Without a doubt, the most important web sensor is your eye. How many sensors do we have to even detect wrinkling, which may be the most devastating defect in our industry? Only one, the eye.

Of 1,000 web machines, how many are equipped to measure bagginess, which is epidemic in most plants? I doubt there would even be one. Yet bagginess is often easy to see. Of perhaps 100 distinct wound-roll defects, how many can be detected with the eye? All of them, as shown in Duane Smith's Web and Roll Defect book, which has a picture for each. How many defects can be detected by instruments? Perhaps none. Only the risk of a few of those defects is even estimated. An example: Excessive gradient of roll hardness on some grades of paper and film may indicate that that roll should be rejected.

Thus we have the bitter truth. Most web-handling and wound-roll defects have no electronic sensor to help us in quality control or troubleshooting. This handicaps most data-based analysis like statistics or Six Sigma. Occasionally, we will grade severity based on eye and use that as input. More often, we only have binary data based on appearance and judgment. These human-based measurements are notoriously inconsistent with time. Nonetheless, that is what we have—and that is not likely to change much in our lifetime.

This lack of relevant data debilitates many technicians and engineers, because they were taught only how to troubleshoot based on numbers. They were not taught how to observe or even how to pay attention. I cannot count how many times my client said that the timing of my visit was not good because the web was not wrinkling then. However, right before them were the shadows of wrinkles, that if only slightly more severe would be rejectable.

Stated in another way, they only had QA eyes of pass/fail, not the eyes of an observer who is already diagnosing the difficulty and estimating risk. A web that is not dead flat as a sheet of glass can be read much like a “near miss” for an industrial accident.

Operators are not so handicapped. They are visually-oriented. They did not grow up with numbers. They did grow up with eyes and ears, and they sometimes use them. They can tell when things don't look good even before they aren't good. They can do this without the sensors on their machine, which by and large are pretty useless. This is why I prefer to spend my time with the operators; they often have the data needed to unlock the problem, though it can not be expressed in numbers. Provided that they've been paying attention, the only remaining hurdle is communication.

All this is not to say that instrumentation does not have its place. Of course it does, for certain situations. You cannot “see” dryer-temperature variation inside the hot box. Your fingers cannot estimate web thickness as well as lab instruments or scanners can estimate. It's just that if you limit yourself to those sources of data, you greatly limit your ability to troubleshoot problems on your plant floor.

920/725-7671 drroisum@aol.com, www.roisum.com