Real-time corrosion monitoring
Integrating corrosion data with other process variables: Existing programs on the control system can assess, identify key plant relationships
By Russell Kane and Keith Briegel
The petrochemicals and pharmaceuticals sectors spend $2.5 billion annually to combat corrosion. Worldwide, the cost of corrosion in the process industries appears to be about $50 billion per year and will probably climb higher over the next five years.
Many operators currently see corrosion on a “straight-line basis” in terms of repair, maintenance, and replacement during fixed interval turnaround inspections.
New technology, however, is available that assesses corrosion deterioration in real time using the plant control and automation system. This makes linking corrosion to process conditions more direct and immediate. It also allows the assessment of corrosion in much shorter time intervals with the ability to control and mitigate the rate of damage and more accurately factor in its true economic impact on plant operations.
To many chemical plant and process engineers, corrosion is simply a routine part of plant operations and a cost of doing business. When a plant problem arises, a corrosion specialist gets the call. Upon solving the problem, the plant operates more or less as before, until the next episode occurs. However, the major impact of corrosion to the business lies in costs associated with lost production, health, safety and environmental issues, and legal liabilities.
New technology can help minimize serious corrosion damage to plant process equipment. This allows a new mode of corrosion prevention via the plant distributed control system (DCS) whereby corrosion measurement links to a suite of key, real-time process variables.
In doing this, corrosion gains are possible in many parts on the corporate balance sheet. Process optimization often brings an immediate reduction in direct costs and helps increase plant productivity and revenues while minimizing corrosion damage. Ultimately, it can provide major gains through a reduction in the “corrosion depreciation allowance” from increased plant asset life.
Integrating rust numbers
In many regards, the corrosion engineer’s job is that of a historical record keeper. This is because the tasks to measure corrosion damage traditionally have played out over relatively long time intervals, typically months to years using corrosion coupons and periodic inspection.
Then analysis of this historical information takes place to confirm or predict the effectiveness of corrosion control measures, the risk of future failures, and the need for maintenance. The historical approach, though, is a major limitation. This is because modern plant operations are more likely to be a manifestation of changes in feed, process conditions, and control limits based on current market conditions.
In one recent case, a plant feed changed every two to three days based on deliveries of particular constituents, which were sourcing on a global basis and influenced by market prices. Unfortunately, these constituents also had widely varying impurity levels that led to corrosivity changes, making historical corrosion measurement worthless.
The emergence of online, real-time corrosion monitoring can improve the relevance of corrosion measurements. This approach reduces the manual effort and the high expenses required to obtain this information.
Most importantly, corrosion information is available faster—sometimes in a matter of minutes—and consistent with the process used for other key process data.
This new approach involves utilizing existing data acquisition and automation systems to handle industrial plant and production facilities.
For example, the plant DCS is used to monitor and control processes, trend key process information, and manage and optimize system productivity in industrial plants. By integrating corrosion measurements into this system, corrosion monitoring is easier to implement, automate, and view with other process variables (PVs).
This approach is more cost-effective than conventional stand-alone systems, requires less manual labor to accomplish key tasks, provides a greater degree of integration with systems in place to record, control, and optimize.
These systems can also more effectively distribute important information (corrosion and process data, related work instructions, and follow-up reports) among different groups required for increased work efficiency and ease of documentation.
Link cause-and-effect in time
Corrosion coupons have been the backbone of industrial corrosion monitoring for more than 50 years. They are simple to use, usually accurate, but completely manual. Therefore, coupon measurements are offline, labor intensive, and not easily configured for automation and control systems.
Coupons must be pre-weighed, distributed to remote locations, installed, retrieved, examined, cleaned, and re-weighed before data is processed. Therefore, a good deal of corrosion engineering and related technical staff time is consumed with manual and often routine tasks, as well as manipulating and viewing historically averaged, offline data.
Approaching corrosion assessment from an automation and control point of view, however, would enable corrosion staff to focus on activities that have more value potential. For example, personnel could use their time to examine, interpret, and understand critical underlying system attributes and relationships. Rather than spending time manually retrieving corrosion data, this information could be on a local workstation along with key process variables.
In some cases, corrosion probes used to monitor industrial plants and pipelines connect to field data loggers that take corrosion rate measurements over a period of weeks or months. Corrosion engineers often refer to this approach as “online monitoring,” despite the fact the data cannot be accessed, viewed, or acted upon in an online, real-time manner.
These techniques can retrospectively identify peak corrosion rates and time periods. However, in these cases, corrosion probe data using conventional methods is qualitative, at best, due to limitations in the 1960’s measurement techniques used in most cases for field measurements. We see this information in isolation, without the PVs that allow its interpretation (i.e. PVs that relate to periods of corrosion upsets). Therefore, it is up to the corrosion engineer to try to locate and piece together relevant process information and manually build correlations to understand the causes of corrosion upsets. In this case, the technical staff time often involves traveling to remote locations to retrieve corrosion data files and manually analyzing logged data. Under these conditions, the corrosion engineer is viewed as a bearer of bad news, as the information is usually available only after the damage has occurred or, even worse, after critical failures have taken place.
The current perception is there is a high “per-point” cost associated with conventional corrosion monitoring approaches, largely due to the high cost of a separate infrastructure and large commitment of time and labor.
Additionally, there is a low perceived value because the data is historical and is viewed weeks and months past due. Therefore, there is a tendency to limit resources for corrosion monitoring because this approach is expensive with only a limited chance of success.
In many cases, problems are viewed after-the-fact, and there is no way to link directly the cause and effect in a time frame that allows cost effective mitigation.
Accordingly, corrosion measurement is a confirmation reading of secondary importance rather than a primary variable that is subject to control and optimization in the process.
This perception is somewhat surprising.
Many plant operators are trying to squeeze out a 1% or 2% improvement in efficiency and productivity. However, corrosion costs are one of the few areas in plant operations where double-digit improvements are possible in associated cost-reduction, particularly if lost production opportunity is included.
Estimates indicate between 25 and 40% of the approximately $300 billion lost to corrosion in the U.S. each year could be saved with better control efforts. In several petrochemical cases (e.g. fractionator overhead and hydro processing), the cost of a single corrosion failure can be in the range of $35-$60 million. Even a few days of lost production can involve over $500,000 in lost production.
Feedback of real-time corrosion rate data and adjusted chemical dosage can offer additional gains in efficiency and reduced operating costs, as well as extended run time.
Further confirmation of the potential cost savings reaped through better and faster corrosion information and implementation of improved process controls are apparent in the recent U.S. Cost of Corrosion Study and referenced in recent NACE technical committee reports.
Automation makes considering corrosion as a PV possible as it reduces the time and effort to obtain corrosion data with high reliability. Corrosion as a PV takes on a new meaning when we can see it at a higher frequency (minutes) consistent with the way other process variables are measured.
More data brings increased statistical relevance, quicker response time, and a greater ability to understand corrosion in the context of the process.
Therefore, the second driver for this migration is the ability to integrate the corrosion data immediately with other process data in an automated manner within the plant DCS, rather than by the manual methods traditionally available to the corrosion engineer.
Here are some of the usual process variables that work in chemical plant control systems: temperature; pressure; flow rate; chemical injection rate; moisture content; valve actuation (opening/closing); level measurement; and analytical data—ORP, pH, dissolved oxygen, and the like.
One historical barrier to integrating corrosion measurements within the plant DCS is online corrosion measurements have been qualitative rather than quantitative due to limitations of single technique transmitters with limited on-board processing capacity.
For use as a process variable, corrosion measurements need to be quantitative, since the system will utilize the data to make automated assessments, generate alarms, and determine the economic consequences of process changes and/or upsets.
With this requirement also comes the concomitant need to accurately assess corrosion modality (e.g. general corrosion, pitting, local area attack).
There is probably no perfect method to assess all corrosion mechanisms. However, in most cases, corrosion involves electron transfer in an electrically conductive local or bulk environment.
It has been shown dew point conditions, many multiphase (oil/water) conditions with as little as 1-2% water, and even some fireside high temperature corrosion issues in fossil-fueled boilers and waste incineration can be monitored using electrochemical methods. Therefore, if properly used, accurate corrosion measurements are possible in a matter of minutes in most chemical processes.
One new multivariable corrosion transmitter employs a suite of automated electrochemical techniques that run in the on-board memory of a single transmitter and which complement one another. This multi-tasking transmitter generates general corrosion rate data by combining linear polarization resistance (LPR) and harmonic distortion analysis (HDA) for greater corrosion rate accuracy.
Additionally, it provides completely new information obtained on the localized nature of corrosion from electrochemical noise (ECN) measurements. When joined in an automated cycle, these techniques can provide two critical operator level corrosion PVs at a similar frequency of measurement as expected for current process variables.
These operator level corrosion PVs are:
Corrosion rate—LPR corrosion rate adjusted for a measured B value determined by HAD
Pitting factor—derived from ECN and LPR measurements, providing a three-decade logarithmic scale ranging from general corrosion, through a cautionary zone, to localized pitting corrosion.
Two additional PVs are also possible using the process control system for specialist observation, diagnostics, and intervention:
B value—(also called Stern Geary constant) comes out of the HDA involving the real-time measurement of the anodic and cathodic Tafel slopes. Use it to adjust the LPR corrosion rates with the electrochemical processes in the system.
Corrosion mechanism indicator—Indicating conditions and trends of passivity in stainless alloys, corrosion inhibition, or scale formation
Remedial actions reduce
Integration of corrosion with modern industrial process control technologies offers substantial operational and cost savings opportunities for plant operators. Consider the following examples of value propositions obtained from discussions with refinery operations and corrosion personnel:
Increased ability to process crudes with higher margins—big savings and increased profits
Reduced cost of unscheduled shutdowns—as an example, a 400,000 bpd unit may shut down for three days to repair a corrosion leak. The cost at a $5 margin on feed is $6,000,000. With better integration of corrosion monitoring and plant economics, plant management can better evaluate the cost of unscheduled shutdowns due to accelerated corrosion depreciation. Typically, a plant will have to run at a higher throughput to make up the unplanned short fall.
Improved asset reliability resulting in improved run length—10% reduction in maintenance costs
Improved unit operation because of better corrosion monitoring—may result in a 2% increase in throughput, or potentially the ability to process more of a lower-quality feed.
Reduced health, safety, and environment exposure resulting from fewer unscheduled emissions to the environment—3% savings
Improved safety record as a result of fewer shutdowns—5% reduction in cost
Savings due to optimized chemical cost resulting from better monitoring—10% reduction
Increased operator effectiveness results by bringing the corrosion data on line and in the control room. This leads to improved decision making with new insights and improved issue resolution time.
The benefits from the final bullet item are evident in a recent implementation of online, real-time corrosion monitoring in a hydrocarbon oxidation processing plant. This example involves monitoring performed at a plant where much of the equipment was carbon steel, 304L, and 316L stainless steels.
Decades of de-bottlenecking and other process modifications had produced corrosion problems. After a year of unsuccessful efforts to untangle materials problems offline, they installed an online, real-time electrochemical corrosion monitoring system.
Materials engineers, process engineers, and plant operators saw immediate changes in corrosion behavior caused by specific variations in the process, enabling them to work together to identify process modifications and remedial actions to substantially reduce damage to equipment.
Based on the results of the initial process evaluation that required only a few weeks, five predominant factors were confidently identified that related to the chemical aggressiveness of the plant environment, which varied substantially with process and operational variables. These included:
An upstream vessel was on an automatic pump-down schedule so it pumped its contents into a reactor approximately once per hour. Every time the vessel pumped down, the corrosiveness of the stream increased.
Operators had varied the concentration of a neutralizing chemical in the process. However, contrary to expectations, they found increasing feed rate of a neutralizer increased corrosion rates rather than reducing them. This new information helped to both reduce corrosion rates and provide chemical engineers with new insight into the chemistry of the process.
Following an initial evaluation of the corrosion data, a plant technician pointed out an increase in corrosion rate of the 304L occurred right after they mixed a new batch of catalyst and it varied with feed rate, which they then controlled to minimize corrosive attack.
The corrosion rate varied quite significantly with process and operational events. These included noting the corrosion rate of carbon steel correlated with the quantity of a key gaseous chemical used in the process.
Short-term spikes to very high corrosion rates manifested week after week. The corrosion rate spikes coincided with the pumping of a laboratory waste stream into the process. Operators changed their procedure to dispose of lab samples another way, thus stopping the corrosion spikes.
ABOUT THE AUTHORS
Russell Kane (Russ.Kane@honeywell.com) has a doctorate in metallurgy and materials science and is an internationally recognized expert in corrosion modeling. He is director of corrosion services at Honeywell Process Solutions. Keith Briegel (KBriegel@rohmhaas.com) is manager of the corrosion and materials science group at Rohm and Haas.
A done deal: $500,000
An important aspect of integration with the automation and control system is the seamless connectivity between varying job functions. The Rohm and Haas Deer Park plant near Houston illustrates an example of this integration in a chemical plant.
Last year, Rohm and Haas, a global specialty materials company, became one of the early adopters of online corrosion monitoring technology.
At the Deer Park site, the company planned a more-than-$500,000 alloy upgrade after failing to determine why two similar chemical units were showing widely different signs of corrosion damage.
While one of the plants had low corrosion rates, the other corroded at very high rates, causing rapid failure of stainless steel piping.
After traditional monitoring methods proved ineffective, the company installed corrosion transmitters and connected them to the Honeywell control system.
Communicating via the HART protocol, the transmitters fed corrosion data directly in the process control system, allowing it to be alarmed, historized, trended, and assigned to process groups.
With this information, the corrosion data dovetailed with other process variables, providing a broader and real-time view of plant operating conditions and methods of mitigation through process optimization. The results benefited both operators and the corrosion experts. Plant operators could access current, actionable process variable information, including a time-trended general (uniform) corrosion rate.
Additionally, the solution indicated the mode of corrosion (localized or pitting corrosion) detection called a Pitting Factor. Corrosion staff could access the same information with the added capability to review data for diagnostic purposes.
Using this new system, Rohm and Haas identified two process scenarios that contributed to the difference in corrosion rates. First, one unit’s corrosion rate was higher immediately after a shutdown. The company then discovered and replaced a leaky valve that was allowing water into the system.
Secondly, process corrosion was more severe when a particular recirculation condition occurred. Engineers modified the process, and the plant avoided this condition on the second, more corrosive unit.
The solution saved Rohm and Haas more than $500,000 in capital expenditure, and the company devised an operating strategy that avoids corrosion. Additionally, operators utilized real-time corrosion data in combination with process information to improve equipment reliability, stability, integrity, and uptime. Whereas corrosion is a known quantity to corrosion engineers, this is not the case with operators and process engineers. This example shows how coupling corrosion data with process data creates a tighter working relationship between corrosion, process engineers, and plant operators.
Including corrosion as an online process variable makes plant personnel aware of the process conditions that can initiate corrosion.
Examples of such conditions include unintentional aeration by venting of equipment to atmosphere, additions of oxidizing agents and aggressive catalysts, lack of dew point control in normally dehydrated systems, and excessively high velocities in attempts to increase unit productivity.
Online corrosion detection in a process control environment will allow plant operators to have immediate feedback on the state of corrosion relative to what they are doing on plant, so they can actively participate in managing excessively high corrosion cost.