance, age, and cumulative run hours. A survival regression technique leveraging Cox’s (1972) methods was developed to combine multiple exponential and Weibull (1951) distributions into a single model to represent emergency diesel-electric generator sets and other complex machinery exhibiting multiple independent failure distributions. A generalized model and reliability tables derived from that model are presented along with maintenance and test recommendations to assist managers in determining the optimal maintenance program for a diesel-electric generator set.</p>","abstract_has_math":false,"creators":["Fehr, Stephen John"],"institution":null,"degree_name":"Doctor of Philosophy (PhD)","degree_level":"Dissertation","degree_discipline":"Engineering Management & Systems Engineering","degree_department":null,"school":null,"contributors":["T. Steven Cotter","Holly Handley","Jennifer Michaeli","Cesar Pinto","Resit Unal"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2017,"date_issued":"2017-10-01T07:00:00Z","date_published":"2017-10-01T07:00:00Z","updated_at":"2026-07-24T03:35:38Z","subjects":["Diesel","Failure","Generator","Maintenance","Regression","Reliability","Engineering","Operational Research","Statistics and Probability"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["9780355778267"],"render_values":[{"text":"9780355778267","href":null,"code":true}]}]},"links":{"outbound_url":"https://digitalcommons.odu.edu/emse_etds/24","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["T. Steven Cotter","Holly Handley","Jennifer Michaeli","Cesar Pinto","Resit Unal"]},{"key":"dc:creator","label":"Author","values":["Fehr, Stephen John"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.available","label":"Dc Date Available","values":["2018-03-14T07:00:00Z"]},{"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":["Diesel","Failure","Generator","Maintenance","Regression","Reliability","Engineering","Operational Research","Statistics and Probability"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["9780355778267","https://digitalcommons.odu.edu/emse_etds/24"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Manufacturer and industry recommendations vary considerably for maintenance and tests of emergency diesel-electric generator sets in emergency standby duty. There is little consistency among generator sets of similar technology, and manufacturers and their representatives often provide contradictory guidance. As a result, periodicity of emergency diesel-electric generator set maintenance and tests varies considerably in practice. Utilizing the framework proposed and tested by Fehr (2014), this research developed a parametric regression survival model of the reliability of modern diesel-electric generator sets in emergency standby duty as a function of maintenance, age, and cumulative run hours. A survival regression technique leveraging Cox’s (1972) methods was developed to combine multiple exponential and Weibull (1951) distributions into a single model to represent emergency diesel-electric generator sets and other complex machinery exhibiting multiple independent failure distributions. A generalized model and reliability tables derived from that model are presented along with maintenance and test recommendations to assist managers in determining the optimal maintenance program for a diesel-electric generator set.
"]},{"key":"dc:title","label":"Title","values":["Emergency Diesel-Electric Generator Set Maintenance and Test Periodicity"]}]}],"canonical_facts":{"dc:contributor":["T. Steven Cotter","Holly Handley","Jennifer Michaeli","Cesar Pinto","Resit Unal"],"dc:creator":["Fehr, Stephen John"],"dc:date.available":["2018-03-14T07:00:00Z"],"dc:description.abstract":["Manufacturer and industry recommendations vary considerably for maintenance and tests of emergency diesel-electric generator sets in emergency standby duty. There is little consistency among generator sets of similar technology, and manufacturers and their representatives often provide contradictory guidance. As a result, periodicity of emergency diesel-electric generator set maintenance and tests varies considerably in practice. Utilizing the framework proposed and tested by Fehr (2014), this research developed a parametric regression survival model of the reliability of modern diesel-electric generator sets in emergency standby duty as a function of maintenance, age, and cumulative run hours. A survival regression technique leveraging Cox’s (1972) methods was developed to combine multiple exponential and Weibull (1951) distributions into a single model to represent emergency diesel-electric generator sets and other complex machinery exhibiting multiple independent failure distributions. A generalized model and reliability tables derived from that model are presented along with maintenance and test recommendations to assist managers in determining the optimal maintenance program for a diesel-electric generator set.
"],"dc:identifier":["9780355778267","https://digitalcommons.odu.edu/emse_etds/24"],"dc:subject":["Diesel","Failure","Generator","Maintenance","Regression","Reliability","Engineering","Operational Research","Statistics and Probability"],"dc:title":["Emergency Diesel-Electric Generator Set Maintenance and Test Periodicity"],"thesis:degree_discipline":["Engineering Management & Systems Engineering"],"thesis:degree_level":["Dissertation"],"thesis:degree_name":["Doctor of Philosophy (PhD)"]},"updated_at":"2026-07-24T03:35:38Z"}