February 15, 2010

Exceptional Opportunities in Process Control - Adaptive Level Control

By Greg McMillan

The tuning settings of many level loops aren't in the ball park. The result is persistent oscillations that spread throughout the process.

Level loops frequently manipulate feed flows to process operations. Variability in these feed flows causes variability in the temperature and composition in equipment whose process loops end up chasing continual changes in feed. Often the level loop creates slow rolling oscillations due to the product of level controller gain and reset time being too small. The solution of increasing the controller gain is counter intuitive and is rarely done correctly since the range of controller gains for level loops is exceptionally large and changes with the density of the fluid and the cross sectional area of the vessel.

Level loops make a good educational lab experiment in process control. To see how a DeltaV Insight adaptive controller automatically identified the tuning and compensated for nonlinearities for level control of a conical tank checkout the article "Adaptive Level Control". For more background on the dynamics and tuning of loops for integrating processes, see Appendix A referenced in this article and the September 2, 2009 entry on this website.




January 12, 2010

Exceptional Opportunities in Process Control - Virtual Plants

By Greg McMillan

Simulation was such an integral part of my job it is difficult for me to visualize a process control career without models. I was asked to join Engineering Technology (ET) at Monsanto in 1976 because I had developed a dynamic compressor model as the lead Instrument and Electrical engineer for what was the largest Acrylonitrile plant in the world. I developed the model in order to understand more about the incredible surge phenomena where reversals of flow could occur in less than 0.01 seconds leading as a minimum to a loss in efficiency and in some cases to the damage of shafts and seals of large and expensive compressors from the extreme momentum swings and vibration. In most plants the ability to initiate and explore abnormal situations is severely limited or not allowed. A dynamic model allows you to readily and quickly try out "What if Scenarios" whose only limit is your imagination.

ET developed FLOWTRAN, a process simulator that was directed by the government to be sold to Aspen institute. Several key specialists left with the FLOWTRAN to develop the process modeling software that eventually was the state of the art process design modeling software by AspenTech. In the ET process control groups, we used FLOWTRAN to get the process gains and then used IBM's Continuous System Modeling Programs (CSMP) followed by Raytheon's Advanced Continuous Simulation Language (ACSL), and ultimately HYSYS Plant for dynamic simulations. After retirement from my career in ET, I focused on using the DCS as a Virtual Plant for simulation and control. The graphical configuration environment where function blocks are equipment and wires are streams (e.g. DeltaV Control Studio and MiMiC) allows the development of dynamic process models in the same familiar way as the configuration of control strategies.

My vision of a virtual plant has a simple first principle model that starts with one component (e.g. water and air) that is corrected by an experimental model automatically generated by a simple test that takes less 10 minutes to execute for most loops. The result is a plant wide simulator. As more information is available and desired, the process knowledge embedded in the model grows but the fundamental basis is the same. No re-write is required. The opportunities and associated fidelity needed are as follows:

1. Control system set point optimization - Fidelity 5

2. Control strategy analysis and R&D - Fidelity 4

3. Root cause analysis and data analytics R&D - Fidelity 4

4. Operator training for abnormal situation management - Fidelity 4

5. Controller tuning and PID structure and options analysis - Fidelity 3

6. Batch configuration checkout and operator training for system familiarization - Fidelity 2

7. Loop configuration checkout - Fidelity 1

Fidelity 1: loop process variables respond in the proper direction to their loop output

Fidelity 2: measurements respond in the proper direction when control and block valves open and close and prime movers (e.g. pumps, fans, and compressors) start and stop.

Fidelity 3: loop dynamics (e.g. process gain, time constant, and deadtime) are sufficiently accurate (e.g. 50%) to tune loops and see process interactions

Fidelity 4: measurement dynamics (response to valves, prime movers, and disturbances) are sufficiently accurate (e.g. 25%) to track down and analyze disturbances

Fidelity 5: process metrics (e.g. yield, raw material costs, energy costs, product quality, production rate, production revenue) are sufficiently accurate (e.g. 5%) to find optimums

In the ISA New Orleans section short course I am teaching on March 3 and 4 titled: "Exceptional Process Control Opportunities - An Interactive Exploration of Process Control Improvements", I will use a virtual plant suitable for process control research, development, and education. I will demonstrate how a user can perform a 10 minute test of a manipulated process flow to provide a fidelity level 3 and 4 model. The contact for the course is Robert Deeb (ISA New Orleans section education chairman).

In the InTech Jan-Feb 2010 Web Exclusive "Advances in Flow and Level Measurements Enable Dramatic Improvements in Process Knowledge and Control", the following perspective was offered on the importance of flows for many types of process models including the following:

• Projection to Latent Structure or Partial Least Squares (PLS)
• Model Predictive Control (MPC)
• PID Adaptive Controller Tuning
• Neural Network
• First Principle

Flows determine what is going on in a process. If you don't get the flows right, not much else matters. Because of valve backlash, stick-slip, nonlinearities, and variable pressure drop, all types of process models have suffered from the use of valve positions rather than flow measurements. PLS, MPC, and PID performance assumes dynamics that are linear and independent of direction and size, all bad assumptions when valve positions rather than flows are used as inputs. Additionally, the valve nonlinearity from the installed characteristic varies with pressures at the inlet and outlet of the valve.

Pioneering advances in dynamic modeling by Alex Muravyev offer a next generation of pressure-flow solvers that will be robust and flexible enough to provide flows from valve positions. The solver is expected to handle complex piping networks and the discontinuities from batch and startup sequences (AdvancedSimulationPressureFlowSolver.pdf). The ability to consistently and comprehensively compute flows for all streams will enable dynamic models to reach the highest levels of fidelity required for research, development, and design of automation systems for nearly all applications. Presently, models can only move up in fidelity when flow control loops are installed on the key streams so that feedback action removes the nonlinearity and unknowns of the valve and piping system. New pressure-flow solvers can eliminate this precondition. A side benefit will be the demonstration by these models of the improvement in process performance that can be gained from cascade, feedforward, and ratio control. The quantifiable benefits from demonstrable test cases can justify new flow devices to provide missing flow measurements or improve the accuracy of existing flow measurements.




January 5, 2010

My Top Twenty Broken New Years Resolutions

By Greg McMillan

For comic relief for the New Year I offer here some of my broken resolutions published in my Control Talk column plus a new number one.

(20) Listen intently to my wife's instructions. Why does my mind still jump to weighty matters like what is next for dinner?

(19) Stop making cheap control valve jokes. Could the next final element reputation I hurt be my own?

(18) Help make smart diagnostics smarter. Do I need to de-fussify my fuzzy logic?

(17) Stop lusting in my heart for more computing power. Is it the PC or me that is the constraint?

(16) Turndown the volume on my headphones. What did you say?

(15) Stop drinking cheap wine. Does good wine ever come in a size large enough?

(14) Read a college text on control theory. Can I watch Star Trek without setting up the state space equations?

(13) Stop answering a question with a question. Why should a consultant do this?

(12) Spend more time with my wife than with Control magazine. Whatever happened to my January issue?

(11) More bark than bite. Can I at least growl? Will I be forced to wear an anti-bark collar? Is this better than a muzzle?

(10) Stop making fun of seniors. Who else do I know? We certainly aren't an endangered species with the influx of baby boomers.

(9) Stop focusing on deadtime. What else is there at Sun City? Whoops, I am already breaking my last resolution.

(8) Final element resolution resolution. Why should I get unstuck when valves are stuck and it gives me a chance to repeat words?

(7) Get into hybrids. No issue here with fashion models. Can a hybrid face up to a 2 ton high lift truck with a cattle guard? Can I drive under a cow?

(6) Show my more sensitive side. Wait, will I confuse people including myself? Do I have to start watching "Brothers and Sisters?"

(5) Stop drinking cheap booze. I will give this another shot.

(4) Listen to hip-hop. What if I am not hip and can't hop?

(3) Become rich and famous. How about poor and infamous?

(2) Lean how to sell. How can I sell a product when I can't sell myself?

(1) Stop pushing the Essential Book even though the royalties are donated for wireless research at the University of Texas and the book is like a fine wine with a lush blend of technology with rich overtones, a balanced feel, and a lingering finish. What if readers like cheap wine? What if readers are not UT fans? What if they are rooting for Alabama? What if they think wireless research will be used in the BCS game?




November 9, 2009

Exceptional Opportunities in Process Control - Articles and Books

By Greg McMillan

After all is said and done, articles and books have been the main method of advancing and sharing the technology for industrial process control.

I don't know of an undergraduate degree in process automation. Chemical, electrical, mechanical, and systems engineering programs offer an undergraduate course or two on process control. However, the typical university control course needs to spend most of the time on Laplace transforms, frequency response, and state-space to provide a theoretical understanding and groundwork for graduate courses. Outside of chemical engineering the focus is more on set point response and signal noise for servo mechanism and aerospace control. Consequently, the student doesn't learn about the critical characteristics of control for the process industry where nonlinearities, deadtime, valve stick-slip, unmeasured load disturbances, and incredibly long time frames are the cause of most tuning and control loop performance problems. Throw into the mix the unknown features of proprietary PID algorithms, and you have a script for islands of expertise. I personally like tropical islands so maybe this is OK. I could retire to one and conduct web based courses instead of doing cross word puzzles.

Courses may not be the whole answer considering that more than 80% of the details presented are forgotten. The PowerPoint slides often don't tell the real story. In my days, professors used the chalk board with only passing references to a book so my only record of knowledge is in notes long gone. Maybe the best way to make courses have a greater long term value is by providing labs for hands-on learning and refresher exercises, key memorable concepts, and resources for reference and further investigation. Audio should be combined with the presentation as exemplified by the slidecast of my Boston ISA presentation Exceptional Process Control Opportunities.

Considering that people don't have time to read books maybe courses and seminars and the structure of books themselves could provide better direction to areas of specific interest to solve problems. This is an argument for electronic books with interactive queries and demos.

For process automation, the articles and books written by practitioners are our best way of capturing and advancing the technology. Unfortunately users are not given the time or priority to write and most companies are reluctant to disclose information that could be considered to provide a competitive advantage for manufacturing. Consequently, suppliers of automation systems and services write most of the magazine articles and books on the practical application of process control. University professors write most of the journal articles and technical conference papers on the theoretical advancements in process control. The two groups don't talk much to each other. The use of industrial control systems for labs is one glimmering area of hope for the meeting of minds from universities and industry (see my last entry on "Exceptional Opportunities in Process Control - Expertise Development" and the June 1, 2009 entry "What I have Learned? - Bridging the Gap between Universities and Industry").

For me writing books was a way of organizing and expanding knowledge gained on the job. I found it allowed me to put technologies to bed (at least temporarily) so I could clear my head for the next area of expertise. My serious technical books in order of oldest to most recent publication date are: Axial and Centrifugal Compressor Control, Biochemical Measurement and Control, Continuous Control Techniques for Distributed Control Systems, Tuning and Control Loop Performance, Advanced Temperature Measurement and Control, Process/Industrial Instruments and Controls Handbook, Good Tuning - A Pocket Guide, Advanced pH Measurement and Control, Advanced Control Unleashed, Models Unleashed, New Directions in Bioprocess Modeling and Control, and The Essentials of Modern Measurements and Final Elements. My favorite book, which is a mostly serious collection of case histories written in a humorous way, is A Funny Thing Happened on the Way to the Control Room. My mostly humorous books in order of oldest to most recent publication date are: How to Become an Instrument Engineer - The Making of a Prima Donna, Logical Thoughts at 4:00 am, How to Become an Instrument Engineer - Part 1.523, Dispersing Heat Through Conviction, The Life and Times of an Automation Professional - an Illustrated Guide, and The Funnier Side of Retirement for Engineers and People of the Technical Persuasion. The last two books were written solely for comic relief.

While I had to largely write the books on my own time (except for the last serious one), the companies I worked for were supportive in terms of approval and recognition. In the end I expect books helped me along with my heroes Shinskey and Liptak to be the first group of inductees into Control magazine's Process Control Hall of Fame.

I think the following message titled "Why Books" from Ted Stillwell who is of the same vintage as me concisely offers "memories of the way we were."

Because I learned process control on the job books provided the only formal learning environment. Starting with the first treatment plant, with a control panel that would not fit through the door, I began my knowledge quest about instruments and process control. Chemical Engineering published Process Automation a 14-Part Series. My first book purchase was Liptaks' Instrument Engineers' Handbook that I read commuting back and forth to the office. The process control companies offered a great training ground for young engineers. Highly experienced application specialists at these companies wrote most of the articles and books on process control. I have five books by Shinskey, the most recent being Feedback Controllers for the Process Industries (McGraw-Hill 1994).




October 23, 2009

Exceptional Opportunities in Process Control - Expertise Development

By Greg McMillan

Before my talk at the Boston ISA section meeting on Oct 20, I had the opportunity to interview Sarah Tremblay and Ted Stillwell, automation engineers for a company that designs water and wastewater treatment systems. Sarah has a degree in mechanical engineering and has been on the job for one month. Ted has over 40 years of experience in the process industry. Like me, Ted started out in construction so he got a lot of first hand experiences on what worked in the field. The interview was an informal discussion for an upcoming Control Talk column on "Expertise Development" probably with a more catchy title such as "The Future is Now."

When I started as an E&I design and construction engineer after graduating with a degree in engineering physics, I went to a 12 week instrument school. One of the attendees at the ISA talk says he knows a company that had a 9 month training program. Such on-the-clock courses and programs are rare. Are we missing the boat? Sarah effectively said "not really" because such an intensive and extended training would not mean much to a new engineer who has not developed a real feel for the job. Sarah is learning by being responsible for small parts of a project. She asks a lot of questions. She visits job sites and goes on panel checkouts with Ted to see how designs translate to actual installations. This is the time honored tradition of how expertise is developed on the job. In 5 to 10 years, you have a proficient engineer. In my case, my development was accelerated by being sent after instrumentation school to E&I field construction for 2 years for the building or renovation and startup of 5 production units. Since sending new engineers to E&I construction is not a widely viable option, what can be done to improve this process?

There are no easy answers. Courses in chemical, electrical, mechanical, and systems engineering should have more emphasis on process measurement and control as practiced in industry. Practitioners (especially recent graduates) should be invited to give guest lectures on case histories of process control improvements and the type of jobs in the process industry. It should be emphasized that regardless of whether the job is in engineering, research, or production, all engineers rely on the automation system to see, analyze, and interact with the process. You need to know how to understand the system's interface and functionality to take full advantage of the systems capability. Process control labs with industrial control systems should be an essential part of this learning experience. Many of the leading universities have taken this approach as described in the June 1, 2009 entry on this web site "What I have Learned? - Bridging the Gap between Universities and Industry."

Sarah made a good point that course labs can be too controlled. The script is fixed and the student doesn't have the opportunity to explore different scenarios and ideas, implying the falsehood that on-the-job situations are typically as uneventful. To help address this issue, I think these labs should be offered as a stand-alone course rather than in addition to a "hands on" experience to demonstrate points in a lecture course. I think the lab should consist of both a physical and a virtual plant for the same unit operation. The virtual plant would allow the student to take the operation and control system to places not practical to achieve because of time and equipment limitations.

This education process needs to ongoing. It should not stop with the new job. Since extended training programs may be too much too soon besides being impractical from a standpoint of cost and time in today's work place, periodic seminars and demonstrations with a virtual plant would seem to be the most effective approach. Case histories and updates on technological advances are essential. The seminars and labs can be conducted via the web if interaction between the presenter and attendee is not sacrificed. Companies need to provide the time and encouragement for ongoing education. The ISA Certification of Automation Professionals (CAP) should be part of the career plan. Participation in ISA should be part of growth process for both the individual and ISA. There should be a company library of the best books on process measurement and control (see next week's entry here for my short list). Users should be encouraged to publish to help solidify their experience and share it with the profession. I always learned something about my application in the process of having to describe the problem, considerations, concept, and solution. See my May 28, 2009 entry "What have I Learned - Writing" on what worked for me. Sarah with a minor in English is ideally situated for this endeavor.

Given that the education process takes years of on-the-job experience it is critical that companies hire new automation engineers now to insure the existing expertise is transferred before the expertise is gone. See my Control Talk Column series "Going, Going, Gone" Part 1 (August), Part 2 (September), and Part 3 (October) for a discussion with some key people from what is probably the best process control group in the USA.

Most of the experienced engineers here in the USA are members of AARP.




July 6, 2009

Post Retirement Key Points - Part 1 (2003 - 2004 Articles)

By Greg McMillan

As I reflected on my career, I reaffirmed that what drives me is gaining a deeper understanding and sharing what I have learned, hopefully with a few laughs along the way. Throughout my career I sought with an open mind the knowledge and insights of the leaders in process modeling and control. I then used simulations to rapidly explore process relationships and to prototype control improvements that incorporate process understanding. The knowledge prepared me to solve tough plant control problems.

During my career at Monsanto I wrote a bunch of articles in the 1980s for InTech on my time in the plants with some humor introduced to help make the material more accessible and memorable. These articles were compiled and published in the book A Funny Thing Happened on the Way to the Control Room available for viewing as an E-book in the April 3, 2009 list of my books on this website. This is my favorite book, I didn't write much in the way of articles or books in the 1990s. I was on the road most of the time.

When I retired from Monsanto-Solutia in 2001 (sans package), I taught at Washington University. The students were great but after the course and lab was developed, it became routine. Also, I felt isolated.

I tell people I flunked retirement. I moved to Austin in September 2004 and started a second career as a part time consultant at Emerson Process Management. This gave me a chance to keep up to date with the latest new tools besides continue my exploration of process control opportunities. Plus it felt like home since Monsanto and Fisher Controls were one for most of my career.

I have been blessed with access to the best minds. In Monsanto's Engineering Technology I got to work with the leaders in process modeling and control. Some went on to distinguished chairs at prestigious universities, several were inducted into the Process Control Hall of Fame, some served as presidents of ISA and AIChE, and others left to become the principal technical resources for leading simulation companies. Here in Austin in Applied Research I get to work with the brains behind DeltaV. Plus my second career is more balanced. Except for the spike in work this year, I take a total of 4 months off each year to travel to see relatives, friends, and neat places and to write books.

Key points of my articles written in my post retirement years provide a quick overview of what I have been doing. The entries on this website in July will focus on the dozen articles I have written since retiring from my full time job. Here are the articles from 2003-2004.

"Has Your Valve Responded Lately", Control, May, 2003
"What is Your Flow Control Valve Telling You", Control Design, May 2004

Putman publications decided to do an encore publication in a second magazine. Some nomenclature typos were corrected in the reissue of the article in Control Design.

1. Deadband originates from backlash in the linkage and connections between the actuator and the plug, disc, or ball. Stick-slip comes from friction in stem packing and seals around the sealing of the plug, disc, or ball for process isolation

2. Deadband from linkage and connection backlash and stick-slip from trim and packing friction create deadtime for slowly changing controller outputs

3. Deadband will create a limit cycle in any control system where there are two integrators in series, such as a PI controller on an integrating process (e.g. level)

4. For deadband, the limit cycle amplitude is the ratio of deadband to controller gain

5. For stick-slip, the limit cycle amplitude is the product of the open loop gain and the stick-slip

6. For both deadband and stick-slip, the limit cycle period is proportional to the controller integral time and inversely related to the controller gain

7. Large actuators can have a large stroking time for a large change in signal

8. The size of the changes signal typically used to checkout control valves will not reveal the deadband or stick-slip and make all but the largest valves look good

9. A volume booster can reduce the stroking time of big actuators but has a large deadband. The booster should be put on the positioner output to quickly drive through this deadband. The booster bypass must be opened enough to prevent fast cycling from the positioner output looking into the booster's small inlet volume

10. Unstable oscillations can break out for large disturbances when the integral action in process loop becomes faster than the valve response. The integral time must be greater than the product of the valve slewing rate, disturbance size, and controller gain. (Not mentioned in the article but frequently discussed on the this website is that position read back from digital positioners and the PID dynamic reset limit option can automatically prevent the controller output from outrunning the valve)

11. Limit cycles are attenuated (filtered or washed out) by vessels or columns. The ratio of the attenuated to original amplitude is proportional to the period of the oscillation and inversely proportional to the residence time (volume/flow)

12. The control valve with the best response is a sliding stem valve with a digital positioner. If one must use a rotary valve, avoid tight shutoff and high friction packing and use a diaphragm actuator with a short shaft and splined connections between the actuator shaft and the stem of ball, disc, or plug. Make sure the stem is cast with the ball, disc, or plug to avoid another connection with backlash

Postscript: Rotary valves designed by piping manufacturers have a lot of deadband and stick-slip as discussed in the July 2009 Control Talk column "Downturn Turndown" in Control magazine.

"The Next Generation - Adaptive Control Takes a leap Forward", Chemical Processing, September, 2004

1. Nearly all controllers are detuned (backed off from maximum performance) to some degree to provide a smooth response and to deal with the inevitable changes in the process dynamics

2. Older technology adaptive controllers had these undesirable features
a. The process had to be disturbed or oscillated (e.g. patter recognition)
b. The dynamics were embedded in tuning settings
c. No real insight as to where the process has been or where it is going
d. Tuning method was fixed
e. Always playing catch up even if same situation was seen a thousand times

3. The next generation adaptive controller can
a. Normal changes in a controller's set point or manual output are used
b. The process dynamics are displayed and historized
c. From changes in the process dynamics, plant problems can be diagnosed
d. Several tuning methods are available
e. Tuning settings identified can be scheduled for preemptive action

4. "The information on changes in the process model may be directly used to monitor loop performance and to provide more intelligent diagnostics. The models can provide the dynamics for simulations and identify candidates for feedforward control and advanced control techniques. For example, loops dominated by a dead time or exhibiting disturbance models for multiple variables, are prime candidates for model predictive control. The dynamic process models in general can be used to create or adapt real time simulations for prototyping new control strategies, exploring "what if" scenarios, and training operators. Process gains that decrease or time constants that increase with feed totals are ripe for real time optimization of the run time between defrosting or cleaning and catalyst reactivation or replacement. The beauty of this route is the models and tuning settings are available from the adaptive controller for a higher level of control by a better knowledge of the topology"

"Advanced Control Smorgasbord - A Lot of Tasty Choices", Control, May, 2004

The online version is missing the following introductory sentences at the beginning of the first paragraph.

"By the time I was assigned to my first electronic control room project, some very smart engineers had already developed most of the techniques to exploit PID controllers.
Relative gain arrays and simple decoupling of the controller output were used to analyze and deal with interaction on a steady state gain basis. The outputs from PID controllers, whose process variable was a constraint variable, were sent to a signal selector to form an override control scheme to maximize or minimize a manipulated variable."

1. Previously, advanced process control (APC) required software packages at $100K a clip, separate computers, special interfaces, and consultants to do the studies and implementation. The total bill could easily approach or exceed a million dollars for a medium project, the biggest chunk being the consultant's time charges. Even a greater consideration was that the process knowledge to exploit or to just maintain the system disappeared when the consultants left the site

2. At the turn of the century, APC technologies were integrated into the basic process control system. License fees were minimal and whole cost of implementation decreased by a factor of twenty or more by the automation of the configuration, displays, testing, simulation, and tuning

3. In the time it takes to read this article, a model predictive controller or neural network could have been configured

4. Perhaps the biggest opportunity for driving the application of APC is the development of online process performance indicators

5. The key variable for process performance monitoring is the ratio of the manipulated flow to the feed flow

6. The controlled variable is best expressed and plotted as a function of the flow ratio (e.g. pH versus reagent to feed ratio, column temperature versus reflux to feed ratio, exchanger temperature versus coolant to feed ratio, and stack oxygen is versus air to fuel ratio)

7. The process efficiency is seen in difference between the actual and optimum ratio rather than in the gap between the actual and optimum controlled variable

8. A novel method has been developed to use model predictive control (MPC) to simultaneously adapt multiple first principle process model parameters

9. For closed loop process control, consider
a. PID for tight control of integrating or runaway processes
b. MPC for multivariable control, interactions, and optimization

10. For online property estimators for continuous processes, consider
a. ANN for highly nonlinear predictions with uncorrelated inputs
b. LDE for lag dominated linear predictions with uncorrelated inputs
c. PLS for steady state predictions from large number of correlated inputs

ANN is an artificial neural network, LDE is a linear dynamic estimator, and PLS is a projection to latent structures or partial least squares prediction discussed in Chapter 8 of Advanced Control Unleashed





June 1, 2009

What Have I Learned? - Bridging the Gap between Universities and Industry

By Greg McMillan

Sometimes it seems universities and industry reside on planets that are light years apart. Too bad we don't have Star Ships with warp drive. Universities have leading edge research. Industry has "state of the art implementation."

Why are universities and industry "worlds apart?"

Engineers in industry don't seem to understand how to apply the research from universities. Professors don't appear to really know what is needed in industry. The tools are quite different. Engineers in chemical, pharmaceutical, and pulp & paper plants configure their control strategies in a distributed control system (DCS). Professors typically have their graduate students program their algorithms and test cases in Matlab.

One way to get industry and universities on the same page is to provide a DCS to the university with all the tools needed for research, such as a Matlab interface. In many cases the Matlab code can end up being configured in the DCS as part of the maturation of the innovation. The use of the DCS minimizes the reinvention of the wheel, such as the PID algorithm with all of its evolutionary enhancements. The setup facilitates the transfer of knowledge between the universities and industry. Being able to explore, prototype, and demo university innovations in a DCS makes it more real to industry and leads to rapid deployment and sharing of actual plant results.

If there is a unit operations lab, process control lab, or pilot plant, the DCS can be used to control the equipment used in the experiments. Students gain valuable experience in learning how to work with a toolset that is designed to meet industrial standards. Just learning the nomenclature and working with a DCS gives the student practical skills and confidence when as a new employee the student enters the control room. The window to see and affect the process is the DCS. Whether the student is going into automation or process design & technology, the student needs to be able to understand how to access and review modes, limits, options, and variables that determine how well a process runs. For example, the student gets to work in a university DCS on PID features commonly used in industry:

(1) PID limits (e.g. output, set point, and anti-reset windup limits)
(2) PID options (e.g. set point tracking of the process variable in manual, dynamic reset limiting, and nonlinear gain modification)
(3) PID form (series and standard)
(4) PID structure to determine whether each PID mode (proportional, integral and derivative) works on the process variable or the error (difference between the set point and the process variable)
.
The first semester I taught the Chemical Engineering course "Introduction to Process Dynamics and Control" at Washington University in Saint Louis as an adjunct professor, the students could not relate to my attempt to introduce practical plant applications and considerations in the normal course of Laplace transforms and bode plots. The second semester I added a virtual plant that consisted of a DeltaV DCS running in the Simulate mode integrated with HYSYS dynamic process simulations for each student. I later configured most of the process simulations directly in control studio. I was amazed how fast the students learned how to work in the graphical configuration environment and operator interface. All they needed was a few screen prints on navigation to get them started. Several of the students subsequently got intern or permanent positions doing configuration at the local DCS industry center. I had these students with experience in the automation industry come back to speak to the next class. The result was a dramatic turnaround in appreciation and understanding of what they would face in industry. The students decided on their own to go online to find and buy tee-shirts with Duncan, the DCS mascot, windsurfing. I ended up buying tee-shirts too and we all posed for a group photo by one of the students.

The main obstacle to the use of the DCS in the university is the initial installation and training. This is addressed by the support of industries with the same DCS who have a working relationship with the university and the local business partners of the DCS supplier. This method has enabled over 100 DeltaV DCS installations at educational institutions.

At the Automatic Control Conference in Saint Louis on June 11, I am co-chairing a session with Professor Tom Edgar from the University of Texas on "Bridging the Gap between Universities and Industry." The presentations are:

(1) "Bridging the Gap Between Universities and Industry"
(2) "Digital Process Control Lab at Washington University"
(3) "The Bioprocess Laboratory at Washington University"
(4) "Rose-Hulman Institute of Technology Unit Operations Laboratory"
(5) "Engineering Research Center for Structured Organic Particulate Synthesis (Rutgers, Purdue, New Jersey Institute of Technology, University of Puerto Rico at Mayaguez)"
(6) "Using a Distributed Control System (DCS) for Distillation Column Control in an Undergraduate Unit Operations Laboratory (University of Texas)"

My next blog will be June 22. In the mean time enjoy summertime.




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The opinions expressed here are the personal opinions of Greg McMillan and Terry Blevins. Content published here is not read or approved by Emerson before it is posted and does not necessarily represent the views and opinions of Emerson. © 2006-2010 Greg McMillan and Terry Blevins. All rights reserved.