PRODUCT QUALITY-CONTROL IN REDUCED DIMENSIONAL SPACES

Effective control of quality variables in high-dimensional processes i s considered. Because of the high dimension of the output space, contr ol of a subset of the quality variables is often practiced, to indirec tly control the entire quality space. An example of this type of situa tion is the control of the full molecular weight distribution (MWD). O ften, indirect control of the MWD, for example, by controlling an aver age of the distribution, is practiced instead. It is shown in this pap er that, as a controller eliminates a disturbance in the controlled va riables (for example, the weight-average chain length), it transfers a nd can possibly inflate the disturbance in the remaining quality varia bles (the full MWD). Therefore, while it may appear that good control is being achieved (the average is at its target), the polymer quality has, in fact, degraded. A simple analysis tool, called the disturbance inflation factor (DIF), is introduced to predict this effect. The DIF is used to predict which manipulated variable results in the best con trol of the full MWD while acting only on a single measured variable s uch as the weight-average chain length. It is further applied to evalu ate if control of the full distribution may be improved by considering other controlled variables, such as the number-average chain length, or other manipulated variables, such as combinations of the existing m anipulated variables. The ideas are illustrated on a simulated polysty rene reactor.