Smart factory concept begins with IT/OT convergence

Smart factory concept begins with IT/OT convergence
The smart factory concept has taken hold in manufacturing facilities throughout the world amid the IIoT trend, and IT/OT convergence will play an important part in this regard.
 
That was the point raised by ABI Research in a recent whitepaper titled How to Embrace IT/OT Convergence.
 
With the so-called Industrial Internet of Things (IIoT) or Industry 4.0 becoming more popular, more and more manufacturers seek to sensorize their equipment and analyze related data to achieve further efficiency and productivity. This in turn results in a convergence between a factory’s operationa and IT departments, which had in the past worked in silos.
 
“Until Industry 4.0 and the Industrial Internet of Things (IIoT) emerged, OT rarely had to work with networked technology. Now, IT systems must have access to physical assets, shop floor workers must have access to analytics, and all parties must communicate and solve problems together. The IT/OT silos are now converging,” the whitepaper said.
 
Such convergence, however, doesn’t come without challenges. Interoperability between IT and OT systems can be a headache, and differences of opinion between the two departments can add to the chaos.
 
“A factory manager buys the sales pitch of an IIoT solution company and slaps some sensors on the factory equipment. The IIoT company sets up some gateways and tells the factory manager that to really optimize the solution, the factory should use a new IIoT cloud software platform. The factory manager goes to his IT department, which immediately erupts in a panic about security certifications and data ownership, leaving both sides upset and anxious about how to proceed and about the cost of a systematic and procedural overhaul,” the whitepaper said.
 

Strategic recommendations

 
But according to the paper, the increased efficiency and productivity resulting from this convergence will ultimately prove to be beneficial in the long run. ABI then offered the following recommendations for ensuring that the IT/OT convergence is carried out in a smoother, more effective manner.
 
  • Drive alignment and integration from the bottom-up with IT liaisons and top-down with a Chief Digital Officer (CDO): According to ABI Research, companies need an individual executive to own and hold responsibility for the IIoT strategy and to promote communication. At the same time, the company can put IT liaisons on every OT team to increase communication and the exchange of ideas between IT and other departments, it said.
  • Train IT liaisons to work with other teams: IT liaisons should not only work with OT teams but every business team, and for them to effectively work with these teams, employers must train them to focus on their specific roles, the paper said.
  • Connect things to edge nodes to control centers to the cloud and then to the ecosystem: According to ABI Research, IT/OT convergence should start at the edge, not in the cloud. “Cloud computing still provides valuable deep learning and interdepartmental integration capabilities, but IIoT specialists need to reverse their thinking from the cloud to the equipment and start thinking about operating at the edge before reporting to the cloud,” it said.
  • Experiment with open, interoperable platforms at the edge that connect to a single open, interoperable platform in the cloud: Companies must use a single cloud infrastructure to best integrate with all departments, but the cloud platform should work with the platforms and apps that work best at the edge, the whitepaper said.
  • Scale one platform and one application at a time: According to the whitepaper, companies should maintain a single IT architecture but launch IIoT applications separately. "This allows the company’s digital/physical specialists to focus on obtaining a ROI and making each application profitable and fully integrated before moving on to the next one," it said.
  • Increase transparency between departments: Not every department needs access to every piece of data, but try to optimize the IT systems and single cloud platform so that when an IIoT solution spits out an actionable insight, that insight goes to the right places, the paper said.


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