CORROSION MANAGEMENT FINANCIAL TOOLS

Corrosion management includes all activities, through the lifetime of the structure, that are performed to prevent corrosion, repair its damage, and replace the structure, such as maintenance, inspection, repair, and removal. These activities are performed at different times during the lifetime of the structure. Some maintenance is a regular activity, characterized by annual cost. Inspections are scheduled as periodic activities, and repair is done as warranted. Rehabilitation may be done once or twice during the lifetime of the structure, and the cost is usually high. Applying different corrosion management methods may positively affect the lifetime of a structure of a particular design without increasing the cost.

In order to meet the corrosion management objectives, tools or methodologies are available to calculate the cost of corrosion over part of an equipment’s or asset’s lifetime or over the entire life cycle. These methods, which range from cost-adding to life cycle costing (LCC) and constraint optimization are summarized below and discussed in detail in Appendix E.

Return on investment (ROI) is a primary performance measure used to evaluate the efficiency of an investment (or project) or to compare the efficiency of a number of different investments. ROI measures the amount of return (profit or cost savings) on an investment relative to the investment’s cost. An ROI calculation is used along with other approaches to develop a business case for a given proposal. ROI is calculated by simply dividing the return or cost savings (projected or achieved) on an investment divided by the cost of the investment. The complex part of ROI is determining the cost savings and investment costs. To compare investment proposals, ROI must either be annualized or the time over which the ROI is achieved is stated.

For example, it has been suggested (Economic Impact) that as much as 30% of the corrosion costs can be saved by implementing state-of-the-art corrosion control technology. If the cost of this implementation is 10% of the savings, the following ROI is realized over the applicable time frame. If your annual corrosion costs are US$10,000, and state-of-the-art corrosion control is implemented, projected annual savings would be US$3,000 at an annual cost of US$300.

Some of the savings may be difficult to monetize, such as decreased risk of environmental accidents, decreased risk of personal injury, lower risk of failure (possibly related to environmental risk and safety), and a cost associated with poor public relations. The details of how to handle these can be different for different industries and applications. One way to deal with these is a risk-based approach and to analyze the risk benefit of a specific project (how much will the performance of a project decrease the risk picture for the organization).

Cost-Adding Methodology

This method, developed by the U.S. Department of Defense (DoD), calculates the cost of corrosion of an asset or a project by looking from the top down. Programs, projects, and assets are analyzed to determine cost components that are related to corrosion. The top-down corrosion cost assessment removed all cost components that have no corrosion. However, usually significant gaps remain that are filled by looking from the bottom. All corrosion-related expenditures are added and compared with the top-down cost assessment. By comparing the top-down and bottom-up corrosion cost assessment, the U.S. DoD has been able to accurately determine direct corrosion costs of a project or asset and to calculate ROI.

The U.S. DoD has used the direct financial approach to track the effectiveness of corrosion control equipment and techniques by determining ROI for specific projects. That is, the DoD only considers those costs that can be tracked by their financial system. A few relevant case studies are presented in Appendix D. The calculated ROI for these projects range from 3 to 56 and are summarized below. Although these cases have a U.S. DoD basis, they are broadly applicable and can easily be applied to the general industry.

• ROI = 9.4 Green Water Treatment. Goals: improving the reliability and reducing the cost of operating and maintaining boilers and cooling towers by using nonhazardous corrosion inhibitors and a smart control system.
• ROI = 8.8 Coating System for CP and Fire Resistance for Metal Structures. Goals: reducing the corrosion rate of the structural steel and increasing fire safety for the structures, as well as validating the technology for other uses.
• ROI = 33 Development of Corrosion Indices and Life Cycle Protection. Goal: develop a life cycle predictive tool to optimize preventive maintenance cycles based on region and material; the predictive tool will be a location-based corrosivity software model.
• ROI = 13 CP of Rebar in Critical Facilities. Goal: corrosion prevention of rebar in concrete in critical facilities located in coastal environments.
• ROI = 15 Ceramic Anode Upgrades. Goal: demonstrate the efficacy of the CP technology in conjunction with remote monitoring.
• ROI = 11 CP Utilizing IR Drop Free Sensors. Goal: Improve corrosion CP monitoring systems and bring cross country pipeline in compliance with industry standards for critical pipelines.
• ROI = 56 Wire Rope Corrosion for Guyed Antenna Towers. Goal: develop a reliable corrosion inspection tool that will ride remotely along each guy wire and measure the corrosive state along the full length of each and every guy wire.
• ROI = 3.0 Solar-Powered CP System. Goal: demonstrate a solar-powered CP system using recently developed high efficiency (96-98%) controls that have flexibility to match the anode groundbed (and its fluctuating conditions).
• ROI = 56 Magnesium Rich Primer for Chrome Free Aircraft Coating Systems. Goal: facilitate the refinement of Mg-rich primer prototype formulations, evaluate the performance, and obtain field-level performance evaluation of Mg-rich based chrome-free coating systems.
• ROI = 16 Corrosion Detection Algorithm for Ship’s Topside Coatings. Goal: deliver a modified corrosion detection algorithm (CDA) that could be used to conduct damage assessments.

Life Cycle Costing

LCC is a well-known approach to determine the cost of corrosion of certain assets by examining:

• Capital cost (CAPEX).
• Operating and maintenance cost (OPEX).
• Indirect cost caused by equipment failure.
• Material residual value.
• Lost use of asset (i.e., opportunity cost).
• Any other indirect cost, such as damage to people, environment, and structures as a result of failure.

The LCC approach makes it possible to compare alternatives by quantifying a long-term outlook and determining the ROI. LCC can be performed by using several costing methods. One method is the Cost Adding Methodology discussed previously. Other methods include the Bayesian Network (BN) approach.

A detailed example of the BN approach to determine the cost of corrosion due to the mechanism of corrosion under insulation (CUI) is given Appendix D. A brief overview is provided here. CUI is a problem in refineries , and other chemical and petrochemical plants. The management of CUI requires a systems perspective because a number of design, construction, and operational factors interact to cause CUI. BN models are highly suited to assess the performance of complex interactive systems because they try to represent the whole system in terms of its interacting parts through cause-consequence relationships. Furthermore, BN models are probabilistic and observational in nature, so they can represent the uncertainties of the system and can be modified based on inspection and sensor data. Finally, BN is a great tool to capture the diverse knowledge of personnel who work with a system.

The predicted business impact could be a valuable key performance indicator (KPI) for operational leaders to make risk-informed decisions, based on their risk appetite and internal decision criteria. The business impact criteria are defined as follows:

• Direct costs: Revenue lost due to down time and clean-up costs from product leaks.
• People: Injury or fatality leading to legal fees, escalating insurance costs, and fines.
• Repair/ replace: Cost of parts and labor for repair/replacement.
• Major accident potential: Defined by the Seveso Directive in Europe (Seveso, 2012), covering any fire or explosion or accidental discharge of a dangerous substance in defined quantities, a fatality of more than six persons injured with hospitalization, massive evacuation, immediate and severe damage to the environment (permanent/long-term), damage to own property (>2 million euro), or eventual cross-border damage.
• Loss of reputation: Reputational damage can lead to loss of clients, additional government oversight, increased borrowing costs, and loss of high-value staff.

A number of scenarios can be constructed on the basis of inputs to BN and the corresponding business impacts can be estimated (detailed costs are shown in Appendix D). For example, in one scenario, the surface temperature is low and therefore the corrosion rate is likely to be low leading to a low probability of failure and injury/fatality. Therefore, most business costs (other than maintenance costs) are low. On the other hand, if the surface temperature is 60 ⁰C, there is no coating under the insulation, and the product is flammable, there is a higher probability of high corrosion and failure leading to significant business costs. The example provided in Appendix D is to examine the cost of an existing system based on multiple scenarios; scenarios that included mitigation measures could also be included, thereby providing a cost benefit analysis of proposed mitigation methods.

An example using this approach was developed by the aeronautical industry. Although this example does not deal with corrosion, it has general applicability and can readily be applied to corrosion management. Prognostics and Health Management (PHM) is described by Feldman et al. PHM provides opportunities to lower sustainment costs, improve maintenance decision-making, and provide product usage feedback into the design and validation process. In the case of PHM, the investment includes all the costs necessary to develop, install, and support a PHM approach, where the avoided cost is a quantification of the benefit realized through the use of this approach. The paper offers a case study of a multifunctional display in a Boeing 737 comparing the LCC of a display system using unscheduled maintenance to the same system using a precursor or anticipation of failure. Analysis of the uncertainties in the ROI calculations was addressed using a probabilistic approach that was deemed necessary to develop realistic business cases.

This case study addresses a specific aircraft avionics failure; however, it can be easily applied to other types of failure such as corrosion. Feldman et al. concluded that in order to determine the ROI of a system, an analysis of all cost-contributing activities is needed such that PHM can be implemented, and a comparison of the costs of maintenance actions with and without PHM can be made. The inclusion of variability in the operational profile, false alarm, random failure rates, and system complexity in PHM ROI models using probabilistic methods (Monte Carlo) enables a more comprehensive treatment of PHM to support decision making.

LCC can be approached in a deterministic and probabilistic manner. Both of these approaches are discussed in detail in Appendix D.

Constraint Optimization

A constraint optimization framework is used to determine the optimal corrosion management practice for a specific structure or facility. This method allows application of optimal practices with a fixed or limited available budget.

The constrained optimization model is presented in Appendix E.

Maintenance Optimization

Maintenance optimization calculates the financial benefit of a maintenance action. It allows inspect/repair/replace projects to be justified by financial benefit. When expressed in terms of net present value (NPV), scheduling of maintenance projects can also be optimized. One way to monetize corrosion maintenance decisions is through risk, which combines probability of failure and its consequence (which can be expressed as cost). An example case study is presented in Appendix D.