Industrial edge computing and cloud computing can help motion control, CNC and other applications by providing higher-level analytics for smart manufacturing applications as CNC processors focus on tool path and motion control. Control Engineering interview with August (Gus) Gremillion, Siemens, discusses edge computing advantages. See Siemens edge computing video interview for more.

Learning Objectives
- Define edge computing and cloud computing.
- Understand how edge computing helps industrial implementations such as motion control and computer numerical control (CNC) applications.
- Learn how industrial edge implementations can apply analytics and other functionality to motion and CNC applications so the CNC can focus on what it’s designed to do.
Industrial edge for CNC insights
- Edge computing and cloud computing, applied to industrial applications, can help motion control, CNC and other applications.
- Industrial edge implementations can provide machine tool applications with higher-level analytics for smart manufacturing applications as CNC processors focus on tool path and motion control.
Using an industrial edge architecture helps manufacturers keep pace with digitalization to help create the digital factory of the future, according to a Control Engineering video interview with August (Gus) Gremillion, Siemens digitalization solutions consultant, who discussed advantages of implementing edge computing, especially for machine tool applications. Gemillion studied mechanical engineering in Texas A&M University and has worked at Siemens about 5 years on motion control, drives, computer numerical control (CNC) and machine tool digitalization, helping companies implement Industry 4.0 strategies.
The edge computing interview:
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Defines edge computing as it applies to industrial automation and controls implementations.
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Explains how edge computing differs from other computing options typically used for industrial automation and controls and when edge computing options can be used instead of other controller or computing options.
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Covers how Siemens edge computing differs from other edge computing options.
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Provides projects and useful metrics for edge computing along with other advice.
Information below from Siemens explains more edge architectures, edge computing, and applications for motion control and CNC.
Edge computing, cloud computing defined
The term “edge computing” means shifting computing power to the edge of a network. With traditional local computing, devices are installed and set up once. Data transmission is mostly performed through local networks or external storage media. Updating devices often requires information technology infrastructure and involvement, which is why it is rarely done.
Cloud computing is the opposite, where data is transferred to a central data center, processed, and the result re-imported. While the cloud’s data center is powerful, the potential volume of data is restricted by the connection’s bandwidth, meaning it is impossible to use the cloud to all process all generated data.
Edge computing technology is an interface between local and global data processing. A powerful industrial computer is located at the machine, helping to process data streams. It also functions as an interface with the cloud, which will now be supplied with processed data, decreasing data traffic. Machine-oriented processing effectively uses high-frequency data that permits only a short check-back indication time (latency).
Computing at the edge for industrial applications, motion control, CNC applications
An industrial edge digitalization platform is much more than hardware. Highly-refined analytics software helps expands existing automation capabilities to include machine-oriented data processing for manufacturing companies. Applications are managed and installed via the cloud.
This gives the industrial edge has an advantage over local networks because applications can be updated at any time without intervening in the production process. Direct connection to the cloud also allows an industrial edge architecture to upload processed data directly.
Machine tools generate up to 2 MB of process data per second. Uploading this data to the cloud from several machines is impossible. Intelligent algorithms can reduce the volume of data, turning big data into smart data. An industrial edge architecture combines local, efficient data processing in automation with the advantages of the cloud.
Industrial edge implementations in use
Such an architecture combines hardware and software to integrate production and manufacturing data by using edge computers designed for the relevant digitalization task.
While a CNC has a very powerful processing unit, the core competency of CNC design is path and speed control. Direct implementation into the CNC would be impossible because these have already been customized by the machine builders and do not offer a uniform platform.
Industrial edge architectures, separate from a CNC system, allow technology providers and tool and work-holding manufacturers to develop applications, creating a platform for digital transformation. The industrial edge development platform provides easy and fault-free programming of applications. Runtime software ensures connectivity with connected automation devices and with the edge management system, with an interface to the industrial Internet of Things (IIoT) cloud. It also facilitates further processing of data in higher-level IT systems and application administration and updates.
Edge computing is open to all devices, applications
An industrial edge offers a platform for processing other machine sensors. For example, camera images can be evaluated to monitor mechanical component clamping. Edge data processing can be imported back into the machine, optimizing current process, minimizing wear and improving quality.
Edge computing is going to be a core aspect of future machine tool use. Application-specific expertise can further increase productivity. An industrial edge environment facilitates real-time data evaluation laying the foundation for future-oriented technologies.
Edited by Mark T. Hoske, content manager, Control Engineering, CFE Media and Technology, [email protected], using information from Siemens and an interview with August (Gus) Gremillion, Siemens digitalization solutions consultant.
KEYWORDS: Industrial edge computing, motion control, CNC
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