Date of Award

Fall 2014

Document Type


Degree Name

Master of Science (MS)


Engineering Management & Systems Engineering


Engineering Management

Committee Director

T. Steven Cotter

Committee Member

Cesar A. Pinto

Committee Member

Pilar Pazos-Lago

Committee Member

Resit Unal

Call Number for Print

Special Collections LD4331.E555 F44 2014


Manufacturer and industry recommendations vary considerably for maintenance and tests of emergency diesel-electric generator sets supporting critical operations power systems facilities. There is little consistency among 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. This work proposes and tests a research and analysis framework to develop parametric regression survival models of modern diesel-electric generator sets in emergency standby duty as a function of maintenance periodicity, test periodicity, and other predictors. Within this framework, predictors are developed from common maintenance and test actions, data is acquired and compiled in a standardized method, and this data is analyzed using non-parametric and parametric statistical stepwise regression techniques. The framework presented herein was tested on a small scale data set data drawn from emergency diesel-electric generator set logbooks at critical operations power systems facilities and is demonstrated as a feasible method of quantitatively determining the effectiveness of different periodicities of common routine maintenance and test actions on real-world data that contains a large fraction of left truncation and right censoring. A full scale study utilizing this framework is proposed to determine optimal maintenance and test periodicity.


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