The Profinet of Things

As Industry 4.0 and Industrial Internet of Things initiatives become larger priorities for manufacturers worldwide, the organization behind Profinet announces its “Profinet of Things” theme aimed at data access, uptime, and openness.

Demonstrating its readiness to take part in one of the biggest trends to sweep across industry in the past decade, PI North America, the organization supporting Profibus and Profinet technologies in North America, officially announced its “Profinet of Things” theme during its annual general assembly meeting in Scottsdale, Arizona, last week.

“Profinet has come to the forefront as a critical piece in the Industry 4.0 and Industrial Internet of Things puzzle, as evidenced by Industry 4.0 naming Profinet and OPC UA as its preferred communication protocols,” said Michael Bowne, executive director of PI North America. “That’s why a theme [for us] going forward will be the ‘Profinet of Things,’ revolving around data access, uptime, and openness. It’s also what we’ve seen here at our general assembly meeting this year. End-users are interacting with OEMs and automation vendors and the fascinating discussions highlight not only the breadth of the protocol, but also its depth.”

For those familiar with PI North America, the 2015 general assembly meeting marked a time of change, as Mike Bryant, the organization’s long-time executive director, announced he would be moving into an executive director emeritus role as Bowne transitions into the PI North America executive director’s job. Commenting on the change, Bowne said, “On a personal note, it's a great honor to begin transitioning into the executive director role. Mike Bryant is a driving force behind the adoption of Profibus and Profinet in North America and around the world. I look forward to his continued guidance and oversight as we continue to grow the organization in the coming years.”

During the meeting, Bryant noted that the technology training sessions held by PI North America reflect a clear industry trend toward Ethernet. Seventy-nine percent of the people signing up for training this year signed up for Profinet training, meaning that only 21 percent signed up for Profibus training, reinforcing the notion that industry is shifting quickly toward Ethernet as the de facto plant network of choice in addition to its requirement in Industry 4.0 and IIoT initiatives.

“With the entire automation world focusing on Industry 4.0 and IIoT,” Bryant said, “PI North America looks forward to introducing more support and education of Profinet without abandoning the installed base of Profibus products. We have to focus on where Profinet fits into IIoT, but we will never abandon our Profibus legacy business, we’ve got a whole lot of installed devices out there that we will support for years to come.”

Though Bryant notes that Profinet is only one piece of the IIoT pie, he adds that it serves a “foundational” role. “If you don’t have it, you can’t move your data up the chain to SCADA, cloud storage, ERP or MES,” he said.

With data at the center of Industry 4.0 and IIoT—whether it pertains to the collection, analysis, or the decision-making aspects of it—many across industry remain unsure of what steps to take first. As one attendee at the general assembly meeting commented, “I’ve got so much data I could send somewhere, but I don’t know who to send it to or what they would do with it.”

“If you think you are drowning in data now, wait until 2020,” said

Raj Batra, president of Siemens Digital Factory business, during his presentation at the PI North America general assembly meeting. “Smart, connected products are forcing us to redefine what a product is and how it’s used.”

Batra quoted 2015 research from Industrial Internet Insights, which reported that:

  • 87 percent of respondents say big data analytics is among their top three priorities;
  • 42 percent say its their number-one priority; but
  • Only 5 percent have implemented a big data strategy.

These results echo responses to a recent Automation World study on big data, the results of which can be viewed in the article “Big Data Dilemma: Finding the Hidden Value”.

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