. "5 Needs and New Directions in Computing for the Chemical Process Industries." Impact of Advances in Computing and Communications Technologies on Chemical Science and Technology: Report of a Workshop. Washington, DC: The National Academies Press, 1999.
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one is willing to accept for a particular plant. For example, if you are designing an airplane and you expect to build a thousand of them, then you can afford to design and build in a super-sophisticated control system because the cost will be spread out over many units. That does not happen in the CPI.
Our plants are large, very complex, and, I am sorry to say, still relatively poorly understood in the sense that we don't know all the details of the chemical reactions and their associated thermodynamics and transport properties needed for the design of these facilities. Because of this lack of knowledge and the inherent safety concerns of handling some very dangerous chemicals, our plants tend to be over-designed to ensure that both safety and production goals will be met. Even for some of our oldest and best-known products we are still improving our fundamental understanding. This is happening largely because of vastly improved analytical instrumentation. In some cases we have benefited significantly from the application of computational chemistry to provide basic data that otherwise would have been too costly and time consuming to measure in the laboratory.
Most of our large plants, particularly those that make polymers, were justified on economies of scale. Initially that made sense because we were only expecting to make one or two products. Over time, because of good chemistry and market demand, the number of products has grown, which has often meant that the plant has had a much broader range of operating conditions. In many cases we have designed and built very good “battleships” but now, because of the proliferation of products, we are forced to try and run them as if they were "PT boats." Another characteristic of those polymer plants that make filament and sheet products is that they typically have a very wide range of time scales. At the front end, the reactor might have a time constant that is measured in hours while at the back end of the process where the filament or sheet is being formed, the time constant may be measured in milliseconds or seconds. The combination of multi-product transitions with wide ranges of operating conditions and time constants leads to some very challenging manufacturing problems.
The essential problem facing the chemical process industries is shown in Figure 5.1. The graph shows the trend of capital productivity with time for both total manufacturing and chemicals. Capital productivity tries to measure how effectively capital is being utilized. Simply stated, for each dollar
Capital productivity for all manufacturing and for chemicals.