s digital computers become more familiar on the
A chemical scene, a new emphasis on science appears,
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bringing with it a new area of professional opportunity. The emphasis is through the process model-a mathematical description of an operation quantitatively relating all the process variables. The new job description is that of process model scientist. Mathematical models are available or readily developed for a variety of commercial enterprises such as libraries, department stores, banks, rolling mills, and electric utility systems. Why, then, is there a process model problem in the chemical industry? Chemical processes, to begin with, are less well understood. They have distributed parameters and are usually described analytically by a matrix containing several nonlinear partial differential equations. T o get around this, the equation properties must be studied, or approximations must be introduced into the model to make the descriptive equations linear. Very few detailed process models are in the literature, and the background of acceptable approximations is limited. Analytical model making must be based on original investigation, on piecing together available bits of information, or on a combination of these. If approximate models are to be used, they will be based on known fundamental principles combined with a statistical analysis of plant operating data. Since the present trend is to seek out process control applications based on the economic advantages of these approximate models, the models and the men who make them can soon be of major significance. The computer manufacturer has to keep several things in mind. After enough process models have been published it may be possible for him successfully to offer computers to the chemical industry as “black box” packages, with the purchaser finding in the literature the model information he needs to make the initial application to his process. Until then, however, each sale will have an accompanying application problem. If the purchaser has not constructed the model in advance, the manufacturer will either have to supply it or forego the sale. The manufacturer with limited application resources will prefer initially to sell computers to companies that have developed models, realizing quick sales turnover while application capability grows stronger. For the user, process models add to his store of proprietary know-how all the knowledge accumulated in developing the model. Even when converted to computer programs, this information is known to only a few employees and a recording tape; therefore is more protectable. But is it, where a processor uses a model supplied by the computer manufacturer? Probably, yes. A process which benefits from computer control based on imperfect models may benefit increasingly as the model is refined and made more analytical. Management, responsible for economic performance, will want to improve the process through a program to improve the model. These model developments within
DIGITAL COMPUTERS AND T H E PROCESS MODEL PROBLEM
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the company will probably soon make the original model obsolete, and any proprietary information from one processor which might inadvertently be available to another processor through the medium of the computer manufacturer would have only a very temporary importance. At the same time a benefit reverts to the computer manufacturer. When the full significance of this feature is appreciated, a number of companies that operate under the policy of holding vendors at arm’s length so that they can learn nothing about the process can be expected to welcome closer cooperation with equipment manufacturers. Whether the manufacturer or the user develops the process model, the development of the model and its improvement, involving very fundamental aspects of chemical science, are giving rise to the control model scientist, a man whose professional career is devoted to scientific model-making for process control application. Several large chemical companies have control model scientists on their staffs. Others will follow as the needs and advantages are recognized. All this portends a new degree of usefulness of fundamental science in industry, readily apparent in the profit picture and significant to both management and the scientist because it draws the scientist closer to the market place. A scientist working in the average university or industrial laboratory is usually months or years removed from the economic effect of his work after he has finished it. A control model scientist, on the other hand, is only days or weeks removed, since his new model is immediately programmed on the computer for trial in the process. The plant becomes his laboratory for evaluating a series of ever more productive models. This rapid impact at the market place provides new and greater opportunities for science to serve the supporting social order.
Carlyle S. Herrick is a Chemical Engineer in the Research Laboratory, General Electric Co., Schenectady, N . Y .
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