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What Is Industrial Edge Computing and Why Is It Important?

Industrial Edge Computing

What Is Industrial Edge Computing and Why Is It Important?

19 Jan, 2020

Growth within the industrial sector has always been spearheaded by the introduction of new concepts that enhanced shop floor productivity. In the late 80s and early 90s, productivity was enhanced by Toyota’s introduction of Lean manufacturing concepts which are still being used today. The millennium brought with it the rise of computing clusters and cloud computing to enhance productivity, but today, with year-on-year productivity growth at an abysmal 0.5% rate, something was needed to jolt industrial productivity from its rut. Enter industrial edge computing.

This article will discuss:

  • What is industrial edge computing
  • The benefits of industrial edge computing
  • Why industrial edge computing is important and its ability to enhance productivity

 

What is industrial edge computing?

Edge computing refers to the deployment of data-handling activities and network operations towards more individual sources of data capture or storage. This means instead of having to access a centralized network segment or the cloud when capturing data, edge computing ensures data can be immediately captured at the edge of a standalone computer, device or equipment.

Bringing industrial applications into the mix, industrial edge computing refers to the process of managing data-handling activities using individual sources of data such as smart edge devices. Thus, in smart factories, IIoT devices, and smart equipment do not have to access centralized cloud platforms when capturing, analyzing, or assessing data. Depending on the importance of the data analysis done on the edge, the information can also be transferred to the cloud for further analysis or integration into a bigger system.

The ability of industrial edge computing to circumvent the cloud when making decisions also comes with diverse connotations which could prove beneficial to manufacturing and other industrial processes in the long run. Some of these benefits include real-time decision-making processes, enhanced security, and increased analytical speed. Thus, the adoption of Industrie 4.0 business models in the manufacturing industry is accelerated.

 

Analyzing the benefits of industrial edge computing

To analyze the benefits of industrial edge computing, take the scenario of an automated guided vehicle (AGV) deployed to deliver materials to multiple workstations within a shop floor. For the AGV to successfully execute its mission, it must be able to collect and process data from the shop floor in real-time to effectively navigate new areas or dodge new obstacles despite challenges such as limited network connectivity challenges or functioning in unfamiliar terrain.

Although the AGV can make use of mobile networks to access the industrial cloud, it will be much more effective and faster if it can handle its computing on-board. This is what edge computing intends to accomplish and this way of computing ensures the AGV stays in sync with its schedule when delivering materials.

The benefits of such a process driven by edge computing are varied and cut across enhancing security, delivering actual real-time business insights, and enhancing productivity. In terms of security, Intel estimates that an automated vehicle will produce approximately 40TB of data after an 8-hour drive. Transferring that much data to the cloud raises hundreds of cybersecurity issues that can be exploited. Edge computing can reduce security challenges by capturing and analyzing the data and making resultant decisions in real-time.

If the data collected by the AGV is routine data about navigation, that data may not need to be sent to a centralized cloud. Whereas in situations where the data is important to enhancing performance, the optimized data can then be quickly transferred to the cloud. This means industrial edge computing can be set up in such a way that an enterprise reaps the benefits of both edge computing and the scalable resources of cloud computing.

When computing costs are being considered, industrial edge computing also provides some cost-reduction benefits. It is cost-prohibitive to transfer large data sets of temporary or unimportant data to a centralized cloud, which is why keeping such data at the edge and discarding after use reduces cost. Edge computing also makes it possible to easily track the performance of individual devices or equipment on a shop floor. This data will help the manufacturer optimize equipment performance while reducing costs and hazardous occurrences.

Edge computing also drives the automation of predictive maintenance initiatives. Smart edge technologies such as sensors, actuators, and controllers can be used to track the health of equipment and the moving parts within it. With edge computing, the machine does not need to communicate with the central cloud before making a decision that will preserve the equipment and reduce downtime in real-time.

The increased visibility edge computing brings to manufacturing also plays a role in delivering the promise of a lights-out factory. If robots, AGVs, IIoT, and manufacturing equipment can make instant decisions, the need for human influence on shop floors will be reduced. This will also lead to a reduction in shop floor accidents and the occasional downtime that occur due to human fallibility.

 

Why industrial edge computing is important to Industrie 4.0

The highlighted benefits already showcase some of the reasons why industrial edge computing is important to manufacturing processes and automation but it still overlooks brownfield facilities. The ability to integrate smart edge technologies in brownfield facilities makes it possible to collect the data needed for edge computing. Once data can be collected and computed at the edge, even dumb machines can be automated and taught to make real-time decisions, thus accelerating the adoption of Industrie 4.0.

The low latency, high bandwidth and trusted computing that comes with industrial edge computing can power an ‘always on’ ecosystem within any facility. Edge computing’s ability to deliver an ‘always on’ ecosystem – where even dumb equipment can produce and manage data on the edge – will drastically reduce downtime in brownfield facilities while increasing productivity and the operational capacity of older equipment.

 

Conclusion

Industrial edge computing is poised to drive the future of manufacturing and increase its abysmal productivity growth rate in the near future. This will accomplish alongside cloud computing as they both have roles to play in ensuring real-time computing is brought to the shop floor. Thus, edge computing and cloud computing can be compared to the way you use your two hands. Here, industrial edge computing handles lesser workloads at the device or equipment level while cloud computing handles larger workloads to enhance productivity.

 

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