Batch to the Future

Pigment Dispersions Manufacturer Plasticolors Uses Predictive-Adaptive Material Transfer Control to Continuously Tighten the Accuracy of Its Filling Batches on the Fly

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Similarly, while most filling devices respond to signals from their load cells or other weighing sensors, they usually can't respond to changes in head pressure as the vessels they're filling from begin to empty out. Because of these limits, consistently performing precise fills—but also doing it fast—has been nearly impossible for many years. As a result, users often decide to err on the side of slightly overestimating and overfilling, which can add up to large losses in material and profit over time—not to mention risking poorer quality that may adversely affect subsequent processes.

Scott Haimerl, Mettler-Toledo's product manager for Q.i, emphasizes that Q.i in its IND780 controllers won't fix mechanical process problems, but it does handle natural process variations that are difficult to control with traditional filling devices. "Most people fill in a feedback mode, adjusting the material cutoff after an overfill or underfill is completed. As a result, targets are raised to minimize the chance of unacceptable underfills. Q.i masters the material transfer process from pre-feeding condition checking to filling by learning about and building a model of every feed."

Better Math = Better Response

To move beyond older filling machines, Georgia reports he and his colleagues first designed a platform with a pinch valve with pneumatic cylinders that pinch the rubber membranes through which the pigments flow, and then integrated Q.i's application initially as part of Mettler-Toledo's Jagxtreme Q.i material transfer controller about five years ago. Most recently, Plasticolors integerated its new valve platform into Mettler-Toledo's beta test of its new IND780 Q.i material transfer controller.

In addition, Mettler-Toledo sent two technicians to help Georgia and the Plasticolors team fit Q.i and its controllers into their filling machine and tailor the controls into their consecutive, continuous process. The system developed has many added parameters that can be set, such as how the filling device recognizes containers, opens and fills them, and then calls for them to be removed. In addition, many of these tasks can be done automatically on even higher-volume lines that use PLCs or DCSs. "Mettler-Toledo helped us set up the filler so the presence of the container triggers the start of the fill, and no manual switching is needed—beginning or end," says Georgia. He adds that Mettler-Toledo's technicians also helped set up material pathways for Q.i in the Jagxtreme and later in IND780 Q.i. These pathways are the timing window when a container can be filled. They're determined by the material's weight, flow, viscosity and other factors.

Basically, Q.i's software contains patented, predictive-adaptive control (PAC) algorithms that calculate the "spill" material in the air space between the valve nozzle and the tub on the scale, which happens during the small slice of time between when the valve cuts off and when the last bit of material lands in the tub. Q.i accomplishes this feat by building a mathematical model of each material feed, and then calculates when to cut off the valve to precisely hit the target weight. This takes roughly 7 to 9 seconds with Jagxtreme Q.i and as little as 5 to 6 seconds with the IND780 Q.i. Then, once Q.i identifies and saves an ideal profile, it will keep using it for subsequent fills. However, it also keeps monitoring these fills and flows for each material feed and keeps making adjustments as needed. For example, Q.i can adjust its valve cutoff by as much as 25% as it goes through a series of fills to compensate for loss of head pressure as the volume in its filling machine's supply tank decreases.

"When setting up a filling process, Q.i asks for the target weight and then observes the flow. However, once the signal comes in to cut off, there will still be some product in the air, especially when we're filling a 1-quart can from a 2-in. valve," explains Georgia. "For example, if a spill is 3 ounces over a 4-lb. fill, Q.i recognizes that the valve needs to be closed sooner, and calculates how much dispensing time to trim. Q.i will check the flow rate with each dose, adjust the cutoff accordingly to stay in its target window and will repeat this process until the last can."   

Faster Accuracy

At the same time, IND780 Q.i's ability to adjust the valve's cutoff allows Plasticolors to maintain the ±1% accuracy it needs for each of its SoluPak tubs. "This is like pouring a half cup of water between two glasses and being able to hit that ±1% mark every time," says Georgia. "Whatever spill hits the scale, Q.i calculates the new shut off in 6 to 8 seconds, and the next fill is even closer to the target. I've never seen Q.i take more than two subsequent fills to hit its target."

In addition, Georgia reports that IND780 Q.i has increased the accuracy of Plasticolors' 4- to 8-lb. containers by 25% to 50% per can. This means less fatigue for its operators, reduced material costs and better quality delivered to its end users. In fact, in Plasticolors' quart-filling program, a series of 200 1-quart fills was conducted, and IND780 Q.i was on target for more than half of the fills, and 98% of all the fills were within ±1% of the target (Figure 3). Haimerl adds that these results confirmed Mettler-Toledo's theoretical calculations about how Q.i was going to perform. 

"IND780 Q.i on our 1-quart can line will pay for itself in about one year. I've seen and investigated a lot of filling machines, and whether they're manual or automatic, none work as well as IND780 Q.i. I think it can be used on any on-off filling application," says Georgia.

Haimerl adds, "We explain that Q.i is a feed-forward technology, and so it can improve throughput up to 30% and improve material feed accuracy up to 90%."

Also, besides being about 2 seconds faster than its predecessor, IND780 Q.i is reportedly better tuned and more accurate because it makes greater use of software/hardware advances combined with the application experiences from the first-generation Jagxtreme Q.i. And, while programming material pathways in Jagxtreme Q.i was a bit challenging, IND780 Q.i automatically knows which pathway to use.

"IND780 Q.i is also more user-friendly for the operators because it's a lot simpler to set each batch," says Georgia. "A few seconds might not seem like much, but it adds up when you're filling 1000 cans of product. That's almost an entire hour saved."

McCormick also confirms that IND780 Q.i is saving  Plasticolors' filling machine and operation huge amounts of time. "We used to fill about 500 quarts per 8-hour shift, and now we're filling about 1500 quarts per shift," says McCormick. "Most importantly, we haven't had any container fill weight complaints with this system. Our production was manual for a long time, but Q.i helped us automate and become more efficient. We're running our filling process leaner, which is really helping as business picks up."  

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