Separating process conditions from product attributes

What is your instrumentation telling you? Can the information help you learn about the product?


Dear Control Engineering: The article Beyond the PV discusses the differences of measuring process conditions versus measuring the product directly. How do we separate those two?

In a given process there will be instruments designed to measure all sorts of things. We have what we call the “big four process variables,” which are pressure, temperature, flow, and level. These are all process conditions, in that they tell you, for the most part, about what’s happening with the process, but no specific attributes of the product.

Let’s say you have a tank holding a given amount of liquid. Measuring the level, pressure, or temperature of the liquid will tell you what the conditions are in the tank, but they will not help you determine if it is water, ethanol, or gasoline. If you’re clever, you can determine the weight of the liquid using a pressure sensor which will help you determine its density. That is a specific attribute of the product.

In a given manufacturing process, you will normally need both kinds of measurements at appropriate stages. As the article points out, the number of options available is huge, but often there are gaps. There are relatively few process conditions that can’t be measured one way or another. (Another article in the June issue describes using infrared to measure difficult temperature applications.) However if you want to find out product attributes, things get much more complicated. The more specific the attribute, the fewer choices you have in most cases.

In his article, Scheele points out that the sophisticated signal processing capabilities available now allow users to combine readings from a group of instruments to determine characteristics that cannot be measured directly. Back to the tank example, if you measure the physical level (volume) of liquid in the tank with a radar sensor, the temperature of the liquid with an RTD, and the weight of the liquid with a pressure sensor, you can get a very accurate picture of its density by performing the appropriate calculations. From process conditions, you can learn about specific product characteristics. Admittedly, that’s a pretty basic example, but the same concept applies in far more sophisticated applications. A Coroiolis flowmeter can tell you the density of what is flowing through it, but it does that function by calculating the value from other attributes, just like the tank example. It is not some type of native densitometer.

Ultimately the key is figuring out how to select and place instrumentation in a process to get the information you really need. As Scheele says, there are possibilities of “building a new knowledge base in which data from conventional field devices is combined with applications expertise, modeling, and advanced process control software to enable measurements that could not have even been imagined as little as 20 years ago.”

Peter Welander,

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