Wyeth says measure first, then automate

Wyeth designed its two new high-speed liquid filling lines with networked exchange of information as a high priority. Published OEE reports are routinely available.

COMMUNICATIONS ARCHITECTURE. A desire for better metrics on manufacturing processes and a more automated approach to getting the
COMMUNICATIONS ARCHITECTURE. A desire for better metrics on manufacturing processes and a more automated approach to getting the

What better opportunity to implement new and improved controls technologies than the installation of a brand new packaging line? So when Wyeth Consumer Healthcare, a leader in nonprescription medicines such as Advil, Robitussin, Dimetapp, Chapstick, Centrum, and Preparation H, laid the groundwork for not one but two new liquid filling lines in its Richmond, VA, facility, management viewed it as a great opportunity to get significantly better at data acquisition. A key goal was to be able to calculate Overall Equipment Effectiveness. Typically known by its acronym, OEE is a measure of three machinery factors: availability, performance, and quality.

“The project sprang from a desire for better metrics that could be more automatically generated where our manufacturing processes were concerned,” says Brad Neuroth, controls engineer at Madison, NJ-based Wyeth. “Remember, these were two brand new packaging lines, which were designed for higher speeds and greater throughput. We wanted to be sure we got the output we'd paid for. On the older lines we just didn't have the best means of tracking downtime, faults, or OEE. So with the start up of these two lines, we wanted to automate a lot of data collection that, in the past at least, hadn't been done all that well.”

While maximizing asset utilization was the key goal, it's interesting to note that a secondary goal was more personnel oriented.

“Our compensation process includes a consideration of line performance,” says Neuroth. “The feeling was that if we had better methods of measuring, we'd be better positioned to provide the proper compensation.”

Neuroth doesn't identify the line integrator behind the two new packaging lines or the suppliers of specific machinery, software, or automation products. But even without supplier names and Web sites, Wyeth's story is worth recounting because it's a vivid reminder of how important data acquisition has become in today's packaging scene. Part of this story Neuroth shared with those who attended the May 24th Packaging Automation Forum in Chicago, sponsored by Packaging World and Automation World. In a follow-up telephone interview a month or so after PAF, Neuroth elaborated on data acquisition strategies identified and lessons learned as the two liquid lines were designed, installed, and commissioned.

Essential layout

The diagram here shows the essential layout of both lines: unscrambler, filler, capper, dosage cup placer, labeler, cartoner, overwrapper, and case packer. It also shows the network of communications links that tie the line together. The goal from a data acquisition standpoint was to monitor line performance and communicate that performance to a metric server.

“Our automation goal was to measure performance, not to improve it,” says Neuroth. “We wanted to know where we stood with OEE, partly because a focus on that kind of operational metric is a growing trend in our industry. We wanted to measure first, then automate second. That way, our future automation projects can be evaluated more effectively and we'll be able to tell what the benefit is once the automation implementation is complete.”

On whom did Wyeth rely when it came time to bring performance measurement to the two new lines?

“There were a number of places to look, “says Neuroth. “We had a history with some of the packaging OEMs who are prominent in the lines, and some of those OEMs had relationships with each other and with the integrator we ultimately hired to tie the OEM processes together.”

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