Refining

A reader who came upon one of the posts in the abnormal situation prevention category asked about ways early fault detection could reduce unplanned downtime in a refinery fluid catalytic cracking (FCC) unit.

I turned to Emerson's Gary Hawkins, a consultant on the global refining team. You may recall Gary from an earlier post on API RP 556 Flame Detection Guidance. I've paraphrased Gary's response:

Predictive diagnostics can definitely help improve the on-stream availability of your FCC unit. In the absence of historical data specific to your current availability of the FCC unit, generally refiners who have implemented predictive maintenance technologies have reduced their outages by half.

I'm assuming that gross generalizations are not sufficient for your purposes so I'll share some of the diagnostics and incidents that can be avoided in FCC process units using diagnostics to enable predictive maintenance. The FCC process is unique within a refinery in that it is extremely dynamic-the unit can be in trouble one minute and safely recover the next minute if proper actions are taken, or the process may need to be shut down for extended periods for repair if proper actions are not taken.

There are diagnostics that continually update the status of the transmitter, detecting internal faults and alerting the operating or maintenance staff of problems with the transmitter itself. However, there are also diagnostics and secondary measurements that can inform operations of impending faults in the process in time to take action to avoid process upsets. A common example of a secondary measurement is the internal temperature of the transmitter. This is useful to detect the failure of heat tracing, warning operations of potential freezing problems. Although not an issue in warm climates, it is an issue with viscous oil streams within the FCC unit (feed, main column bottoms), and it can also be useful to detect transmitter overheating.

Within the reactor section of the FCC unit, key process measurements such as the catalyst level and slide valve differential pressure (DP) are measured with differential pressure instruments that require a special purged process connection to keep the lines clear from plugging with catalyst. Rosemount pressure transmitters with Statistical Process Monitoring plugged impulse line diagnostics can detect the onset of plugging, before the line is so plugged that the measurement is compromised. This diagnostic is very useful for avoiding incidents caused by faulty measurements. This same technology can be used to detect the onset of flooding in fractionation columns and furnace flame instability detection.

Reactor temperature is one of the key operating variables. The advanced diagnostics within the Rosemount temperature transmitter can warn of impending failure of the thermocouple element used to measure the process temperature. Depending upon the actual installation, the transmitter can be configured to automatically switch to a spare thermocouple before failure.

The diagnostics within Fisher digital valve controllers can warn of potential problems with any control valve, before control is lost. Issues with low air supply, torn actuator diaphragm, packing friction (too tight or too loose) can be detected.

Instrument diagnostics can also improve the availability and reliability of Safety Instrumented Systems with DeltaV SIS that can use HART parameters transmitted by the field devices.

The instrumentation specified by the process designer and shown on the Piping and Instrument Diagrams (P&IDs) is typically the minimum amount of instrumentation required to operate the unit. However, operating the process with greater efficiency and reliability often requires additional measurements going beyond the P&ID. WirelessHART-based measurements offer ways to cost effectively add new measurements to monitor pump health, heat exchanger fouling, air-cooled exchanger vibration, fired heater efficiency, etc. These additional measurements also have diagnostics to support the overall reliability improvement of the process.

Hopefully I have provided you with a good idea of a number of ways you can improve reliability of the FCC process unit that you can compare with your own experiences.

Gary, thanks for the great examples!

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Update: An astute reader in Australia noted that there is a separate plugged impulse line diagnostic. I turned to Bill Zhou, whom you may recall from earlier pressure measurement posts for clarification. Bill responded:

Statistical Process Monitoring is a flexible diagnostic that can detect decrease and also increase in variability, allowing for numerous possible applications in addition to plugged line detection. This diagnostic is available in HART and Foundation fieldbus.

There is also a separate diagnostic called "Plugged Line Diagnostic" which is only used to detect plugged lines and is only available in Foundation fieldbus.

I've updated the post to reflect this correction. Thanks for the sharp eyes, mate!

Update 2: I added the bolded phrase "in addition to plugged line detection" in the update above to clarify that SPM can help to detect plugged lines in HART devices.

I plucked this story from a growing and vibrant, "inside the Emerson firewall" community. This community connects Emerson global sales, project, and application folks together, primarily to ask about references--"has this has been integrated with that" sort of exchanges. The particular question was about examples of distillation control.

Emerson's Doug White responded with an example of a European refiner with the business objectives to maximize throughput, maximize the value of product recovery, maximize heat recovery, and maximize heater efficiency to improve overall energy efficiency. The fractionating distillation process involved fired heaters and atmospheric, stripping, and vacuum distillation towers.

The Emerson team, led by Project Manager Chibuike Ukeje-Eloagu, worked with the refinery's engineering and operations staff to plan and execute this project. The project implementation plan was first to conduct a site survey to gather data on current performance and perform preliminary step testing to understand the process dynamics of this unit.

Next the team would design functional, detailed and acceptance test specifications for review, iteration, and acceptance by the refinery project staff. After this design phase was completed, next would come the build phase where the advanced process controllers (APC), steps tests of manipulated variables (MV) / disturbance variables (DV), and models would be developed.

The final commissioning step would be to commission the controllers, train the engineering and operations staff, and conduct the site acceptance test per the test specifications. An important final step was to benchmark the process' performance, compare against the original process data collected, and calculate the return on investment for this optimization project.

Model predictive control (MPC) embedded in the refinery's DeltaV control system was employed because the process had large interactions. These interactions made single and cascade loop control strategies difficult to implement and maintain over time. The process had a number of disturbances for which the model needed to account. It also took a long time for the process to reach steady state conditions. The solution was to create five APC controllers--one for each fired heater, one for the atmospheric tower, reflux drum, and stripping towers, and one for the vacuum tower.

One of the key constraints in the process was the product compositions of the gas, naphtha, kerosene, light diesel, diesel, atmospheric gas oil (AGO), low-vacuum gas oil (LVGO), and high-vacuum gas oil (HVGO) produced. The traditional method had been manual measurements that were drawn and sent to the lab once per day.

Chibuike's team developed regression-based inferential sensors or virtual analyzers, built with neural networks, to predict the product compositions in real time. An example of a virtual analyzer was one to predict the diesel pour point. These virtual analyzers perform inferential analysis using a regression based on product flow rates and distillation column temperatures. The predicted values are updated daily against the laboratory results to help keep the neural network models virtual analyzers tuned and making accurate predictions. The model predictive controllers use these predicted values as constraint variables to keep the products within specification limits.

Upon installation and post-audit, the throughput was increased to a level where the downstream units actually became the bottleneck. The quantifiable results were a payback within three months. This came from increasing production of more valuable products while reducing product giveaway and improving heater efficiency. The non-quantified benefits were reduced operator actions to maintain steady-state operations and improved response to disturbances such as crude oil composition changes.

Over the past several years, the controllers and virtual analyzers have been in continuous use. The refiner and Chibuike's team have ongoing service agreements should immediate help or tweaks to the models need to be made. The models are robust and tolerant of inaccuracies to a certain degree and so long as no major process modifications are made, the models have not required refitting to the process dynamics.

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Update: I wanted to give a note of clarification that the neural networks initially used were replaced by regression-based inferential analyzers due to insufficient historical data in the historian to properly train the neural networks. I've updated the text in the original story above.

Chibuike shared with me that the in country Emerson office provides the day-to-day ongoing support as required to keep this optimization project successful.

OK, I confess to being an engineer in my core when I was explaining to my son the other day how the heart is a reciprocating pump. The systolic and diastolic pressures are the high and low-pressure peaks based on the heart's expansion/contraction cycle. Blood pressure is one diagnostic indicator on the health of the heart and circulatory system.

What prompted me to remember all this was a presentation I'm looking at by Emerson's Tim Olsen. You may recall Tim from his successful election to the position of 2nd Vice Chair for the AIChE Fuels & Petrochemicals Division (FPD). The subject of the presentation is pump health monitoring.

Thankfully, Tim did not take this heart analogy path we find ourselves on in this post. Typically, a process pump failure will cause a process upset and loss of production. If the pump is pumping flammable or hazardous substances and has a seal failure, safety, health, and environmental issues may occur. Having a spare in-line pump does not prevent unexpected failures that may result in conditions requiring prompt operator attention.

Without monitoring, pump seal failures often appear to be sudden and indicated by spills, vapor clouds, or fires. Today, for most process pumps, warnings come from periodic manual vibration measurement. Tim shares that most refiners monitor their critical pumps, perhaps 5% of all the pumps. The definition of what is critical is likely similar across refiners, but there will be differences.

Both safety and economic reasons are considered when identifying critical pumps. Every pump, critical or not, can cause pains such as process upsets and increased maintenance costs. For this reason, pump health monitoring may be warranted on many "non-critical" pumps. In the case of refiners, Tim cites a pump failure example, which can lead to insufficient fractionator reflux causing column overhead system over-pressuring. This in turn leads to the lifting of a relief valve to flare.

Tim recommends adding wireless measurements in places where existing diagnostic instrumentation is not present. He has observed three key areas that refiners are looking at pump monitoring capabilities: alkylation units, critical workhorse units like the crude unit, fluid catalytic cracking (FCC), and hydrocracker, as well as those applications with a history of unexpected pump failures.

Continuous vibration monitoring is important to identify and prevent root causes of seal failure from occurring. Some causes of this vibration include poor shaft alignment, worn bearings, loose pump mounts, broken foundation mounting bolts, cracked foundation, cracked or damaged impeller, and cavitation. This excessive vibration increases the wear on the pump's mechanical seal leading to failure.

Replacing the field operator or maintenance technician's manual spot measurements with continuous measurements provides the information to predict when failures will likely occur to allow maintenance to be performed before a failure occurs. This information can be historized and trended and made available in real-time to both console operators and maintenance departments. Wireless vibration transmitters form the heart of a health monitoring solution that is secure and easy to implement.

Tim makes the point that that having pump health monitoring is like adding sets of eyes continuously focused on these pumps, providing operators the opportunity to take corrective action before the pump failure. This early warning can help avoid the associated health, safety, and environmental impacts.

Pump health monitoring as part of an overall predictive maintenance program can deliver financial returns. In a Chemical Processing article, More-intelligent devices help plants get smarter, Emerson's Doug White noted:

Actual implementations of predictive maintenance have led to significant gains... Potential production from existing equipment typically increases 1-3% because of fewer unscheduled shutdowns, while unplanned maintenance costs decrease 10-30%. The return on investment can be among the highest of any possible plant expenditure...

Although this may admittedly be a stretch, the cost of pump health monitoring is perhaps like the cost of good nutrition and exercise for maintaining a healthy heart.

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I saw some startling facts in a presentation by Emerson's Pete Sharpe, whom you may recall from many process optimization-related posts. This week he visited The Automation Group (TAG) office in Houston, to discuss distillation and fired heater optimization. I was speaking with Aaron Crews who was able to catch this presentation. Aaron's expertise has also has been highlighted in several automation modernization and social media related posts.

Did you know that there are over 40,000 distillation columns in the U.S. alone? And that they consume 40-60% of the total energy in the chemical and refining industry. And that these distillation columns consume 19% of the total energy consumed by U.S. manufacturers. And finally, that these consume 6% of the total U.S. energy usage. If you drive along the Texas Gulf Coast and see all the refineries, petrochemical, and chemical complexes, it's not hard to accept these statistics.

I think it's safe to say that anything that can be done to improve the energy efficiency of these distillation columns will reduce operating costs, improve emissions, and lower the overall domestic need for energy. Pete noted that reducing energy consumption is one of the best ways that U.S. manufacturers can meet the Environmental Protection Agency (EPA) greenhouse gas reporting rules.

Pete and his team of refining and chemical consultants, work with process manufacturers to optimize the performance of their distillation processes. SmartProcess Distillation packages the team's subject matter expertise, couples it with Emerson products such as the DeltaV system with its embedded advanced process control, and provides planning, engineering, commissioning, and training support on these optimization projects.

For those not as close to the process of distillation, a distillation column separates components based on different boiling points. The column is made up of trays, and the temperatures of these trays usually reflect composition on that tray. These temperatures need be compensated for pressure.

From a control strategy perspective, in any column, you are trying to control a composition of the top product and the composition at the bottom of the column - simultaneously. The mental framework one follows is, "What comes in must go out." This translates into a material balance and energy balance. The material balance is represented by the fraction of the feed that goes overhead, or the overhead (OH) rate divided by the feed rate. The energy balance is represented by a reflux ratio, or the internal reflux flow rate divided by the feed rate. Dual composition control uses both the material and energy balance handles to simultaneously control both overhead and bottoms compositions. Since these are highly interactive, it typically requires a model predictive controller like PredictPro to accomplish closed loop control.

Aaron relayed a key point that Pete emphasized. As you approach 100% purity on either end of the column, the change in energy per change in purity increases dramatically, making high-purity columns prime targets for energy savings. Pete stressed that Advanced Process Control will almost always reduce the column variability, push to minimum reflux limits and allow operators to run closer to the specifications. This in turn results in improved product quality controls, less quality giveaway, lower specific energy consumption and less emissions. Good for profit, good for the environment.

Pete shared some typical results achieved in installing the SmartProcess Distillation application. For 1-2 weeks of engineering to design, install, and commission, plants have been able to achieve a 40-80% variability reduction, 5-10% throughput increase, 5-10% energy cost reduction, less off-spec / rework and improvements in safety and environmental metrics.

If you see opportunities to improve control on your distillation columns, it seems like the energy reductions and improved operations can fund it.

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Update and bump: Tim just let me know that he's been elected to the position of 2^nd Vice Chair for the AIChE Fuels & Petrochemicals Division (FPD). As described below, he'll serve a four-year term including one year as division president. Congratulations, Tim!

Emerson's Tim Olsen, a refining industry performance consultant, recently presented to Argentinean refiners on advances in automation. Tim has 20 years of experience in refining starting as a technical advisor on refinery unit startups for UOP before joining Emerson as a performance consultant. He has been active in the AIChE Fuels & Petrochemicals Division (F&PD), is a 3-year, nationally elected director for the division and is the programming chair for Topical 7 on Refinery Processing.

In his presentation, he shared some statistics on the amazing march of technology over the last 40 years. Computer processing performance has increased 50% per year compounded over the 40 years. RAM memory and disk space storage have increased in a similar manner. Communications bandwidth for both wired and wireless have also experienced exponential speed increases.

The exception to this exponential technology performance increase is software productivity. It has increased only 4% annually from the 1970s to 2000 and is even less for the first decade of the 21^st century. It has become the dominant cost in system development and implementation. The upside is that software typically has a much longer life than hardware.

Tim highlighted some changes made possible by these trends including low-cost computing and communications, virtual organizations independent of distances, disappearing computational limits, and increased digitization since practical limits on storage space are disappearing.

Specific for refiners, the instruments that touch the process provide more than a process variable back to the operator. Build on digital bus networks, the operators and maintenance technicians receive the not only the process variables, but the goodness of the information. They also receive diagnostic and predictive alert information to help avoid abnormal situations. I recently highlighted some of these diagnostics accessible from handheld devices.

Refinery control rooms have also changed. Where once each unit had a separate control room with single loop analog control and panel board interfaces, there are now more site wide control rooms with coordinated multi-loop digital controls and high-resolution monitor-based operator interfaces.

The economic conditions in which refiners operate have also changed. Many may recall the days of cheap energy, cheap water, cheap waste disposal, less emission standards, predictable supply and price of raw materials, and a large talent pool. The controls and layered advanced software applications were the pricy component. These conditions have largely flipped over the past decade.

Tim offers many examples in the presentation. I'll highlight one--the hydrocracker quench control valve. The digital valve controller on this quench valve can identify low instrument air levels and alert maintenance techs and operators before poor control response occurs. Early recognition and reporting of this situation is critical since the reaction is exothermic. If the operations staff reacts and repairs the instrument air levels, emergency depressurization and shutdown can be avoided. See the presentation for other examples on predictive analytics, plant turnarounds, system modernization, key performance indicators (KPIs), advanced process controls, and more.

I'll also put in a plug for Tim having known him for many, many years. Tim has been active in the AIChE F&PD since 2002 and is seeking the 2nd Vice Chair position. When I asked how this works, he explained that you are elected as a 2^nd Vice Chair, become the 1^st Vice Chair the following year, assume the Chair/Division President the 3^rd year, and become the Past Chair in year 4 to advise the new Chair. It sounds like they have a solid, on-the-job training model to me!

Members in good standing with AIChE should have received an email to vote on-line between January 15^th and February 15^th. If you're a member, you can see the full list of candidates and positions and decide for whom you will cast your ballot.

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As the politics of greenhouse gas emissions in Washington and other capitals around the world continue to unfold, process manufacturers must continue to meet the regulatory mandates that come their way. They are also challenged to improve safety, security, and their operating margins to address global competitive pressures.

Emerson's Patrick Truesdale, a refining and chemical industries senior solution consultant, will be presenting at the March 21-23, 2010 NPRA Annual Meeting. His presentation is entitled, Benefits in Achieving Regulatory Compliance. At first blush, it seems counterintuitive that achieving regulatory compliance would have financial benefit. But, for refiners, energy is the largest operating expense. Patrick notes that energy efficiency projects not only reduce these operating costs, they also aid in regulatory compliance and improve safety.

In the U.S., the new greenhouse gas mandatory reporting rule (GHG MRR) mandated that monitoring begin January 1, 2010 with the first report due on March 31, 2010. The report specifies levels of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) emitted based on industry accepted measurement standards and procedures from ASTM International, the American Petroleum Institute (API), and others. The reporting rule defines strict quality assurance (QA)/quality control (QC) standards and associated documentation. Non-compliance to these reporting rules includes civil and possible criminal penalties.

Patrick points to three ways to most economically meet the GHG MRR regulations. The first is to put the business processes and procedures in place to enhance loss control. It's a good idea to follow well-established measurement standards and fiscal controls such as Sarbanes-Oxley, custody transfer, foreign trade zone (FTZ) customs and excise, etc. Loss control can also be enhanced through mass and energy balances as well as the establishment and ongoing monitoring of key performance indicators (KPIs).

The second way to help meet GHG MRR regulations is to enhance key equipment performance such as control loops, measurement devices and systems, and leak identification and repair. The third way is to improve the energy efficiency of key combustion units such as furnaces, heaters, and distillation columns. As you focus on these energy efficiency opportunities, it also means you're reducing emissions, as I described in an earlier post. Benefits can also come in safer operations from reduced variability, increased equipment reliability, better utilization of assets, improved quality, and improved loss management.

Patrick presents a path forward based on the strategy of "low-hanging fruit" first. Start with the low capital cost items in terms of funds and time to implement that have the highest potential savings. The good 'ol 9-box grid with high-medium-low potential savings versus high-medium-low capital costs is a good way to organize the projects to execute.

For instance, making procedural changes, monitoring KPIs, improving instrumentation and controls might be low in capital costs yet deliver medium-level potential savings. Fixing insulation, steam traps & leaks, etc. may be low in both capital costs and potential savings. Redesigning the process and upgrading process equipment may be high in capital costs yet yield significant savings.

In the presentation, Patrick offers numerous examples such as suggested KPIs to establish and track, measurement of fuel flows by mass instead of volume, adding wireless devices to improve energy monitoring, resizing pump outflow control valves, and using advanced multivariable control on fired heater units to operate at optimum combustion levels.

There are more examples than I can fit into this post, but I hope these give you a flavor of the experience that Patrick plans to share in this presentation. If you'll be in Phoenix for the NPRA Annual Meeting, it may be worth your time to check out Patrick's presentation. It would be a great thing if you could take some of his thoughts back to your plant to improve energy efficiency and reduce energy costs, while helping meet the regulatory reporting mandates and improving process safety.

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As yesterdays's Wall Street Journal points out in the article, Cramped on Land, Big Oil Bets at Sea, oil companies have to look in increasingly difficult places to find energy.

As energy producers look beyond oil and gas for other energy sources, alternative fuels have been playing a growing role. Right before the holidays, Emerson's Al Novak, director of the alternative fuels team organized an Alternative Fuels regional summit in Houston, Texas. The Texas Gulf Coast accounts for nearly a quarter of the United States refining capacity. This locale helped shaped some of the summit's focus on using refining leftovers like petroleum coke or coal in alternative fuel gasification.

The summit brought together people from academia, process manufacturing, process automation, engineering, procurement & construction, capital investment, and government to share ideas and practices on production processes, stages of deployment, market conditions, and legislative landscape.

The local newspaper, the Houston Chronicle, interviewed Al and published the article, Q&A Making the alternative fuels push EMERSON: Fuel from coal draws attention. Al addressed how climate change legislation might impact projects using coal and petroleum coke (a.k.a. pet coke):

If carbon emissions are capped or taxed, they currently don't have any mechanism for capturing CO2 at a cost effective rate. The positive for things like coal gasification is it provides a real concentrated CO2 stream. In the event capture is required, there is at least a means to capture it in a fairly cost-effective manner. Climate change legislation could actually drive some of these plants forward because they provide a means to do the capture.

On fuels derived from coal or pet coke qualifying as renewable fuels under U.S. federal energy laws, Al noted:

DOE [U.S. Department of Energy] has been pushing advanced coal gasification facilities for a very long time. The loan guarantees that are coming out right now were actually authorized under the Energy Policy Act of 2005. Under the American Recovery Act, I believe it was an additional $2 billion that was approved for CO2 capture demonstration projects. Gasification qualifies under those monies.

A final point Al made about the environmental concerns with using coal for transportation-related fuel was:

The biggest, in terms of environmental, is the CO2. Again, it provides a means for capture. It is a cleaner process than, say, burning coal in a power plant, because the nature of gasification allows you to take all the mercury, the sulfur, the other noxious chemicals you get if you burn it outright. It allows you to clean the fuel up much more efficiently.

You might find the full Q&A beneficial if you are involved in the research, funding, design, engineering, or production related to alternative forms of energy.

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I saw in my Sound Off blog RSS feed that Dan Hackett, part of Emerson's Daniel Measurement and Control business, did a podcast interview with Walt Boyes. The 25-minute podcast is on some new Daniel Ultrasonic flow measurement technology being introduced at the upcoming Emerson Exchange.

Dan starts by describing how these critical ultrasonic flow measurements work. I thought Dan's explanation was more understandable than my Guadalupe River rafting analogy in an earlier post. If there's no flow, the time it takes the ultrasonic pulse to travel across the pipe from one side upstream to the other side downstream and back is the same. As the flow increases, the time difference between the travel across the pipe each way increases--since one way the pulse goes with the flow and the other way it goes against the flow.

Dan described how some of the Daniel liquid and gas ultrasonic flow meters have 4 measurement paths to get different measurements at different points to integrate an average flow. The average axial velocity multiplied by the area of the pipe gives the uncorrected volume flow rate through the ultrasonic flow meter.

He described how these critical meters are used primarily in custody transfer applications. For those not familiar with the term, custody transfer is like the cash register where the possession of feedstocks, intermediates, and finished products changes hands between companies, governments, or countries. The measurements must be highly accurate and agreed to by both parties.

As Walt pointed out in one of his questions, ultrasonic flow measurement, because of low-pressure drop and high turndown capability, can handle a wide range of applications from very high temperatures to very high pressures. Dan described an application in gas measurement where this technology was being applied. Offshore and onshore gas production measure high-pressure natural gas--usually at the custody transfer point with the gas distribution pipelines. High volume consumers of natural gas, such as power plants and aluminum producers will meter the incoming natural gas. Also, many municipal districts measure the incoming natural gas before it goes into their distribution systems for the area businesses and residences.

For liquid custody transfer, crude oil production and processing are typical applications for ultrasonic flow measurement. Dan mentioned that right now it's mainly used in the feedstock and finished products areas of refineries, and less so in the process itself, where other flow measurement technologies are typically applied. In a refinery, the custody transfer surrounding the incoming crude and the refined products such as gasoline, diesel fuel, and kerosene are good applications for ultrasonic flow measurement. A final application Dan notes was liquefied natural gas (LNG) facilities where the incoming natural gas is measured and also in regasifiers where the liquid is converted back to high pressure gas for final distribution.

The new ultrasonic flow meter transducer being shown at the Emerson Exchange extends the temperature and viscosity range to address more applications like the heavy crudes found in the oil sands and oil shales. Typically, conditioning processes were required to reduce viscosity and or temperature, which add operational costs to the custody transfer measurement process.

One of the big enhancements Dan mentioned was on the software side, where diagnostics now embedded expert knowledge to identify conditions such liquid fractions in gas and pipeline deposit layer buildup. In oil & gas applications, the first case helps spot expensive liquid condensate giveaway. Accumulated buildup inside of pipes impacts the integrity of the custody transfer measurements. When these diagnostics are connected to the Daniel CUI 5 or AMS Device Manager software, operators and maintenance personnel are notified of a problem immediately and offered suggestions for corrective action. The CUI 5 baseline viewer provides a consolidated view for monitoring performance within pre-set ranges.

I found the podcast to be 25 minutes well spent as well as the recent email newsletter in getting up to speed on the latest developments in ultrasonic flow measurement and good application fits.

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Sometimes plants go through a revamp and things just don't work right. Loops that used to run fine in automatic mode now run in manual mode and require constant attention. I caught up last week with Emerson's James Beall, a principal process control consultant, whom you may recall from earlier posts.

James shared a great story with me about a recent visit he had to a refinery. Many months ago, they had gone through a crude unit revamp. They were struggling with the operations and it required quite a lot of operator intervention to keep things running. Many of the key crude unit loops were being run in manual because automatic mode was too unstable.

James described it to me as a back-to-basics visit. Working with the operations and plant engineering staff, they discovered quite a number of instrument and tuning problems. One example was a level transmitter that had been improperly configured. James used some of the control performance tools to gather and assess the process dynamics around the level loop.

While performing a bump test on the level loop, the team noticed the level signal responding in the wrong direction. A quick check revealed that the level transmitter calibration had set the transmitter to have reverse action, which prevented the level controller from working. It's no wonder the operators wisely had put the loop into manual mode to prevent this from happening.

Using a methodical one-by-one process through the critical loops, James helped the team properly tune each loop and discover problems with the surrounding control valves and instruments. All the tuning skills in the world can't help get a loop to behave properly if the valve is sticking or the transmitter is not performing well. The maintenance staff fixed what they could with their available spare parts and put a plan together for fixing the other problem assets.

Over the course of five days, the team resolved the major issues and smoothed out the operations of the crude unit. James shared with me that this approach helped the operations team regain confidence in the tuning and return the loops into automatic mode. His time spent with the team also was used to share his expertise to help them be able to work through future issues as they arise. In that sense, it was also in-the-field training on process control performance.

I like the quote he shared from one of the operators after the first two days on-site:

My goodness, you fixed more of these problems in two days than has been fixed in the past several months.

James noted that these results were really the result of a great teamwork effort with the plant personnel. Thanks for sharing this great story, James!

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I heard a few weeks back that Emerson's Dr. Doug White, was going to be honored by the American Institute of Chemical Engineers (AIChE). I was sworn to secrecy, which is not an easy thing for someone with an itchy finger on the "publish" button. Since the press release is now out, it's safe to talk about Doug.

He is a Principal Consultant for the Process Systems and Solutions business and has held positions such as Vice President APC Services for Emerson, President of MDC Technology, President of Profitpoint Solutions, Senior Vice President for Automation Technology for Aspen Technology, and President and Chairman of Setpoint; all leading companies in the development of modern process plant advanced automation applications.

At this week's 2009 AIChE Spring National Meeting, Doug receives the:

AIChE Fuels and Petrochemicals Division (FPD) award, one of two FPD annual awards, for his outstanding technological contributions to the advancement of these industries.

The Fuels and Petrochemicals Division describes this award:

Recognizes individuals who have made substantial technological contributions to the advancement of the fuels and petrochemicals industries. Selection criteria includes: 1. Long and recognized record in the nominee's areas of achievement. 2. A chemical engineer and preferably an AIChE member. 3. Awardees are selected based on a combination of technical achievement, management skills, business acumen, academic leadership and general service to the profession. 4. Selection shall be balanced between the fuels and petrochemicals industries.

We have featured Doug several times on this blog, including stories of saving energy with advanced automation, justifying capital projects, and assessing energy reduction opportunities. The common thread is that Doug helps quantify the solution with the business objective. He helps engineers speak the language of finance to get the capital or expense budget required to do the project and quantify the results.

I thought in addition to Doug's wisdom shared over the years that I'd give you a little of his background. He has a BSChE from the University of Florida, an MSChE from California Institute of Technology, and an MA and PhD in ChE from Princeton. He's been a member of AIChE for more than forty years.

Doug has applied the fruits of this education and work in the field of process manufacturing and has developed special expertise in the field of advanced manufacturing automation. He has more than thirty years experience designing, developing, managing and implementing advanced automation and optimization systems in oil refineries and chemical plants around the world. He has authored or co-authored more than fifty technical papers on these subjects, many documenting first-of-a-kind system installations.

At this week's AIChE conference Doug will present, The Digital Plant: Progress and Promise. Doug discusses the current state-of-the-art in process plant sensors, automation, and information technologies and offers some projections on future developments. He shares the areas of plant operation that have seen the largest effects to date and the areas in which he expects to see the greatest impact in the future. I guess there's no time to rest on one's laurels when there is wisdom to share.

Congratulations on this well-deserved award, Doug!

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I received an email from the Center for Operator Performance (COP) about a newly completed study, Color Usage in Graphic Displays for Process Control. Emerson is one of the founding members along with members from process manufacturing, academia, EPCs, and automation suppliers. Emerson's Mark Nixon, who leads the research efforts for the DeltaV system, is also the chairman for these research efforts at the COP.

The center oversees research to meet the needs of the members and is responsible for contracting universities and human factors companies to conduct the research. The center also serves as a repository for human factors data in process control and training in human factors as requested by the members. Research interests include the following:

Expertise - With attrition of operators, much expertise is walking out the door of process plants. What makes an expert operator? What skills does an expert possess that a novice does not? How can novices become experts faster?

Simulator Effectiveness - While simulators in general are a wonderful tool for enhancing operator performance, their application in process control has historically yielded mixed results. What are the key attributes of a successful simulator training program? How important is simulator fidelity in the success of training?

Graphics & Data Presentation - Process operators deal with thousands of process variables that ultimately become the basis for a single decision. How can graphics better support this effort? What impact does background color have? Does the use of one color for more than one meaning impact performance?

Alarm Actuation Rate - What is the upper limit for alarm processing? How long can this limit be sustained without impacting performance?

The Operator Display and Color Usage study is the first of a multi-part study investigating the overall topic of display design. In this study, the researchers reviewed the current literature, surveyed operators, and visited a number of operating sites. A key component of this project was to bring the researchers up-to-speed with what the state-of-the-art is in the petrochemical industry.

As part of their learning, the researchers were looking for evidence on whether or not best practices related to color and visualizations are being followed. The 99-page color usage study is available for members of COP and was prepared by Dr. Jennie Gallimore and Jennifer Shinkle, with Wright State University. With Emerson as a member, I was able to get my hands on a copy and here are a few things I gleaned. If you're interested in the full research, here's the COP contact page.

One conclusion that the researchers came back with was that although there is considerable research on the use of color and other visualization techniques for display design, guidelines specific to the petrochemical industry are scarce. Color as well as other guidelines such as position, form, and animation could potentially help display designers to improve their overall display implementations.

The researchers also made another observation; color is probably not the most pressing problem, a bigger factor is the overwhelming number of displays and the design and presentation of the information on these displays. For example, although mimic displays such as P&ID's are simple enough to create, they are not necessarily the best way to present information to operators. Further studies are required to look into better ways to organize and present information on displays.

The research was performed working with U.S. refining and petrochemical manufacturers and their operations staff. The mean age of study participants was 46 with an average of 16 years experience. The report notes that more than half of the research participants have some form of corrected vision. As someone in this age demographic and needing those "cheater glasses" myself for dimly lit rooms, I can appreciate this growing trend.

The research also looked at lighting conditions in the operator rooms, environmental conditions (temperature, humidity, noise, and vibration), total colors used in operator displays, alarm-related colors used, and different aspects of display element effectiveness. It looked at many other things too, including display technology, considerations in vision and color perception, and ways color is used in visual displays. From the responses, the study points to opportunities for improvement to better define color usage and visualization guidelines.

I asked Mark his key take away from the research. Mark notes that although there is considerable research behind visual encoding techniques, that research has not made its way into our industry. A key challenge that people responsible for configuring displays face are that there are few guidelines describing best practices and for the best practices that do exist, there is very limited research proving that the techniques actually work in our industry. The center's goal is to provide that research. A well-designed operator interface will improve overall plant operations and environmental, health and safety conditions. The members of the COP share these objectives and are jointly funding this research.

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As reported by the Automation Gear blog, a big breakthrough has come to Micro Motion Coriolis flow meters. They can now be powered with two wires. These same wires carry the process variable and digitally communicate other process variables back to the process automation system via HART.

I did some reading and learned that that ultra-low power technology in the transmitter coupled with an optimized Coriolis sensor design made it possible to power these flow and density meters on a 4-20mA HART signal. Process manufacturers should continue use the 4-wire design for the real demanding applications like fiscal metering and custody transfer, meter verification and ones with entrained air.

Outside of these demanding applications, many mass flow, volume flow, density and temperature applications are well suited for the 2-wire Coriolis meter.

I caught up with Tom O'Banion, who leads the chemical industry efforts in Emerson's Micro Motion division. He noted that Coriolis technology has increasingly been used to measure liquids and gases because of its accuracy and reliability compared with other flow measurement technologies.

With units typically spread over great distances, installation costs have been one limiting factor in the use of Coriolis technology. Tom noted one refiner's estimate of $15 per foot plus labor for the cost of pulling the additional power wires needed for the 4-wire transmitter. This can add up quickly in tank farm or hydrogen metering applications that are typically long distances from the rack room.

Many natural gas metering stations on individual units were installed when natural gas was inexpensive--$1/Mscf. With prices now closer to $8/Mscf, chemical manufacturers and refiners want to track natural gas usage much more closely to optimize their operating costs. A typical small ethylene cracker may consume $200-$300 million in natural gas per year. Instead of differential pressure across orifice plates or turbine meters, a two-wire Coriolis meter can more accurately measure natural gas consumption and provide the flow, density and temperature measurements via HART back to the automation system for tighter control.

Another application Tom mentioned is hydrogen metering. It is usually located along the perimeter of the refinery. It's very expensive and quite difficult to measure with conventional technologies. Using the existing wiring, the 2-wire Coriolis meter provides more accuracy and less maintenance.

Tom also noted that installation costs with the additional wires sometimes prevented the use of Coriolis technology in applications for which it was better suited--especially if the analysis had been based on installed costs rather than lifecycle costs (which favors Coriolis technology with no moving parts.) The two-wire version shrinks the installed cost difference.

It's great that technology continues to advance to create more opportunities to optimize and save energy. I'll continue to pass along applications as I come across them.

James Beall delivered a Back to the Basics - Process Control Diagnostics Improves Refinery Performance presentation at the recent AIChE spring meeting. James, whom you may recall from earlier variability management posts, is a principal process control consultant. He's a senior member of Emerson's variability management consulting team.

In this presentation, James stressed what he normally stresses with process manufacturers--that some of the largest and most frequent opportunities exist in basic process control. These opportunities include eliminating variability at the source, tuning the controllers to meet the control objective, using ratio, cascade and feed forward control as well as using a process analysis system to diagnose problems and tune loops. Addressing these opportunities also builds a control foundation essential for any advanced process control (APC) initiatives.

He referenced a 1997 McKinsey study that showed 50-60% of the value realized from a process optimization project comes from addressing loop variability. The balance 40-50% comes from applying APC on top of these optimized loops. The financial results from reducing variability are being able to operate closer to constraints such as specification limits. Benefits can come from reduced energy consumption, less waste and rework, higher yields, higher quality, etc.

The variability management team keeps statistics on control loops with excessive variability from site audits. The major causes of this variability include control valve performance (30%), improper tuning (30%) and improper process design (20%).

James shared several valve-performance examples including a regenerator pressure valve. By looking at the setpoint, pressure, output, and valve position trends, he spotted the valve sticking and then jumping 3% followed by a quick spike of another 2-3%. This caused periods of oscillations before settling out. Once the sticking problem was addressed, the oscillations became tiny ripples on the trends. Similarly, poorly tuned loops can cause large oscillations impacting overall process variability.

He noted that you must have a process dynamics analysis and diagnostic tool of some type to pinpoint these sources of variability. Problem identification is the first step in corrective action. And these problems may be significantly impacting the overall efficiency of the process.

James described some of the tests that he and the variability management consultants use with the Entech Toolkit. One of the most important tests is to identify the process dynamics so that the control loops can be properly tuned. Emerson's Entech Toolkit can identify common dynamics such as first order, second order overdamped and integrator+lag. Dynamics that are more complex can be identified by this process analysis toolkit (11 tests in total) and the associated controller can be properly tuned. Many of the more complex process dynamic responses cannot be identified by less sophisticated analysis systems.

If you have the bandwidth and inclination to learn the skills to do it yourself, James recommends three Emerson Education Center courses: Process Dynamics, Control and Tuning Fundamentals, Process Analysis and Minimizing Variability and Modern Loop Tuning.

I received an email from a university student with a great question the other day. It prompted a great answer from Pete Sharpe, a Principal Advanced Automation Consultant. You may recall Pete from earlier posts on process optimization.

I've retained the anonymity of the person asking the question by editing the question:

I am doing my thesis on estimation of benefits by implementation of advanced control, I read your articles in this field and it help me so much, but I still have some questions, I would like to know if you could give me information about how to calculate the benefits to pour point, viscosity and Research Octane Number (RON). I will be grateful for your help.

Pete responded:

I was forwarded your request about calculating benefits. I've had some experience in this area. Are you estimating benefits for a blending process? If so, the opportunity is to reduce variability and approach the specifications closer using less of the more valuable components. So instead of making 87.5 RON on the average, you reduce it to 87.1. The value is the total blend rate times the difference in average octane times the octane barrel cost.

Anyhow, I'm attaching a paper that perhaps might help describe how these benefits are calculated.

I contacted the ISA and received permission to re-host this paper, Estimating Benefits from Advanced Control (Copyright © 1986 ISA. Reprinted by permission. All rights reserved.)

In the paper, the authors (Pete, P.L. Latour, and M.C. Delaney) apply statistical methods to estimate savings from dynamic control improvement and steady state optimization. At the end of the article, they run through a distillation column example calculating annual dollar savings by reducing process variability and thus allowing the column to operate more closely at its limits.

Whether you're a student or a project engineer, you might find the calculations in this "oldie but goodie" paper useful in trying to estimate and quantify the benefits for your project.

Last week I did a post about pipeline surge pressure relief and a technical guide about this written by Emerson's Daniel business. They are known for gas and liquid fiscal flow measurement solutions for the oil and gas industry.

I received a nice follow up note from Dave Seiler about a Latin American refiner who was fighting turbine meter maintenance problems due to large concentrations of foreign materials in the pipeline liquid flow. The problem was so acute that they actually had to install two meters in parallel so they could switch between meters while the other was being maintained.

The refinery engineers worked with the local Daniel team to replace the turbine meters with a 6-inch liquid ultrasonic flow meter. These do not have moving parts, unlike the turbine meters, which were being impacted by the particulates in the flow.

I didn't know much about the ultrasonic technology in flow applications, so I googled around and found a Hydrocarbon Processing magazine article reprint, Use liquid ultrasonic meters for custody transfer, in the Daniel area of the EmersonProcess.com website.

Dave is a co-author of this paper. The article does a great job of simplifying how the ultrasonic technology works. It also includes the math on how the ultrasonic flow measurement works.

My analogy, fresh from a rafting trip down the Guadalupe River, is to imagine that you're floating down the river with an ultrasonic transducer on one bank, and another on the other bank a little further downstream. Ultrasonic pulses are sent between the two transducers in each direction. The pulse traveling across the river from the upstream one to the downstream one will obviously travel faster since it's going across the river with the current. And of course, the reverse is true; it takes longer to travel across the river going upstream against the current. With the formulas in the article and enough perseverance, you can calculate the river's flow rate from these time differences. For the 3D world of pipe flow, the authors' explain:

The resulting time difference is proportional to the fluid velocity passing through the meter spool. Single and multiple acoustic paths can be used to measure fluid velocity. Multipath meters tend to be more accurate since they collect velocity information at several points in the flow profile.

Now back to the story... after the installation of an ultrasonic flow meter, the refiners saw that the meter was reporting low flow rates when the product in the pipe switched between gasoline and diesel.

The local Daniel service technicians collected maintenance logs using their Customer Ultrasonic Interface software (CUI) and sent it to the support team in Houston for detailed analysis. The team verified that the meter was working correctly for both liquids. They deduced that the flow was being diverted somehow during the transmix, or product switchover, where both products are flowing through the pipe until the switchover has been completed. This was possible because of the meters ability to accurately measure both flow rate and speed of sound of the liquid passing through the meter with extremely high accuracy.

The refiner verified that this is what indeed was happening where this transmix was being routed away through a smaller pipeline for further reprocessing. With the age of the refinery and the retirement of experienced operators, the current operators had not been able to see this transmix operation occurring in their process. The refinery engineers were impressed that the team in Houston could deduce this from their analysis of the data.

The refinery engineers involved in this project are presenting a workshop at this year's Emerson Exchange in late September. If you face similar challenges, you might want to catch this one.

I've written about terminal and offsites operations a few times in the past. I had a chance to catch a presentation given by Emerson's Shoyeb Hasanali, who leads the terminal management solutions team.

Shoyeb began by giving us a good grounding on terminal operations. These facilities provide receiving, shipping and storage facilities for liquid or gaseous products processed by or produced in a refinery or petrochemical complex. These sites typically include tank farms, blenders and loading and unloading facilities. The loading and unloading facilities may handle truck, rail, marine or pipeline transport of these liquid and gaseous products.

Some of the issues terminal operators currently face is a lack of spare capacity to handle additional bulk products, increasing safety, environmental and regulatory compliance requirements, and an increasing number of product variations.

The rapid price increase in refined products has caused a shift in the movement patterns and logistics in the transportation of these products. The automation and information systems within existing terminals were not designed for the current economic climate and rapid changes in spot prices. Terminal operators often have disparate automation systems for custody transfer, loading/unloading, blending, vapor recovery and other units.

Shoyeb and his team of terminal management solution consultants work with terminal operators to provide front end engineering design (FEED) to identify the opportunities to improve the flow of accurate and timely information required in rapidly-changing price world.

The FEED study is typically followed by functional designs, functional requirements and factory acceptance testing for the hardware and software used in the solution. Much of the technologies for these solutions come from various businesses within Emerson Process Management. These include Saab Rosemount tank gauging, Daniel custody transfer, metering skids, loading rack presets, Micro Motion flow and density measurement, METCO metering services and DeltaV blend control.

The team has delivered projects all over the world on products including gasoline, diesel, jet fuel, asphalt, fuel oil, lube oils, chemicals, fertilizers, liquefied petroleum gas, liquefied natural gas and specialty chemical products.

Those of us with teenage kids, or memories of their kids as teenagers, or even what we were like as teenagers may recall the question, "Why do I have to learn ____ if I'll never have to use it?" This is very fresh in my mind because I had that very conversation the other night. The blank in this case was chemistry. My point was that you really have no way of knowing what you'll need to know so you might as well learn it.

Well today, I'm reading an article from the August edition of Hydrocarbon Processing magazine written by Air Product and Chemical's Win Hoglen and Emerson's Julie Valentine, a member of the Micro Motion business. The article, Coriolis flowmeters improve hydrogen production describes how accurate steam-to-carbon ratio control improves efficiency in a reforming hydrogen plant located within a refinery. The article explores the chemistry in the reforming process converting the light hydrocarbons (methane, ethane, propane, butane) and water (in a superheated steam state) into hydrogen and carbon monoxide. A shift reaction then converts the carbon monoxide and water into carbon dioxide and hydrogen.

For those not in the refining industry, this hydrogen is needed to scrub the sulfur out of gasoline and diesel to meet the clean fuels regulations that countries around the globe have adopted. The sulfur reacts with the hydrogen to make hydrogen sulfide and then it is further processed into elemental sulfur.

The thrust of the article is not the chemistry lesson I just described, but the challenges to most efficiently produce this hydrogen. A major challenge is the chemical composition of the natural gas since:

...the amount of steam required for the reforming reaction can vary widely depending upon the number of carbon atoms per molecule of the gas (i.e., one molecule of steam is required for each carbon atom, but there can be from one to four atoms).

Traditionally, volumetric flow measurements were used which usually involved differential pressure measurement and gas chromatograph or mass spectrometer analysis. Calculations determine the actual mass flow (carbon mole flow.) Errors in the carbon mole flow result from errors in the volumetric flow when the composition changes. Also, this analytical equipment requires regular maintenance and steam flow must be increased to handle any spikes in carbon mole flow during this maintenance period.

There are problems with both too much and too little steam flow. Too little reduces catalyst life, and production instability that may lead to a costly plant shutdown. Too much steam wastes energy and may require additional capital investments for more steam capacity. The measurement and control challenge is maintaining a constant steam-to-carbon ratio.

Coriolis flowmeters, through the Coriolis effect, measure actual mass flow very accurately and require less maintenance. The drawback is that the mass flow measurement cannot distinguish impurities like nitrogen and carbon dioxide in the natural gas supply.

The article describes testing done where methane concentration ranged between 78% and 89% and ethane between 7% and 15%. Maximum variation in the steam-to-carbon ratio was 0.02 units of steam, much better than the 0.2 in the traditional measurement method. The percentages of nitrogen and carbon dioxide were relatively stable.

From the testing done at various Air Products and Chemical facilities, Micro Motion Coriolis flowmeters are well suited for a natural gas stream that has relatively fixed percentages of inert gases or nitrogen concentrations that do not vary outside of 3% less than design.

A final note, I forwarded this article on to my teenagers to demonstrate the point that one never knows when one might need to know something learned in one's past.

I'm catching the session, Realized Benefits from Foundation Fieldbus at the ISA Expo 2007. ARC Advisory Group's Larry O'Brien moderated the session.

The first part of the session looked at BP's use of Foundation Fieldbus (FF) in an onshore oil & gas production SCADA application in the U.S. state of Wyoming. They tested various suppliers systems and field devices in the harsh Canadian winter environment to compare the robustness of the various FF offerings. At each well site of eight wells, control was run in the FF devices, which in turn were connected, into their remote terminal units (RTUs). They saw immediate project savings in the wiring/installation labor/physical footprint savings. A key benefit they saw was remote diagnostics into these devices from a central location.

Next Suncor Firebag shared their Foundation fieldbus experiences. Suncor has standardized on Foundation fieldbus for all capital projects. Firebag has 9-10 billion barrels of reserves using today's extraction technologies. The extraction efficiency is expected to increase over time and these known reserves will increase. Suncor documented commissioning savings of Foundation fieldbus versus conventional devices of one sixth of the time. The benefits cited included faster time to first oil, and instrumentation maintenance practices moved from preventive to predictive. This helps eliminate unnecessary maintenance and avoid unplanned shutdowns.

They are currently looking at applying the statistical processing from the high-speed history in the FF devices to detect flame flutter on furnace and boiler flames. Another application they are investigating again with this high-speed sampled data is early detection of water hammer conditions in piping. This condition can cause millions of dollars in damage to the pipes if it is unchecked.

Emerson's Marcos Peluso gave a quick overview of the case for control in the field and robustness as measured by mean-time-between-failure. The key is the communications path is shorter when the control loop executes between a sensor and final control element than when it is between a sensor, automation system controller, and final control element. The loop can also execute with more certainty with the execution times of the fieldbus segment. Marcos indicated that the application should determine whether control is run in the automation system controller or in the FF device. There are strengths to each approach.

EnCana next presented how they could get gas compressor stations up and running more quickly with Foundation fieldbus devices than with conventional field devices. For their installations, all control was run in the field devices. This designed proved helpful in avoiding lost production when batteries did not hold their charge from solar panels. The remote terminal units and wireless network transmitters dropped out when the battery voltage dropped, but the FF devices kept running. Operators drove to site after they lost communications but found the compressors continuing to run with the loops fully in control. Overall, they we able to reduce operating expenses by linking together their remote compressor stations by centralizing the operators window into their decentralized control. Troubleshooting could be done remotely which reduced downtime.

Finally, Shell briefly shared their Foundation fieldbus experiences. While they agreed with the project savings others had experienced, they saw the biggest value in moving from preventive to proactive maintenance. They recommended this is where process manufacturers should spend the bulk of their planning efforts. This process often involves a cultural change so it takes time and quite a bit of planning and execution. Their approach is to have focused resources continually reviewing the diagnostics from intelligent field devices and performing maintenance based on this information. They cited savings in the millions of dollars from shifting to this approach.

I've highlighted the topic of plant turnarounds (planned downtime for maintenance) a few times in the past. Back from the Emerson Exchange, here's my take on the Smart Turnaround workshop. For continuous processes that run for years, this turnaround provides opportunity to update, fix, repair, and replace a host of plant assets including instruments, valves, electrical distribution equipment, connectors and cabling, and the overall performance of the process.

The Emerson presenters looked at the advanced planning that can be done from these various perspectives. From these diverse areas of expertise, diagnostic testing helps develop a turnaround plan that prioritizes critical asset work, defines the scope of work, develops the schedule for the work, and identifies the parts and people required to best get this difficult work done.

Chris Forland an operations consultant whose work I've highlighted in earlier posts kicked off the session discussing some of the challenges of the turnaround process. A big one is finding problems you didn't expect while in the turnaround. These unexpected problems cause extra charges and delays. Chris discussed ways that Emerson turnaround specialists can help with the detailed planning to make sure the work is efficiently performed during the turnaround. He noted that less time to plan mean less flexibility as the turnaround date approaches. Other challenges included maintaining compliance with safety and regulatory compliance, working with budget constraints, reducing process variability, losing experienced personnel due to infrequency of turnarounds, and pressuring of short turnarounds due to sold out condition of produced product.

Scott Grunwald, a turnaround business manager in the Instrument & Valve Services business, recommended that with the valves and instruments, you start by building the plan based on the benefits to be achieved the roles of all participants in the maintenance activities, and the prioritized list of activities and anticipated timelines. The process starts with a walk down of the facility. Next, FlowScanner is used to measure internal valve conditions to identify problems to address during the turnaround. When it's time for executing the turnaround, only valves needing significant work are removed. Other valves are repaired in place.

The team often brings an on-sight mobile trailer that is a self-contained workshop to rework the instrument and valves right on-site. This helps to expedite the repair process.

Looking at turnarounds from an electrical reliability perspective, Steve Metzger described the goal--to prioritize and focus the resources by pre-diagnosing troubleshooting, followed by the planning of the repair services and parts required to get the lead times properly. The key is to do as much pre-work as possible, fix what's possible, and remove it from the scope of the turnaround to lessen the pile of work to be done.

On-line partial discharge testing before the turnaround detects cables with degrading insulation that could cause short circuits and unexpected downtime. This testing helps determine which cables are OK and which need to be replaced during the turnaround.

James Beall, also highlighted in earlier posts, summed up the goal of a Smart Turnaround--to identify the items you can fix in advance, and prioritize what can't be in the turnaround plan. James and the variability management consultants look at the control performance and opportunities to reduce process variability through better tuning. James gave an example of a mixing temperature control loop where the deadtime was nine minutes between a change in setpoint and response the temperature was changing. The problem was not in the loop tuning but rather in the lag caused by the temperature transmitter being located 250 feet from where it should have been. Finding this early in the process allowed this installation mistake to be scheduled and fixed during the turnaround.

Chris closed this presentation with how you can look at the return on investment to help justify the experts required to make the planning and execution of the turnaround a success. It's a bit of a chicken and egg scenario since you don't know what type of ROI this turnaround planning can create without having the experts come in to begin the process of identifying improvement opportunities.

Chris has developed a model based on turnaround experience with typical costs from each of the aspects of turnaround planning and typical costs for the maintenance activities. This model is in an excel spreadsheets so that the assumptions can be easily changed to fit the unique aspects of each process manufacturer. Both cost avoidance and increased revenue from improved plant performance is calculated, each based on the size of the process and amount of equipment considered.

By taking a comprehensive planning approach, and getting an early start, turnarounds do not have to cause quite the number of gray hairs that they have traditionally been known to cause.

Update: Mitzi Amon, director of marketing for Emerson Electrical Reliability Services team adds that the prioritization is accomplished by performing online diagnostic testing prior to the turnaround to determine what electrical equipment needs to be serviced during the turnaround. This helps clearly define maintenance work scope during the turnaround and what can be done prior to the the turnaround.

A colleague pointed me to an article, Timeline of a refinery pump failure and how it could have been prevented, on the Belgium-based EngineeringNet.be website. The story was about a South American refinery that had a high-speed centrifugal pump fail catastrophically resulting in production losses and large repair costs. Todd Reeves is in Emerson's Machinery Health Management team, part of the Asset Optimization organization.

What happened was an inboard bearing lost lubrication, overheated and finally seized up. The unfortunate part of the story is an automated motor-pump train monitor and advanced vibration analysis system had been installed four months earlier and was working properly.

This monitoring equipment included the CSI 9210 Machinery Health Transmitter connected to the automation system via Foundation fieldbus. This equipment did its job communicating advisory alarms it began to detect problems in the lubrication system.

These alerts went unheeded until they became maintenance alerts and ultimately failure alerts. Todd wrote that the health curve of the pump deteriorated rapidly in the final ten minutes before failure.

Why? The equipment did its job and dutifully reported the problem. The issue turned out to be more of overall unit tuning and alarm management issues. These alerts had been lost among other alarms coming in.

Working as a team, the refinery and local asset optimization experts reviewed the overall alarm strategy and identified opportunities to reduce the alarms and alerts coming in to the operators.

Specifically for the pumps, a best practice was established to add additional temperature measurements on the pump. Training was established to clarify how these alerts would be transitioned between the operators and maintenance staff. Clarifying this process is important when working with predictive diagnostics. At the time, it is not yet an actual problem--but like this centrifugal pump example--will fail if not addressed.

Last October, I featured one of Emerson's advanced automation service consultants, Lou Heavner, and how he worked with Lukoil to create virtual sensors based on neural networks.

Their efforts were told in more detail in the March 2007 issue of InTech magazine. The article, entitled, Crude gets smart, described the Russian refiner's challenge to keep their refined products within specification. They had been relying on lab samples that came back from the lab to the operators only once or twice a day.

To get feedback on product quality and composition more frequently, Lou and the team used neural network blocks in their DeltaV system's controllers to create property estimators. As the article states:

The goal of a property estimator is to provide an accurate gauge of product quality, especially after lab results have become stale, which is most of the time. Property estimators are not intended to eliminate lab analyses, although the frequency of analyses may lessen once estimators are proven. Even though estimators may not be as accurate as lab analyses, they can be worthwhile calculated variables to help engineering and operations personnel monitor, troubleshoot, or understand and control the process.

The article describes the steps the team took to collect the data to train the neural network models. It offers guidance for those looking to implement property estimators. Some examples of their recommendations include:

• The time stamp should reflect the time of data extraction from the process--not when it was scheduled for sampling, or when the lab technician performed the analysis, or when they reported the lab results.
• Avoid filtering or manipulating the process data. Raw snapshot data usually makes for the best models.
• If the process does not vary much, the model will not be reliable if the process wanders into a range with no collected data... the model will be changed to "Uncertain" and the operator can be alerted.

The team believes they may have one of the world's largest installations in terms of neural network models. Currently operating models include ones measuring boiling points, flash points and viscosity on the pre-flash, atmospheric, and vacuum towers.

If operators at your plant are waiting on lab information to make quality adjustments to the process, you may have a business case for creating property estimators to augment the lab sampling process.

In an earlier post about fired heater efficiency and reliability, I had spoken with Emerson operations consultant, Chris Forland, on the opportunities for refiners to optimize this energy intensive unit.

Working with engineers in the Rosemount Analytical Gas division, Chris has developed a spreadsheet with fired heater efficiency economic calculations which allows refiners to get a rough estimate of the potential value in applying efficiency solutions like the SmartProcess Heater Optimizer.

You can enter data in the cells with blue text for each fired heater in your plant to get a quick assessment. Chris has filled in typical values from a cross section of refineries in case you don't have exact data. This will let you get a feeling for the overall improvement opportunity and if there is enough return on investment to warrant a closer look.

If you have fired heater units in your manufacturing process, give this calculator a try and let us know what you think by adding a comment or contacting us.

Emerson's Lou Heavner, a consultant on the Advanced Automation Services team, recently co-authored a paper, Using Neural Network Technology for Virtual Sensing in Crude Refining Units, at the recent ISA EXPO 2006. Lou worked with engineers from Russian oil refiner, Lukoil.

Always a great presenter, Lou not only shared his expertise on this project, but the fact he homebrews beer. I imagine this keeps his control application skills honed!

The paper describes the need to improve quality of refined products to improve upon the current process of taking lab samples once or twice a day. The operators would make changes to the process based upon the lab readings. They tried to control key temperatures and other process variables on the pre-flash, atmospheric, and vacuum columns by manipulating flows including reflux, furnace fuel, pump-arounds and product draws.

To make these quality adjustments more in real-time, the refinery engineers want to use something other than costly and maintenance-prone on-line analyzers. They decided to use neural network technology to build real-time inferential property estimators which could run inside the refinery's existing DeltaV controllers.

Lou work with the Lukoil engineers to build ten artificial neural networks measuring gasoline, kerosene, diesel, VGO, and residue on the pre-flash, atmospheric, and vacuum towers. They believe this application of virtual sensors to be one of the world's largest on a single crude unit.

The real work comes in collecting the data needed to train the neural networks. They needed around 100 lab samples for each model and the continuous historical data for process variables over this sample period. The DeltaV Neural software helped automatically perform the data collection and model training need to build and prove the neural networks. Up to 20 process variables were collected as inputs in training each of the ten neural networks. Any abnormal operating conditions were identifies to exclude the data from this time period from the model. Any of the variables that had little or no effect on the model outputs were eliminated.

The largest challenge in the data collection effort was in the lab data. It had to be accurate in terms of precise time of taken sample and the proper analysis of the sample. The quality of the neural networks is directly impacted by the accuracy of the samples. Another important factor is to make sure the process data is not filtered or manipulated, but instead a raw snapshot.

The resulting inferential sensors predicted what the lab results showed within a few degrees. The ones estimating lighter refined products were more accurate. The engineers have not closed the loop to run the control strategies based on these readings, but they do present the information to the operators to make adjustments more frequently then they could with samples coming only once or twice a day.

From my days as a young systems engineer working on offshore oil & gas platforms in the Gulf of Mexico, I know that abnormal situations in our processes are something we all wish to avoid. A 1999 study by the ASM consortium estimated $10 billion USD in losses for U.S. process manufacturers due to abnormal situations. The question is how best to prevent these abnormal situations from occurring in the first place.

Emerson's Ravi Kant and Roger Pihlaja recently presented a paper, "Abnormal Situation Prevention (ASP) in Complex Systems" at the recent NPRA Q&A and Technology Forum.

In their presentation they stress that the potential severity and cost of an incident increases if timely corrective action is not taken. An example cited from a refinery abnormal situation is the failure of a butterfly valve. After going several hours without detection by the automation system or operations personnel, it caused the Cat Cracker (FCCU) to shut down. In a matter of minutes this caused the refinery to shutdown, resulting in more that $1 million USD per day in lost revenue.

Ravi and Roger explained how abnormal situation prevention (ASP) technology embedded in the sensors, actuations, and machinery health are closest to the process and have access to better information. This ASP technology can predict root causes of abnormal situations through high-frequency spectral and statistical data analysis within these smart devices. The main reason for doing this analysis closest to the process is that the sampling frequency is greater--22 samples per second, instead of 1 sample per second to 1 sample per minute typical at the automation system level.

Data analysis at this higher frequency can uncover process anomalies including drift, bias, excessive noise, process spikes, and plugged conditions. Some of the detection and prediction algorithms and techniques which are employed include: polynomial extensible regression, principal component analysis, statistical process control, decision trees, fuzzy logic, and neural networks.

They cited some specific ASP applications in refineries including early detection of catalyst losses, catalyst circulation issues, afterburn conditions, column and heater coking, temperature runaway, and acid levels outside optimal or safe levels. The key to detecting these process conditions is sharing this data analysis at from the field device level, up through the equipment level, up through the process unit level to the operators and plant maintenance staff. Digital communications technologies like Foundation fieldbus and HART provide the information path.

Roger also shared with me other high-frequency data dependant ASP applications in the process including:

• Plugged impulse line detection for DP flow transmitters
• Flame instability
• Stick/slip in FCC solids transfer lines
• Stirred tank vessel agitator diagnostics
• Continuous rotary drum vacuum filter diagnostics
• Fouling & DP level transmitter plugging in evaporators
• Detection of developing ASP issues like arching, bridging, & rat-holing in bulk solids storage vessels
• In-situ proof testing of emergency relief systems

Work continues to refine and extend these predictive ASP technologies to more smart field devices to increase the "eyes and ears" on the process in order to avoid the costs and losses associated with abnormal situations.

In an earlier blending applications post, I mentioned some of the advantages of online/inline blending over traditional, batch-based blending. It's a process which crosses many industries including refining, pulp and paper, chemicals/specialty chemicals and food and beverage to name a few.

I came across an article, Optimizing blending operations by Julie Valentine, a refining specialist in Emerson's Micro Motion division. Julie notes that for refiners, the motivation for changes to the blend process are in improved control, improved measurement, improved analyzers and improved optimization techniques. One of the keys is high performance flow measurements of the raw materials to precisely control their flow rate as they are blended together. The Micro Motion Coriolis flow meters are extensively used for both the raw material and final blending product flow measurement. Their 0.1% accuracy couple embedded advanced control in control systems like the DeltaV system, enable blend optimization to be done within the control system.

In the article, Julie describes a U.K. lube blending plant which switched from a sequential measurement system to a flow measurement based system. This switch enabled the raw materials to simultaneously flow into the mixing tanks, increasing the throughput of the operation. The accurate measurement of the raw materials meant that the blend would be on-spec as it was filling in the mix tank, and shortened the overall mix cycle, again increasing throughput.

The Coriolis meters also provide high accuracy density measurements, which was important since blend component pipe headers are cross connected and this density measurement can quickly spot and notify operators of cross contamination which can affect the quality of the blend.

One other example Julie cites is where the blending optimization for the blend of gasoline allows refineries to make use of the blend components available from production and choose the blend which will produce the required specification at the lowest cost, while also managing inventory levels.

The accuracy of the flow measurement is critical to the blend optimizer. Julie cites a study where poor flow measurement with 0.3% accuracy translates into lost profitability of up to $200,000 per year for a 100,000BPD facility. This is caused by the blend optimizer making the wrong optimization decisions based upon the inaccurate data it receives.

As blogs have brought self-publishing to individuals and their growth has skyrocketed, the next wave--self-published videos--have arrived and even come to our conservative world of process automation.

YouTube and Google Video are two examples of sites where you can upload your videos to share with the world.

I bring this up because I received an email this morning of a video done by Pennsylvania Cable Network with their PCN Tours series. The 52:35 video features a tour of American Refining Group in Bradford, Pennsylvania in the U.S. They are celebrating 125 years as the United States longest continuously operated refinery.

Take a look at 17:45 and 20:15 and you'll see Emerson's DeltaV system in their crude unit control room and reformer control room. It's great that PlantWeb technology could play a role in their success.

As we continue to move forward in this new age of communications, please let me know if your process automation work is highlighted in one of these newer self-publishing mediums like blogs, podcasts, or videos.

Many process manufacturers have flow metering stations where ownership of incoming raw materials, intermediates, and/or outgoing products change. This custody transfer process is common with oil and gas producers, refiners, and chemical/petrochemical manufacturers.

Accuracy is critical since these measurements impact the bottom lines for both the seller and buyer. And, with the introduction in the U. S. of the Sarbanes-Oxley (SOX) Act of 2002, companies are required to put the controls in place to prove the accuracy of these measurements. Other countries have similar regulations requiring these documented proof-of-accuracy processes.

Robert Fallwell, a regional manager in Emerson's Metco Services business, has written an excellent article, Sarbanes-Oxley audits: coming soon in the July issue of Control Engineering magazine.

Robert shares his expertise on how process manufacturers need to prepare for the SOX auditors. He boils it down to:

...they ask for proof that flow measurements are accurate, that you have procedures to ensure measurement accuracy, and that the plant's operators, engineers, and production accountants have been trained in the correct procedures for the measurement control process.

If your business is impacted by SOX or similar regulations, you'll want to incorporate some of the ideas presented in this article.

As I mentioned in an earlier post on fired heaters in refineries, this is an area where refiners can reduce energy costs by modernizing and optimizing the performance of these units.

The objective is to operate the heater at the lowest fuel cost, while being able to reliably handle the variability in fuel quality and BTU content for any waste fuels used by the heater. Many of these units operating in established markets around the globe are 20 to 30 years old and these often experience unplanned outages due to component failure. Another challenge is the tube coking / fouling in the units which can reduce operating efficiency.

Every 3-5% improvement in fired heater efficiency can mean 3 to 5 cents per barrel net margin improvement. For a 100kbpd facility, this translates into $1.8 to $2.9 million USD in annual savings.

I spoke with Chris Forland, an operations consultant for the Emerson Process Management group. Chris and the other consultants have helped refiners identify several ways to improve the efficiency and reliability of their fired heaters.

It starts with a study to baseline the performance and to confirm the operating issues impacting performance. This study helps to identify opportunities for improvement and to provide estimated costs and benefits to determine return on investment for the improvement initiative.

Beyond the SmartProcess Heater Optimizer mentioned in the earlier post, some typical opportunities Chris sees for improvement include on-line continuous measurement of fuel quality and BTU content, in-situ measurement of oxygen and carbon monoxide in the exhaust stack, predictive diagnostics for the smart instrumentation, digital valve controller actuator for the damper drives and control valves, and predictive measurements around the flame and relative coking.

These projects usually include a post project audit to determine the actual return on investment versus that forecasted one in the front-end study. This provides a measurement for the success of the project by determining the actual return on investment.

Recently an email came in that said Refineries and Petrochemicals specialist, Ravi Kant, and ASP Validation and Verification Engineer, Ahmad Hamad, in our Performance Technologies division, won the Fuels & Petrochemical's Award for best paper (out of more than 80 papers) at the AIChE 2006 Spring National Meeting.

This was something I had to get my hands on and find out why, and extend hearty congratulations to Ahmad and Ravi. The predictive PlantWeb technologies developed by this team find their way into AMS Suite software products, Rosemount transmitters, and other Emerson smart field devices.

With many industries like refining and petrochemicals running near full capacity, abnormal situation prevention provides a method for early detection with problems in the process and provides an opportunity for timely corrective action--before down time, quality issues, or even safety issues occur.

The paper, Advances in Abnormal Situation Prevention in Refineries and Petrochemical Plants, looks at traditional ways of preventive maintenance and the drawbacks in performing unnecessary maintenance, sometimes requiring down time, and being unable to detect abnormal situations.

It also explores other techniques for abnormal situation management. These solutions use knowledge-based diagnostics with data drawn from the continuous historian to develop a multivariate model. The source data from the historian is typically very low frequency from once per second to once per minute. This approach fails to detect abnormal situation which can develop rapidly. It also often fails to find problems with machinery, devices, and transmitters in the process. An example might be a stuck valve.

Ahmad and Ravi describe how advances in microprocessor performance and digital communications like Foundation Fieldbus and HART make it possible to do high frequency diagnostics within smart field devices. Emerson Process Management has developed Abnormal Situation Prevention (ASP) blocks in smart field devices like Rosemount 3051s transmitter, which capture high frequency process data at 22 samples per second. The blocks perform statistical, frequency-based, auto-regression, wavelets and other diagnostic measures to try to discover problems in the process in their earliest stage. And automation systems like the DeltaV and Ovation systems can turn the most critical of these alerts from these ASP blocks into operator and maintenance alarms for corrective action to begin.

The paper describes for cases where this early detection can prevent abnormal situations from occurring. These include: coke detection in refineries, catalyst circulation in fluid catalytic cracking (FCC) units, maltrays detection in crude columns, and gas turbine abnormalities. These are but a few of the critical applications where abnormal situation prevention technology can be applied.

Like anything else, the closer you can get to the source of the abnormal situation, and the earlier you can identify it, the sooner you can mitigate or prevent the situation from occurring.

You don't have to look too hard to find news stories (here, here, here) of rising oil prices and their impact on process manufacturers around the globe.

Refineries and petrochemical manufacturing processes can especially require vast amounts of energy to process the feedstocks into intermediate or final products.

I spoke recently with Doug White, who leads our advanced automation services consultants for Emerson Process Management. Some of the folks I've written about like James, Eric, and Lou are senior consultants in Doug's organization.

Doug mentioned that one of the units at which refiners and petrochemical manufacturers should take a close look is the fired heater which provides the required heat for the distillation process. In many plants, these units were built 10-15 years ago or more. Most were built in times when natural gas was extremely inexpensive. There was little need for energy efficient designs--so even today they consume energy at higher rates than they could.

He sees these units as a quick way for manufacturers to save costs and improve their bottom lines.

Doug described these opportunities and gives very practical advice on how to get the project assessed, implemented, and sustained in an Oil & Gas Journal article entitled: Advanced automation technology reduces refinery energy costs. Some steps Doug recommends from the assessment phase:

1. Data gathering. Compile information about existing systems.
2. Interviews with plant staff. Find current energy-use problem areas, understand current operational procedures, and stimulate ideas on possible changes.
3. Evaluation of plant energy economics. Understand what are the major users and their costs of operation.

If you are one of the manufacturers struggling with higher energy costs, this article is well worth the read to develop a plan to reduce these high energy costs.

Update: Repaired broken hyperlinks.

One of the guys who has been around as long as I have is Lou Heavner, a Consultant in our Advanced Applied Technologies team. As an MIT graduate, he is one really sharp person, and also someone who can simplify and communicate complex ideas.

I asked Lou about what he's been working on recently in the world of applying advanced process controls for process manufacturers. Lou's been recently involved in a project in the European region where he consulted with a refiner to get DeltaV PredictPro working on a crude unit and to take advantage of its optimization capabilities.

During that project, it became clear to Lou that the term optimization conjures up a different vision for most people. He was confronted with matching the capabilities of the system to the expectations of the customer and needed to dive pretty deeply into how optimization works in the DeltaV software, just to explain and train the local refinery staff.

The crude unit is the first unit in a refinery and the fractionator is a great place to start applying APC technology. An optimizer can take advantage of the capabilities of PredictPro and the extra degrees of freedom in a typical crude unit to drive the process to maximum throughput and/or minimize the energy required (as fuel in the fired heaters.) It can also support an objective to maximize yield of the more valuable cuts (products). The system is working and delivering benefits, but Lou is doing further work to quantify the results and turn this skeptical refiner into a good reference site.

Applications like these have been developed for many industries and branded as SmartProcess Optimization application packages. Some of these applications for refineries include the Fractionator Optimizer and the Heater Optimizer packages.

As one who applies the advanced process control software on a regular basis, Lou's feedback to the Emerson technology development teams has enhanced the software over a number of releases.

Lou is a regular presenter at the Emerson Exchange sharing his expertise with the Emerson customers who attend. This year he'll be presenting a short course which explains how to implement optimization with DeltaV PredictPro and surveys several optimization techniques including non-linear searches for minima, load allocation, and LP (linear programming) solutions. These optimization techniques are a key and inseparable part of those who employ use model predictive control techniques.

I heard a story of a tremendous effort from our advanced applied technology experts to help a refiner stabilize his units after a restart. I went to the source, James Beall who is the team leader of our U.S. Control Performance team. It turns out that he is the one responsible for these successful efforts.

He received a call from one of our local business partners late on a recent Wednesday night to assist this U.S. based refiner with the startup of some of their units including three new distillation columns. This refiner had battled the startup for several days but could not stabilize the unit or produce on-spec product. The unit would have to be shut down within 48 hours due to limited storage if stable operation and in-spec product could not be achieved.

James arrived early Thursday morning and began to assess the situation. He installed Emerson's EnTech Toolkit to be used for process control diagnostics, complex loop dynamics identification and advanced loop tuning. He reviewed the situation with the customer, prioritized and set the order of tuning of the control loops around the columns. Using DeltaV Tune and the EnTech Toolkit to provide coordinated loop tuning, the columns were stabilized by 10:30 pm, 12 hours after arriving on-site.

During this process, several measurement problems were identified and plant personnel began to troubleshoot and correct the problems. Once these instrumentation problems were resolved within a few days, James returned to the site to continue the control performance improvements.

The quantified results? The columns achieved 100% of design production 5 days after James first arrived and nearly another 20% after a total of 7 days.

Based on these results, the refiner is looking to set up a continual process performance improvements program with James and the Control Performance team.

A recent post on Control.com's global on-line community for automation professionals asked about how to go from pneumatics to a process automation system in a refinery.

Given the strong global demand for refined products, refineries want to avoid any downtime when modernizing their automation and safety instrumented system technologies. This process of cutting over from old to new while the process is running is called a Hot Cutover.

Ken Suetterlin, a senior Emerson Project Manager from our Refining and Chemical Industry organization responded to the Control.com post with the following recommendations:

1. Identify which loops are to be converted as Hot Cutover and which are to be done during Turnaround. If possible, we recommend you convert loops related to safety shutdowns during Turnaround. The loops in each category can be color coded on P&IDs and/or indicated by category in an instrument database. Then you can sort by Hot Cutover and get a list of all loops in that category.

2. Once you have a list you'll want to work closely with Operations to schedule the loops based on production priorities and loop complexity.

3. Install and test as much as possible in advance to avoid last minute surprises.

Upfront planning is critical to avoid downtime. In a Shell Deer Park refinery modernization project, Emerson supplied all phases of engineering services related to Hot Cutover including conceptual design, FEED (Front End Engineering Design), detail design, FAT (Factory Acceptance Test), field commissioning, SIT (System Integration Test), SAT (Site Acceptance Test), and installation. The team worked closely with installation contractors, and provided the engineers and technicians for actual cutover.

The Hot Cutover process at the Shell Deer Park refinery which included critical units like the Cat Cracker is described in an April Hydrocarbon Processing article.

Here is a description of some of the expertise and technologies Emerson applies in a Hot Cutover project.