Benchmark Your Extruders For Quicker Processing Fixes

Not recognizing output reductions and resolving them quickly can cost a lot of money. Benchmarking your machines will help.

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I often visit operations where the extruders are operating well below the equipment’s original capability. Generally the output has degraded over a period of time due to a series of “one-time” production upsets that never got completely corrected. Not recognizing these and resolving them quickly can cost a lot of money. This issue should have the attention of management on a daily basis.

Once the decrease in output is recognized, one of the easiest ways to determine the cause is to reset the extruder to a “benchmark.” A benchmark should be established for each extruder and each product, and the written record should be kept for comparison anytime output falls below the norm. A good benchmark analysis should include every aspect of the extruder that can be observed and documented, such as which zones are calling for heat or cooling frequently, the temperature of the feed throat, the melt quality and stability, specific output, drive load, etc.

Even though some extruders are equipped with elaborate data loggers, these devices do not monitor all aspects of the extrusion operation. Establishing a true benchmark goes beyond simply printing out a “snapshot” in time from the data logger and requires some additional visual observation by an experienced person.

Since the moving parts of the extruder are made almost entirely of steel, it is not susceptible to sudden changes. I‘ve actually heard some say—half kidding, I hope—that their extruders have a “personality” and occasionally act up “out of spite.” Trust me on this: Extruders don’t have mood swings, and there’s a logical and scientific explanation behind every output change.

Some wear may occur over extended periods of time, but in most cases that takes years before it starts to affect output rate. Consequently there is no way to explain a sudden loss of output except that something else has changed. If the screw is turning at the speed shown on the benchmark, then it should have the output shown on the benchmark. It should also have the same melt temperature, amp draw, head pressure, and barrel heat/cool response and every other observable characteristic. By referring to the benchmark data, you don’t need to guess what the output used to be or how the extruder was set up.

Using the benchmarking approach saves a great deal of time in troubleshooting, and it can be done without a lot of physical work. Simply resetting everything to the benchmark conditions will often quickly reveal the problem area. In this analysis we’re not after how it works, but only what has caused the change in performance.

When I say, “Reset everything that can be possibly reset to the benchmark settings,” I mean everything, including barrel temperatures, downstream equipment temperatures, suction pressure or head pressure, polymer mix (virgin/regrind/additives), feedthroat cooling, screw cooling, screen packs, etc.

Once that’s done, look for any differences in melt temperature, melt quality, amp load or drive load, stability (surging) and temperature-zone response to get clues as to how they could result in a decrease in output.

For example, if you find the drive amps or motor load are lower than the benchmark level at the benchmark screw speed, you might first assume that not enough material is entering the screw or that the material has changed. Look for any of the following causes:

•Something stuck to the screw in the feed section.
•Obstruction in or above the feed throat.
•Change in flow of screw or feed-throat coolant.
•Change in additive package or regrind.
•Change in a zone’s heating or cooling cycle (particularly in the first zone), indicating a loose thermocouple, burned-out heater element, or stuck cooling valve.
•Lower temperature of the feed material.
•Polymer change.

This is only a partial list but covers some of the more likely causes of a change in drive amps or load. The point is to go back to a documented condition with every setting and then see what has changed to get clues as to what’s really causing the problem. 

To correct a processing issue, some operators start changing every setting until they get the line to run again, even if they succeed at a much lower output. However, that chaotic approach makes everything so convoluted that it becomes difficult to see the real problem, as the new settings may be “fighting” one another and completely mask the original problem. Benchmarking often simplifies the search for a solution.

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