IDG Contributor Network: Overcoming barriers: An evolutionary approach to edge computing

Pushing industrial control intelligence to the edge—closer to where manufacturing and production processes are happening—offers tremendous potential for increasing business efficiency and agility. Add in the ability to perform real-time analytics on the plant floor, and the possibilities for optimizing operations are endless.

This is not lost on operational technology (OT) professionals. According to a recent market report by ARC Advisory Group, 91 percent of industrial automation users surveyed said that having better systems and connectivity at the edge will improve real-time decision making. Early adopters are moving aggressively to push intelligence to the edge as part of a larger Industrial Internet of things (IIoT) strategy. So why isn’t everyone jumping on the edge computing bandwagon?

Change equals risk

A major challenge is mindset. Industrial enterprises tend to be risk-averse. Anything perceived as posing a risk of disrupting manufacturing processes will face an uphill battle. This explains why so many plants are filled with aging industrial control systems, including some applications, operating systems and hardware that are no longer supported. For the OT personnel responsible for keeping production lines up and running no matter what, change equals risk.

For some, the connectivity required to handle the flow of data essential to intelligent edge systems also equates to risk. Freestanding systems that run just a single process are difficult to hack, which is why you often find dedicated desktop workstations or servers running a single application or machine. Sure, it’s inefficient, but many OT professionals view this as the price of limiting risk.