Chemical Processing - November 2007 - (Page 24)

PAT >> Hybrid approach Figure 4. Use of both empirical and first-principles models has speeded up fermentation batches. Source: Pavilion Technologies. mesh network solution, a range of products that includes a wireless corrosion monitor (Figure 3). “This has turned our previous loop-powered digital HART corrosion transmitter [the SmartCET instrument] (see www.chemicalprocessing. com/articles/2005/525.html) into a battery-powered unit that now has a measurement cycle time of 30 seconds at its fastest speed,” notes Dawn Eden, Houston-based marketing manager - corrosion. Such response speed puts corrosion monitoring into the same league as the traditional process variables of temperature, pressure and flow — but begs the question “Is a near-real-time response really necessary for such a relatively long-term phenomenon as corrosion?” The answer is an unequivocal “yes,” says Eden, citing a couple of practical examples: “acid runaway situations where getting the concentration wrong can cause the diluted acid to tear through quite substantial thicknesses of piping in a matter of hours Similarly, if you’re dealing with a process where product quality has to be absolutely right and you can’t afford any contamination [from corrosion], then you want to have a very early warning of when something is going wrong.” Beyond the black box However, many other types of online analysis remain either too expensive or simply impractical to implement. To handle such chores, the arrival around 15 years ago of a neural-network-based approach of soft sensors and inferential measurements seemed too good to be true. And, some might argue, so it has turned out. Others, though, see a widening role for inferential sensors as people gain more confidence in their capabilities. “The key issue,” says Arthur Kordon, data mining and modeling leader with Dow Chemical in Freeport, Texas, “is that data-driven solutions don’t have the in-built credibility 24 • November 2007 that you have with hardware solutions or models based on first principles. Another issue has proved to be the growing maintenance costs of inferential models based on a limited set of data, which means that you almost always have to extrapolate at some point — and unfortunately a neural network is not a technology that shines in extrapolation.” Those early “black box” types didn’t just infer measurements, too often their sales pitches also implied that all a plant had to do was supply sufficient empirical and historical process data for a model to be built that could predict product properties and provide input for closed loop control of the process. Mike Brown, vice president solutions for Matrikon, Edmonton, Alberta, sums up those early days: “The problem was that people were pushing the technology so hard — exploiting the power of the CPU and all that availability of data — but doing it in a way that was ignoring basic engineering fundamentals. The whole concept of data mining was very powerful but the promise of the technology wasn’t really delivering what clients were expecting. If you changed your feedstock, often your predictions were off but it took a while to realize this and retune the model. It was low cost to buy the technology — compared with buying the analytical hardware — but the support cost didn’t go down significantly.” One of the early pioneers of soft sensors was Pavilion Technologies, Austin, Texas (which Rockwell Automation announced it was acquiring). Over the last two to three years the company has put a lot of effort into developing a hybrid approach to inferential sensors, says senior product manager Ric Snyder. “There was no perfect first principles model, and no perfect empirical model. Both have their pluses and minuses, but we have a lot of runtime now on the hybrid model and use it built into our existing MPC [model predictive control] solution. All of the chemical plants where we have our www.chemicalprocessing.com http://www.chemicalprocessing.com/articles/2005/525.html http://www.chemicalprocessing.com/articles/2005/525.html http://www.chemicalprocessing.com

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Chemical Processing - November 2007 Contents From the Editor ChemicalProcessing.com Field Notes In Process Energy Saver Compliance Advisor PAT isn't Standing Pat Pursue the Perfect Plant Eliminate Exchanger Tubing Troubles Portable Conveyor Speeds Paint Production Process Puzzler Plant InSites Equipment & Services Product Spotlight/Classifieds Ad Index End Point

Chemical Processing - November 2007

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