Life-cycle cost modeling can be used to compare expected performance of corrosion protection systems over the entire life of a steel structure. Life-cycle models consider not only initial application costs, but also future maintenance costs. Critical, however, to the value and validity of the model are the assumptions used for the longevity of various corrosion protection systems and the timing for maintenance interventions. Coating durability guidelines for corrosion protection coatings estimates the time to first maintenance and also provides a schedule for subsequent maintenance actions. Fortunately, many steel structures exist with various corrosion protection coating systems so that cost models can be verified against real-world performance. While guidelines for liquid applied organic coatings compare well with observed real-world performance, estimates for the durability of duplex zinc coatings significantly underestimate the life of the coating, thereby overestimating the life-cycle cost. Real-world performance of organic coatings and duplex zinc coatings will be compared to illustrate the validity and limitations of coating durability guidelines used for life cycle cost modeling.
The life of corrosion protection coating systems very often will not meet the design life of the steel structures they are supposed to protect. Decisions about corrosion protection coating selection are usually focusing on the costs for the initial application, ignoring the certain future maintenance costs. However, repeated maintenance operations, and resulting downtime, can add significantly to the total cost of ownership.
Life cycle cost (LCC) calculations provide a method for evaluating corrosion protection systems based on a proposed maintenance schedule over the expected life of a structure.1 Comparing the calculated LCC of each system determines which system provides the lowest total cost of ownership. However, the assumptions used for the longevity of various corrosion protection systems and the timing for maintenance interventions are critical for the value and validity of the model.
