By Jim Montague, Executive Editor
What if you were the hero in the new Prince of Persia movie and had the magic dagger that could take you back in time just a minute or two so you could correct any problems? Well, besides being a fantasy warrior, you'd also make a heckuva plant engineer—assuming you had the right data to fix your problems and knew how to apply it. So, while it's too bad time travel isn't possible outside of Hollywood or other fictions, having lightning-fast access to more useful information can get you pretty danged close—especially in batch applications.
For instance, Plasticolors (www.plasticolors.com) in Ashtabula, Ohio, is a specialty color house that creates all kinds of colorant and chemical dispersions that plastics, coatings, inks and other producers use to help their manufacturing clients create an endless variety of products. Plasticolors uses high-speed-energy mineral mills to grind dry pigments, such as metal oxides and other dry chemicals, into resins to reduce particle size, and then adds dispersants to balance and stabilize the mixture. These are delivered in 1-lb. to 5000-lb. containers to its plastics customers and indirectly their clients, who make automotive parts, ladders, flooring, colored urethanes and other products.
Of course, the primary focus of all these coloring efforts is accuracy. So Plasticolors operates an extensive lab to match specified color requirements and maintain consistent product quality down the line. Because these processes weren't very high-volume historically, Plasticolors' staff usually did them manually over the years. However, that situation changed about five years ago, when one of Plasticolors largest customers requested larger shipments of colors in its smaller containers of just a few pounds each. These colors typically go to high-volume makers of fiberglass and epoxy-based flooring.
"There's a lot of pressure on us because we have to find and buy good raw materials in volume. Since the recent economic downturn and recession, our customers and their clients are stocking less on their shelves, working much more lean, but then also needing to make money as soon as they can," says Rick Georgia, Plasticolors' plant engineer.
Adapting to Automation
Because of this heightened demand, Plasticolors decided to automate the machine it built and operates to fill its SoluPak pre-weighed tubs of liquid pigment (Figure 1). Georgia designed and built the pinch valve on the machine. He reports that it meters material out of a funnel and into the pre-weighed, 1-quart-size packages, and these need to maintain consistent weights of ±1% at minimum. "Operators used to manually open and shut the machine's valve all day by hand, but it was an ergonomic hazard because of the repetitive stress, and most operators could only get close to 1%," says Georgia. "We used to have one operator, who worked here for more than 20 years, and she alone could get to within 1% manually. But even she acknowledged that she couldn't do it consistently. Even so, we were able to meet our customers' needs for years, and yet we still wanted to get better. So when we read an article about P&G and Mettler-Toledo's (www.mt.com) Q.impact (Q.i) system, we thought it might work here too." Plasticolors was acquainted with Mettler-Toledo's lab scales because it used them for many years to handle intricate weighing of scaled-up batches.
Figure 1. Plasticolors' filling machine uses Mettler-Toledo's IND780 Q.i material transfer controller with the Q.impact software application to increase throughput and maintain consistent ±1% accuracy each time it fills 1-quart SoluPak tubs with liquid pigment dispersion.Michael McCormick, Plasticolors' coatings industry manager, adds that, "Our company has always made custom solutions, but Q.i enables our SoluPak packaging to meet the needs of our customers while exceeding their expectations. We have operators with a good feel for the process and a vast amount of experience who can target 1% accuracy, but the Q.i software lets any operator of any experience level run this filling operation. This means we don't have to rely on any one person, and it lets us be more consistent."
Limits of Dribbling
To better understand what makes predictive-adaptive material transfer control quicker and more accurate than traditional filling, weighing and reacting, it's first important to understand how the traditional way works. Typical material transfer in most batching applications uses some type of dribbler procedure that fully opens the valve and then begins to close and slow the flow before the target weight and final cutoff is reached. Some filling machines use a second, smaller valve to do this dribbling task. However, Georgia explains that the problem with dribbling is that it takes more time to achieve sufficient accuracy—about 12 to 15 seconds in most cases.
Dribblers also can't account for material added after the cutoff is reached and the order is given to shut off flow, but before the valve actually closes, and these amounts can add up to inaccuracy, poorer quality product and lost profit.
"Most filling machines just read from the scale, OK the cutoff and shut off the valve almost completely to dribble the rest of the fill. Or they choke off the main flow and then open another little internal valve to dribble the rest of the fill," says Georgia. This traditional, multi-speed method also means more lines, pumps and equipment than Q.i's single-speed control (Figure 2). Likewise, because they only seek to meet assigned weights, most filling devices can't account for changes in flow caused by changes in ambient temperature, humidity or other environmental shifts.
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."
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.
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."