Pet food manufacturer Iams is using the NWA?Quality Analyst statistical process control package, available from Adept Scientific, to ensure consistency at each stage of the process

When it comes to cat and dog food, The Iams Company is serious about quality. The company uses statistical process control (SPC) and continuous process improvement at each stage of its production. “Our quality system is developed around the whole production cycle,” said Dave Bechtel, Iams director of worldwide quality. “It entails every phase of the manufacturing process: from development to procurement to manufacturing to shipping and distribution to customer follow-up.”

New SPC programmes are first tested and implemented at the Iams processing plant in Aurora, Nebraska, and then rolled out to other plants in the enterprise. The plant is a typical Iams facility, producing 200,000 tons of premium dry cat and dog food each year.

The production process begins with testing ingredients to make sure they conform to specifications. Then the ingredients are placed into bins before being put into mixers. From the mixer they are placed in an extruder and then cut into the sizes and shapes demanded for various products. After cutting, the pieces go into a dryer, where the moisture is reduced to specified levels. External fat and ingredients are then sprayed on and the pieces are cooled and packaged.

At each step, Iams uses SPC to determine whether the process is capable of meeting specifications (in statistical terms, this is expressed as Cpk). Once assured that it can, operators gather routine day-to-day data for trend analysis. From there, SPC efforts focus on establishing tighter and tighter controls to decrease variability.

“We know we’re making progress when line operators are no longer running to specifications, but to targets that were established by our on-site manufacturing process control teams,” said Clint Paisley, quality assurance manager at Iams Aurora.

An example of how Iams uses SPC is to more closely target the accuracy of package fill weights. Underfilling is not an option, both because of customer satisfaction and strict regulatory requirements. Overfilling is one way to make sure requirements are met, but it adds cost. The goal is to get as close as possible to the target fill weight without going under.

During each shift, an Iams operator measures fill weights and plots the data. At shift’s end the data is entered into a statistical software package, NWA Quality Analyst. The software analyses the data and when a new shift starts, gives the incoming operator a statistical profile for the preceding shift: average package weight, the number of measurements below the lower control limit and the number that exceed the upper control limit.

“We provide operators with the information and if they see that a particular product is running outside of limits the process needs to be evaluated,” said Paisley. “We look to run on both sides of the target with minimal variation and not under declared value weight.”

Bechtel said that NWA Quality Analyst enables them to take data and, from a capability standpoint, determine what their systems are able to deliver. “For a long time we used a standard fill weight target,” he said. “Now, with NWA allowing us to talk specifically in terms of data instead of in generalities, we’ve been able to optimise fill weights, generating savings while staying fully compliant. And, as we get more involved, we’re tapping into NWA’s more technical capabilities such as t-tests and regression analysis. There’s room to grow as our quality program develops.”

Iams chose NWA Quality Analyst for SPC data analysis because of ease of use. “I’d been using Excel for SPC, but found it didn’t provide the desired statistics. With the amount of data generated, the files became much too large to handle,” said Paisley.

Using the software, Iams operators can see how the process is performing by using I/R charts and histograms. The software makes it obvious when rule violations of the normal process parameters happen. When violations occur, the causes can be recorded and corrective actions logged. Paisley uses the information to track changes to control limits and machine maintenance.

“With NWA, people no longer have to depend on gut-feel or guesses about how the process is performing,” said Paisley. “They have real data upon which to make analyses and then decisions. This leads to high consistency.”

Paisley praises NWA software for its ease-of-use: “We don’t need complex statistics. We need basic tools such as how to collect data, how to look at standard deviations and simple work instructions on situations that occur. Today, I have operators who can readily pull up histograms and use them to make the process better. NWA Quality Analyst is perfect for that.”

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