Myth: Partial Least Squares Calibrations Last Forever if Done with Modern Stable Instruments!
I n the "old days" of NIR, some instrument drift and seasonal variation was acceptable (as frankly there was a notable lack of options) but it was also understood that "every now and then" calibrations, of course, had to be updated or adjusted. Whether the specific reason was, for example, the amount of sunshine on the grassland changing the chemical composition of the feedstock analysed by NIR, or the analytical instrument was subjected to a replacement (a big change) or just suffered a little change in optical response (drift) was not so important since one had to update the calibrations anyway. With the introduction of modern instruments with virtually no drift, indeed often with awesome stability, many users now seem led to believe that a calibration will last forever. Touche this is partly true, at least for clean mixtures of pure chemical substances as widely used, for example, by pharmaceutical and chemical manufacturers and producers. For applications involving products of natural origin, the situation is, however, different and all too often still a serious matter. The easy way is, as always, tempting: calibration curves are put together at the start of the project and great performance can often be achieved certainly in the beginning (we here, of course, assume that all fallacies of using cross validation in this context have been thoroughly avoided) Then calibrations are implemented in instruments and for a while everything seems right. What is sometimes unfortunately forgotten, even in this day and age of "super stability" is that nature, and not least process operations, come with less than this awesome stability, with the inevitable consequence that all calibrations (validated well or validated badly) will eventually diverge and start to lose prediction power. When an instrument QC plan and a control chart are not followed strictly, one will likely only find out when it is all too late. A fast, NIR based analytical method is truly a valuable and very powerful tool for a process operator. It allows fast and accurate adjustments of recipes and process settings. In contrast to this desirable "fact" is another fact: if the NIR analytical system is not kept on a short leash with a valid, robust QC setup, fast methods can unfortunately turn out to be a fast way to get all too expensive "help" "Trust is good, control is better!" This saying, allegedly attributable to I. Stalin in relation to managing a political movement, has a less contentious application in the PAT arena. In Figure 1, we show a typical example of a control chart showing a long stable period (good) but with a clearly visible twist in the tail something is indeed happening as regards analytical agreement with the lab in the very last time period, actually only affecting the last two (or three) weeks. A control chart is supposed to allow the process operator to react sensibly, rationally, i.e. by analysing the situation and, if andwhen necessary, adding new "needed data" to the calibration. But before rushing to the task of adding such new data to the calibration (the deviating data in Figure 1) one must always keep an open mind and acknowledge that the control chart simply identifies a difference, not necessarily a valid cause for calibration updating. Pick your words with some care when approaching the laboratory, but it could, for all we can read from the chart, be the lab values that are on the run not necessarily that the process is drifting out of specification The "needed data" above is new data that truly represents the process or other chemical/physical changes that have taken place over the last period and which are not currently in the calibration model. If control samples are not taken regularly, i.e. irregularly or not covering the process adequately, the "needed data" is not available and hence cannot be added to the model. But we can do the second best thing and add data from "now" but the special situation(s) 1.0 0.5 0.0 0.5 1.0 1.5