Actionable analytics key to Rockwell Automation’s smart manufacturing portfolio
Great Lakes Brewing Company worked with Rockwell Automation to connect production machinery and provide workers with the data analysis needed to improve operational efficiencies as part of a digital transformation using industrial internet of things solutions to focus on smart manufacturing. Brewery staff can access data insight by talking to Shelby, an app, built on the Microsoft Bot Framework, that uses natural language processing to help quickly identify and solve equipment problems.
John Blystone, electrical and control supervisor at Great Lakes Brewing, said Shelby enables “us to tap into a wealth of existing data to solve problems very quickly.” He called the bot–think Siri except specialized for smart manufacturing–“instrumental in our transition to a more connected plant floor.”
Blystone tied the digital transformation initiative into the company’s mission of providing high-quality beer. “We are relentlessly focused on quality–from the ingredients we use to our production process and beyond. Adding advanced analystics and hardware diagnostics to our factory floor allows us to continue fulfilling our quality commitment by giving us more meaningful insight into our production equipment.”
Specifically, Great Lakes Brewing Company is using Rockwell Automation’s FactoryTalk Analytics for Devices. The appliance captures data from an industrial network then converts the information into a “health and diagnostic dashboards,” according to the company. If there’s a problem, the system can send “action cards” to engineers’ smart phones or tablets.
In addition to supporting the Shelby app, FactoryTalk Analytics is designed with a focus on “device interactions,” which the company describes as enabling “these devices to start becoming system aware, gaining an understanding of device interactions. Understanding the devices allows a higher level of analysis to be performed. For example, the system feed can find and display issues that would normally be very hard to determine by checking each device, but since we know about each device, systemic issues can be identified and alerted on.”
