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Abstract

Control of many chemical processes is optimized using compositional data, rather than physical properties, as the means of control. Using near infrared spectroscopy as the analytical tool affords the opportunity for on-line measurements in real time. A calibration set of NIR spectra bounding the acceptable process space within which a particular property is to be controlled is obtained by conventional means. Applying a multivariant statistical method to the calibration set affords a method of identifying the most important characteristics of the set which governs the controlled property, and is inherently related to the composition of the process product. Control then is effected by using only a small number (2-4) of such characteristics, which can be determined quickly and simply from the measured spectra, as the control criteria to be applied to the process as a whole. The result is a very effective way of controlling a complex process using only 2-4 non-obvious criteria objectively determined from a calibration set and which can be applied in real time and virtually continuously resulting in a well-controlled process whose product composition is (ideally) invariant.

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First Claim