Postprint version. Published in Reliability Engineering & System Safety, Volume 73, Issue 3, September 1, 2001, pages 281-291.
NOTE: At the time of publication, the author Allen Estes was affiliated with the United States Military Academy - West Point, NY. Currently, August 2008, he is Head and Professor of Architectural Engineering at California Polytechnic State University - San Luis Obispo.
The definitive version is available at https://doi.org/10.1016/S0951-8320(01)00044-8.
Civil engineering structures are designed to serve the public and often must perform safely for decades. No matter how well they are designed, all civil engineering structures will deteriorate over time and lifetime maintenance expenses represent a substantial portion of the total lifetime cost of most structures. It is difficult to make a reliable prediction of this cost when the future is unknown and structural deterioration and behavior are assumed from a mathematical model or previous experience. An optimal maintenance program is the key to making appropriate decisions at the right time to minimize cost and maintain an appropriate level of safety. This study proposes a probabilistic framework for optimizing the timing and the type of maintenance over the expected useful life of a deteriorating structure. A decision tree analysis is used to develop an optimum lifetime maintenance plan which is updated as inspections occur and more data is available. An estimate which predicts cost and behavior over many years must be refined and reoptimized as new information becomes available. This methodology is illustrated using a half-cell potential test to evaluate a deteriorating concrete bridge deck. The study includes the expected life of the structure, the expected damage level of the structure, costs of inspection and specific repairs, interest rates, the capability of the test equipment to detect a flaw, and the management approach of the owner towards making repairs.