The Faraday Chromate intitiative analyzed Electro Impedance Spectroscopy (EIS) data to study the effectiveness and life of particular coatings on accelerated corrosion environments.
KBSI has developed technology that performs data mining of maintenance data, estimates balance life, and delivers the right information at the correct level and appropriate time to the maintenance decision maker. This technology will support maintenance depots by providing a sound basis for decisions and judgments in the corrosion arena. This will enable the Department of Defense to replace the current body of subjective, disjointed, and anecdotal information about weapon system corrosion with credible information that is based on metrics and data, leading to substantial decreases in the maintenance costs associated with detecting, repairing, and tracking corrosive areas. In collaboration with Faraday Technologies Inc., one of the leading electrochemistry experts, we have been very productive in working toward this goal.
A persistent maintenance challenge for the U.S. Air Force is monitoring the corrosion of painted surfaces of aircraft in their fleet. Corrosion mitigation of aircraft structures is typically accomplished through the use of corrosion protection systems such as coatings, sealants, and appliques. However, these protection systems break down over time, allowing the ingress of aggressive, corrosive species into occluded sites on aircraft structures. To avoid the cost of corrosion, this breakdown must be anticipated, and the protection system must be reinforced, repaired, or replaced before damage occurs. KBSI has experience in enhancing existing theoretical models for protection system breakdown and corrosion mechanisms with sophisticated data mining processes to validate, refine, or change those models. We have demonstrated the power of data mining to model aircraft components such as coated lap splice joints and its associated corrosion protection system. Experimental data generated at Faraday Technologies labs have been used to validate the data mining models developed at KBSI. KBSI has partnered with Faraday Technologies for the past 8 years, developing data mining and forecasting algorithms and visualization for the data they generate at their laboratory as well as for field data. Our collaboration has resulted in numerous SBIR awards, both Phase I and Phase II, for coating systems mainly for the Air Force but also for the Navy.
KBSI has also developed a reliability-based methodology for quantitatively predicting the service life of coatings exposed to their intended service environment given that the time to failure data of these coatings has high variability. This reliability-based methodology has a strong theoretical basis and has been applied successfully to other domains such as the aeronautical, electronics, medical, and nuclear industries. The Electro Impedance Spectroscopy figure shows experimental Electro Impedance Spectroscopy (EIS) data on 15 repeat panels all subjected to the same accelerated corrosion environment Lap Splice Joint Solution (LSJS) for Unscribed (U) panels for a given coating, provided by Faraday Technologies. Since the variability in measurements is high across these experiments, it is common practice to simultaneously expose multiple nominally identical panels to the same service environment.
Given this data, our next step was to estimate a criterion for failure based on a failure EIS value chosen by corrosion experts. Using Weibull distribution fits, KBSI has shown a reliability-based methodology to quantify the life of the coating given the variability in measurements.
This material is based upon work supported by the United States Air Force under Contract No. FA8650-07-C-5007. Any opinions, findings and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the United States Air Force.