Munich’s annual Oktoberfest is rightly regarded as a bacchanal with 6.3 million of your closest drinking buddies, but there’s also a county fair component, with dozens of antique tractors and carnival rides like Eva’s Trip to Paradise.
An early 20th Century tilt-a-whirl without the whirl, Eva’s Trip is powered by its original 11-hp Siemens motor, in service since 1939. The Germans call it a roller coaster, but compared to the thrill rides elsewhere on the fairgrounds, it’s a tame relic.
A similar analogy applies to the machines that make food. Mixers, ovens and even robots have the same functionality today as they did decades ago, but automation advances create a night-and-day comparison in terms of performance. And the best, as they say, is yet to come.
The programmable logic controller is the automation equivalent of Eva’s Trip. No automation vendor will say it out loud — they collectively sell millions every year — but the PLC is obsolete technology. Sure, it provides the logic needed to safely and efficiently run a machine, and its industrial hardness is unquestioned, but PC-based controls are essential in the era of Big Data.
The Achilles heel of automation is loss of flexibility, an easy trade-off when production schedules are static. The trend in food and beverage is in the opposite direction, points out Eckard Eberle, CEO of process automation at Siemens Process Automation in Nuremberg, Germany. The flexibility challenge is further complicated at companies with multiple facilities, none of which is ever identical. That works against operational efficiency.
Extracting data from sensors and field devices as well as controls is well and good, but unless it can be converted to useful information, the effort is wasted. Collecting data isn’t hard: Siemens’ Craig Nelson, senior product manager-motion control, cites the example of a manufacturer who currently consolidates 30,000 data points a minute from its facility. “People who are on the leading edge of the digital factory view data as their competitive advantage in asset utilization, waste reduction and peak-demand shaving to reach the optimal point to produce,” says Nelson.
The data beast drives supply chain optimization. The Barilla Group recently launched an experiment that matches raw material genealogy with product serialization. Working with the Italian division of Cisco, Barilla is printing QR codes on farfilla pasta and tomato and basil sauce containers sold in Italy.
By scanning the code with a smart phone, shoppers are linked to a website where details on where the raw materials were harvested, where the grain was milled, which plant processed it and when the finished good was distributed. The “digital passport” embedded in the code ostensibly advances food safety and answers the “where did this food come from?” question posed by consumers -- although the more significant advantage may be the supply-chain visibility it should provide Barilla.
“The Internet of Everything changes the way we farm, produce, distribute and consume food, making it more transparent and therefore safer,” Agostino Santoni, CEO of Cisco Italia, maintained in a prepared statement. But the pilot project is really a baby step in the more ambitious goal to track the more than 1,000 raw materials Barilla sources, all the way from the farm field to the supermarket. Data manipulation on a massive scale will be required, and farfilla and sauce are the shakedown test.
Big Data and its sister, the Internet of Things, also play a central role in another Cisco project involving Sugar Creek Packing Co. , Washington Court House, Ohio. The company recently commissioned a brownfield project in Cambridge City, Ind., a facility acquired from a bankrupt food processor. Harvesting large amounts of data and feeding it back as actionable information was considered essential for establishing a high-performance work team structure at the new plant, explains Ed Rodden, chief information officer.
“High-performance work teams are quite different from what you see in traditional meat processing facilities, where top-down management is typical,” says Rodden, The semi-autonomous teams work with little supervision, with production, maintenance and HR issues handled by team members. If they are to hit their production targets, they need meaningful feedback. Video monitors with KPI numbers are insufficient.
A sous vide cooking system is the centerpiece in Cambridge City. “That’s a disruptive cooking technology and a highly automated system, with hundreds of sensors to control the process,” Rodden says. To access the data, team members use a Cisco mobile app called Jabber, “essentially an IP phone,” he adds. Conventional cell phone coverage in an industrial facility is spotty at best, and installing a booster system would have added $300-500 million to project cost. Jabber radios essentially function like a desk phone and integrate easily with plant software.