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By Walt Boyes and Nancy Bartels
Simulation and modeling of processes had their birth forty-odd years ago in refineries. Using simple, low-fidelity models, refineries could, in some cases, improve their outputs, profit margins and life cycles by 50% or more. Now this technique has branched out into pharmaceuticals, life sciences, specialty chemicals and other batch and hybrid process environments. Why? Because fake mistakes cost less than real ones.
The savings come from the ability to develop better processes quicker, improve safety and deliver a better, more efficient training experience.
“To be able to model something so you can look at the model and make a prediction on what a small change in that model will be, is an incredible time-saver. If you make your model correctly, then you can predict how things are going to change, going from a two-liter bioreactor to a twenty-liter unit to a 2,000-liter bioreactor. We can affect not only the manufacturing area, but also the product development area and cut the time to market,” said Trish Benton, a life-sciences consultant.
She is working with Terry Blevins of Emerson Process Management and Scott Broadley, president of measurement and control manufacturer Broadley-James Co., on a partnership to develop advances in simulating and modeling bioreactor processes. We interviewed the three at the Emerson Exchange 2007 user group meeting last month. (To hear the complete interview click here).
Blevins noted that simulation and modeling tools are at the heart of Emerson’s efforts to incorporate the Process Analytical Technology (PAT) Initiative into its product offerings. While the PAT Initiative originated in the pharmaceutical manufacturing industry, it is quickly filtering out across all the process industries, including refining and specialty chemicals.
The ability to integrate the simulation tool set with the control system is one of the factors pushing simulation out of the refineries and into the rest of the process industries.
“That’s what we’re trying to do,” says Broadley. “We’re trying to integrate this modeling capability with our bioreactor control package called ‘BioNet’ that is used for large-scale process development and doing lots of runs and variations on runs to find out what is the optimum pH, dissolved oxygen and other conditions under which these cells are to propagate. With a predictive model, we can do a number of what-if scenarios which might guide you right off the bat into the proper avenue to run down without blundering into blind alleys. But even beyond that, with the predictive control tools that Emerson is using with these models, we believe we will be able to do inline corrections, looking at the model and deducing the direction that the process is taking.”
Breathtaking stuff. And biotech isn’t the only industry where this type of “model-to-control system” interfacing is going on.
We also interviewed Blevins with another set of partners. This time, Bob Wojewodka and Philippe Moro from Lubrizol Company joined Blevins (To hear the complete interview click here). Lubrizol makes extensive use of offline simulation and modeling techniques, but what Wojewodka wants to do is integrate the large amount of offline analytical information developed from history and from their models directly into the control system.
“What we’re doing,” Wojewodka said, “is looking at batch processing specifically. Batch processing has been around for centuries, but it hasn’t been well-studied, mainly because of complexity with data and the integration of that data and the analysis of that data into the batch context, and all the ramifications around that…especially in an online and real-time mode.”
Wojewodka wants to take the analysis down to the process dynamics level. “We’re going to actually look at process dynamics,” he continued, “Process information, coupled with business data, coupled with analytical data in such a form that we can look at relationships between process and outputs—outputs being product quality, product uniformity, economic parameters…but especially in an online mode.”
Many simulation software packages have the ability to tie into engineering and design software suites directly to create other efficiencies for process industries.
TransAlta, operator of Suncor’s Poplar Creek cogeneration facility in Ft. McMurray, Alberta, found that there was a problem with one of its boilers, and using Honeywell’s UniSim simulation software, its engineers discovered they could solve the problem by engineering in a second control valve.
Barry Hu, automation and process engineer at bioprocessing company Genencor International’s Cedar Rapids, Iowa, facility, says his company first bought MiMiC simulation software from Mynah Technologies for help doing the company’s roll-over from a Rosemount RS 3 system to DeltaV.
“We needed to redo all the programming for that,” said Hu. “That is such a complicated process. We wanted to make sure everything was running correctly in DeltaV before conversion. The linkage between the batch platform and the control hardware was really tricky. The simulation enabled me to avoid a lot of problems there. It was a debugging tool to make sure all the sequences were set up correctly. We were able to simulate the entire environment on a single computer. We were expecting some major disaster when we rolled over. We thought we’d lose three batches in rollover and we lost none. There were no major surprises. We had record production after the conversion.”
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