Emerson Process Experts

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Batch process manufacturers have long understood that applications which require both sequential and continuous control have been a challenge. A typical example is a centrifuge application commonly found in Biotech and Pharmaceutical manufacturing processes. A centrifuge separates solid and liquid material by spinning a sieve-like device at high rate of speed, and recovering the liquid, solid or both materials.

I caught up with Brian Crandall, a Life Sciences industry project engineer. He said that proper control was critical since centrifuges are quite expensive, and sensitive to a variety of failure conditions. These conditions need to be addressed within seconds to prevent equipment damage and possible injury to operations staff.

Brian summed up the control challenge as the centrifuge having various operational states. Moving between these states is best done using sequential operations. However, monitoring of the failure conditions, which change in severity and action depending upon the operational state, must be done in parallel with the sequencing.

If a failure condition occurs, the current sequence has to be stopped, and the specific failure sequence started within a minimum timeframe. The S88 Batch Model defines a sequential state driven approach, but it does not fit the requirements of this application. The big issue is the failure monitor does not offer continuous monitoring required for quick reaction to the failure condition.

Using a DeltaV system for this particular Biotech application, Brian designed, tested and implemented a modified S88 state model that had the ability to stop a sequence without waiting for a transition thus meeting the high-speed timing requirements of the equipment. Multiple sequences would be required for the main sequence, shutdown, and E-Stop to allow stopping one sequence and starting another at the same time. Also the code design needed to modular to fit the rest of the S88 modular design philosophy. Also, this design placed control at correct level in S88 batch model, at the equipment module level.

Some failure conditions the design addressed included: high vibration, VSD fault, low seal water pressure, and low instrument air pressure. Depending on the state of operation, the failure conditions required different actions per a failure condition matrix.

Other industries have applications requiring this mix of continuous and sequential control. Some examples include a refiner in the pulp and paper industry, extruders in the specialty chemicals industry, and other state-driven processes or equipment.

Tags: S88 | ISA-88 | centrifuge control | continuous control | sequential control | control strategy | project execution |

May 26, 2006 in Control Strategies, in Life Sciences, in Project Services | Comments (0) | Trackback (1)

I caught up with Lou Heavner who you may remember from an earlier model predictive control post. When it comes to blending operations in refineries, Lou knows this application very well.

He’s recently created a Blend Lite application which is a scaled down version of the Blender Control application that has been developed and deployed for numerous refiners around the world.

The full blend control application has in-line blending which offers several advantages over sequential blending, especially in the reduced time required to blend large volumes. Some products like gasoline involve many components and the finished product must meet many specifications. The standard blending package addresses the many component/many spec problem and frequently includes the use of an in-line analyzer and blend optimization.

There are a number of blending applications that involve only a few components and don’t require all of the advanced functionality that is usually required for gasoline blending. Refineries have some products that fit this simpler application like jet fuel and asphalt. Other industries have processes that fit this simpler blend application. The key value in these applications is the ability to simultaneously blend multiple components--all in the correct ratio--even if one of them becomes constrained. These simpler blend applications still need functions such as: blend recipes, start/stop sequencing, failure monitor, ratio controllers, ramping and pacing.

Lou said to consider the Blend Lite Package if your application has the following:
- In-line blending for up to 5 components with one flowmeter and control valve per component
- Ratio control of current flows or totalized flows with pacing during the blend and ramping at the beginning and end of blend
- Up to 32 blend recipes
- Blend reports
- Start/stop capability for one valve and pump per component
- Basic operator graphics like those provided for the Blend Package

Tags: blend | refining | recipe |

May 25, 2006 in Process Optimization | Comments (0) | Trackback (0)

In AutomationWorld magazine Editor-in-Chief Gary Mintchell's recent blog post, Safety Integrated System training, he describes an SIS training course recommended by a former colleague.

I caught up with Pat Garland in Emerson's Educational Services organization to see what training we were offering to help automation professionals learn the ins and outs of the safety including the global safety standard IEC 61511 (ISA S84 in the U.S.)

Along with a lot of efforts in other parts of Emerson Process Management developing safety instrumented system (SIS) products, SIS project services, and ongoing SIS lifecyle services, the Educational Services team has developed courses around safety from basic understanding of terminology and global standards to more specific product training.

Pat specifically pointed me to some on-line eLearning courses which include a Safety Engineering Overview and a more in depth Safety Engineering course. You can see sample courseware here (requires Flash player.)

These are paid for classes but include access to the course for three months and email access to Emerson safety experts for this three month duration. Based upon the feedback of automation professionals who have participated in the various forms of education services, many more eLearning modules are in development.

Pat has posted his email on the eLearning page, so fire away if you have questions or post comments here.

Finally, speaking of commitment to education, it was great to read Control magazine Editor-in-Chief Walt Boye's blog post today, More on "Being the Solution..."

Emerson Process Management is the undisputed king of giving to colleges, universities and technical trade schools, as near as I can tell. They have donated millions of dollars worth of field instruments and DeltaV systems, or sold them to academic institutions at cost, depending on the need of the particular institution. In particular, they've donated to the three North American Fieldbus education centers a whole lot.

What Emerson does is the template for the first way to expend education resources: support actual engineering education. This must be done. Thank you for being part of the solution. Please don't stop.

Tags: safety instrumented system | IEC 61511 | S84 | SIS training |

May 19, 2006 in Education, in Safety | Comments (1) | Trackback (1)

S88, short for ANSI/ISA-88 is a standard for addressing batch process control. This design philosophy for software, equipment and procedures provides a consistent set of standards and terminology for a batch automation project.

I spoke with Christie Deitz who coauthored a paper entitled, Writing a Functional Specification for an S88 Batch Project.

Christie believes that S88 provides many benefits for the project team and project stakeholders. It starts with establishing common structure and terminology for clear communications between the automation, quality control, manufacturing, and the management teams. The nature of the modular standard facilitates object-oriented, class-based designs. This helps minimize documentation by defining requirements only once for the entire class. It also helps improve the consistency of the design. By streamlining many instances into one class it means that design, implementation and testing efforts are reduced which help the project stay on schedule.

She stresses that the key is to use S88 early during the requirements definition. According to GAMP (Good Automation Manufacturing Practice), the functional specification defines the process automation requirements and becomes the basis for the design specifications. The functional specification may include a process description, piping and instrumentation diagrams (P&IDs), process flow diagrams (PFDs), and an instrument list.

Christie encourages process manufacturers to make sure automation or other S88 knowledgeable people are involved early in the process design to make sure the advantages of a modular approach are built into the project. It's also a good idea to include stakeholders from automation, process engineering, production and quality into the creation of the functional specification. This front end work will minimize changes due to misunderstandings by the project stakeholders. These changes become more expensive the later they occur in the project schedule and can delay the startup date.

Process manufacturers have many choices in how to organize the specifications. Christie's experience is that functional specifications should be created for each area, which allows classes to be described within a single document. There are typically five to ten process areas within a process. This allows for a limited number of documents to manage.

By taking this approach Christie and the experts in our Life Sciences organization have helped deliver projects ahead of schedule, which means faster payback on the project.

Tags: S88 | ANSI/ISA-88 | functional specifications | project management | requirements definition | class based |

May 17, 2006 in Life Sciences, in Project Services | Comments (0) | Trackback (3)

Most process plants have at least one key quality parameter that is not measured in real-time. Traditionally, process manufacturers have relied upon manual lab samples to verify that the process was producing products within the required specifications. The issue with this approach is the time delay between when the sample is drawn and when the lab analysis is complete. If the results are not within the required specifications the product during this period of time must either be reworked or in some processes, disposed of. This reduces the efficiency and profitability of the process.

Over the past decade, neural network technology has been introduced as a way to create models to act as soft sensors for properties where no physical sensors exist. Soft sensors are also used in conjunction with analyzers to fill in gaps between sample points or for validation/backup of expensive analyzers. Some examples include: Kappa analysis in the pulp and paper digestion process, end (cut) points of products in the CDU/VDU columns of a refining process, food properties, end of fermentation process prediction, and emissions analysis.

In spite of the indicated potential and the improved tools, the acceptability of neural net soft sensors has been fairly limited. I spoke with Ashish Mehta, a lead developer in the DeltaV APC technology organization, who feels the complexity (actual and perceived) has been a major factor. He presented a paper, Successfully developing a property estimator with DeltaV Neural (7.8Mb), at the last Emerson Exchange to help alleviate such concerns.

Ashish mentioned the real benefits of using soft sensors:

• They provide real-time online predictions of important quality variables (as fast as 1s)
• They reduce process variability as predictions can be used in feedback
• They improve control as quality parameters can be incorporated into APC/optimization strategies

Like other process optimization projects, it's important to make sure your instruments providing the data for the model are sound. Ashish recommends auditing the sensors and valves providing the measurement data to make sure they are reliable and reasonably well tuned. Important process equipment should not be out of service or bypassed causing it to be operating in a non-standard way. Finally, it is critical that the lab measurement and analysis process is streamlined to ensure that measurement values and delays are accurate.

When it comes to selecting the variables as input to the neural network, make sure you capture the ones causing the dominant effects. More inputs are better, although avoid those offering redundant (highly correlated information.) Use calculated inputs like ratios/first principles-based inputs.

Ashish stressed that neural networks are empirical models where the underlying model knows, and is therefore only as good as the data it is trained on. As a result it's important to collect the data over a wide operating range, and make sure outliers (say due to shutdown) are removed from the training data set. Generally, you should also maintain an additional data set, different from the test set, to verify the model by comparing its prediction with the actual data.

If the soft sensor has been created using DeltaV Neural, it is commissioned by a simple download to an NN function block. The function block approach greatly simplifies the online operations and increases the soft sensor lifetime. For example, it will monitor for any of the inputs being outside its trained range and mark the soft sensor output as uncertain, so that the control strategy can take this uncertain information into account. It continues to use the lab analysis results in a feedback fashion to automatically adapt the prediction value to any process changes after training.

In addition, the NN function block can be used in a closed loop control strategy as the PV of an MPC (or PID) block. According to Ashish, the greatest opportunity is the ability to use the key quality measures, that were available only infrequently, in full closed loop (advanced) control and optimization strategies thereby resulting in significant variability reduction (and likely increasing the operation's profitability.) You should always look ahead to closing the loop on the quality parameters that you want to develop a soft sensor for.

Tags: neural network | soft sensor | property estimator | prediction | process identification | quality measurement |

May 15, 2006 in Process Optimization | Comments (0) | Trackback (0)

After reading about the "10 Truths of Safety Instrumented Systems" in a ControlGlobal.com email (Control Magazine's online website), and getting a copy, I'd spoken to our of our safety experts, Andrew Dennant, and was working up an analysis of the 10 truths...

...and then I read the comments of Nova Chemical and ISA Safety Division Newsletter Editor/Webmaster Brian T. Smith on Walt Boyes' SOUND OFF!!! blog.

Andrew and I will add just one point to the discussion underway.

When thinking about availability, consider the entire safety loop, not just the logic solvers, since the majority of failures occur outside the logic solver. An analysis of the data sources like the Offshore Reliability Database (OREDA) and exida’s Safety Equipment Reliability Handbook shows that up to 92% of hardware failures happen in the field and only 8% happen in the logic solver. Studies by the Health and Safety Executive in the UK show that less than 15% of all failures are hardware-related. Doing the math, 15% x 8% = 1.2%, puts us in the range of failures that are caused by the logic solver.

The key to high process availability is having a smart SIS which diagnoses the complete safety function including the logic solver, sensor, and final control element, correctly engineered in accordance with globally-agreed best practice safety standards, aka IEC 61511.

UPDATE: The figures cited in the Health and Safety Executive study are from the publication, Out of Control: Why control systems go wrong and how to prevent failure (2nd edition), orderable from the HSE site.

Tags: IEC 61511 | safety instrumented system | SIS | safety integrity level | SIL | SIF |

May 11, 2006 in Safety | Comments (4) | Trackback (0)

Highly regulated industries like those in which Life Sciences manufacturers operate need efficient solutions manage and properly document their production and use of materials in the manufacturing process.

The production process usually includes both manual and automated operations. The automated part is typically controlled with process control systems with batch software like the DeltaV system.

I spoke with Principal Engineer Todd Ham who coauthored a paper with Senior Technologist Dick Seemann, both in our Life Sciences industry organization. The paper, A Model for Integrating Material Management in a Production Environment, was presented at a past ISA Automation West Conference.

The paper generically describes a solution that Todd and our Life Sciences industry experts implemented at a biotech manufacturing facility. A manufacturing execution system managed the materials for manual parts of the operation.

Todd said the key to the solution was defining an integrated material management model which included support for the processes: batch campaign creation, raw material weigh-and-dispense, manual material charges, and automated material charges.

In their solution, the first step is campaign and batch creation. A unique campaign ID is established which all material information related to the campaign will connect. Also the batch report manager in the process control system can access this campaign ID, to bring in all the material information into a complete electronic batch record, needed for the release of final product. This information is included with the batch history, alarms, events, operator actions, and other data collected by the process control system.

Todd describes a manual weigh-and-dispense operation. An operator logs into a handheld personal data terminal/barcode reader. The system checks and verifies that he has authority and the up-to-date training to perform the weigh-and-dispense procedure. The operator selects the campaign, is presented with the appropriate and available weigh booths, and scans a weigh booth ID barcode. Next the operator selects an intermediate batch container which has been verified by the system as being the correct size, being clean, etc.

With everything properly validated the operator selects from a list of materials presented on the handheld device connected to the warehouse inventory system. Once the material has been retrieved and barcode scanned it is validated for expiration dates, lot numbers, and any other required quality measures. The operator dispenses and confirms the measured weight within the allowed tolerances.

A label containing all this information, as well as an electronic copy for the electronic batch record is available for the production environment. Similar integrated material management processes are available for manual material charging, automated material charging, and the creation of the batch report.

These integrated manufacturing procedures provide enforced compliance for the manual production activities. And overall cycle times can be reduced since the records captured from these procedures are available in the overall batch record instead of collecting and signing off papers after the fact.

Tags: Manufacturing Execution System | MES | Manufacturing Procedures | Process Control System | PCS | Campaign | Batch | Recipe | Material Charge | cycle time |

May 9, 2006 in Data Management, in Life Sciences | Comments (0) | Trackback (0)

Periodically most continuous running plants must schedule a shutdown to perform the maintenance activities which cannot be done while the process is running. The process of managing this period while the plant is shut down is commonly known as a turnaround.

Turnarounds are very expensive in terms of lost production and the expenses associated with the maintenance activities performed so it's critical to plan and execute these activities as efficiently as possible.

I spoke with Mark Coughran, whom I highlighted in an earlier post, about the planning role the Emerson control performance group can play in a process manufacturer's turnaround planning process. Based on the experience the team has gained working with process manufacturers across many industries, they have collected their best practices into a Pre-Shutdown Automation Service.

With this service, Mark and other consultants help identify and prioritize the control loops and devices that should be improved including control strategies, tuning, control valves, dampers, drives, process sensors, and transmitters. They pre-diagnose the troublesome control loops and devices which most impact process stability and flexibility and that can only be fixed with the process shut down.

The process begins by working with plant staff to assess the performance of critical loops with the most economic impact on the plant. Using tools like Emerson’s EnTech Toolkit and Entech Valve Tester for loop performance measurements and analysis of process dynamics, control performance consultants provide specific recommendations to optimize controller and instrumentation performance and recommend further improvements to the instrumentation, process design, and control strategy to be implemented during the turnaround. A key aspect of these tools is that they enable performance diagnostics while the process is running in normal operating configuration giving an online holistic view of operating control performance.

When problems are identified that have a significant impact on operational performance, the team makes specific work package recommendations for the turnaround, which may call for follow-on services that Emerson's Instrument & Valve Services team or local business partners can provide such as offline testing of control valves, dampers, and instruments using tools like FlowScanner and AMS ValveLink.

Typical problems uncovered as a result of this pre-shutdown service include: poor valve trim or positioner performance, excessive loop oscillations, sluggish response, excessive dead band, or loop interactions which can often be solved with advanced control.

By pre-diagnosing and better focusing the control improvement efforts, the pre-shutdown service helps make turnarounds more efficient and results in better control performance post-turnaround.

Tags: control performance | turnaround | loop performance | process dynamics | plant shutdown |

May 5, 2006 in Process Optimization | Comments (0)

After reading CONTROL magazine's Editor-in-Chief Walt Boyes’ Compared to Wireless? blog post, I spoke with DeltaV product manager, Bob Huba, who oversees the cyber-security requirements and developments in the DeltaV system. Bob authored the DeltaV System Cyber-Security and Best Practices for DeltaV Cyber-Security whitepapers.

Bob, a voting member on the SP99 committee, has a slightly different take than Walt’s assessment that what is driving the committee,

...has as its end result getting the Department of Homeland Security off our backs...

This may be a side benefit but Bob feels this is not what is driving the committee to action.

He believes the automation suppliers and end users really understand the importance of having some sort of standards to measure control system security. In fact, Bob says the greatest push for this standard is coming from the user community. They are driving this committee the hardest which seems to be bringing greater cooperation and more focus on getting something done.

If you are interested in some of the work to date by the SP99 committee, you can purchase these reports from the ISA:
ANSI/ISA-TR99.00.02-2004 Integrating Electronic Security into the Manufacturing and Control Systems Environment and ANSI/ISA-TR99.00.01-2004 Security Technologies for Manufacturing and Control Systems.

Tags: cyber security | SCADA | SP99 | ISA | ANSI |

May 3, 2006 in Cyber-Security | Comments (0) | Trackback (1)

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.

Tags: refining | petrochemicals | AIChE | statistical control | multivariate analysis | abnormal situation prevention | ASP |

May 2, 2006 in Abnormal Situation Prevention, in Refining | Comments (0) | Trackback (0)