Edge Computing

Receive comprehensive business insights and actionable intelligence from the edge using the Simio Software. Simio’s Digital Twin and Simulation software provide an excellent ecosystem for visualizing and analyzing your facility’s edge computing data.

To deliver complete industrial automation, achieving real-time data capture, analytics, and data transfer must become the holy grail. Although cloud computing has taken us closer to the goal of accurate real-time automation, industrial systems are not yet fully there. This is because capturing granular data from the deepest parts of any facility and sending it to the cloud comes with its own challenges. These challenges include time lapses during data transfer and communication issues between assets or facilities and the cloud.

Enter edge computing. The concept of edge computing revolves around computing at the network edge of every equipment and device on Manufacturing shop floors. This means every equipment will be able to capture the data it generates, analyze this data, and make decisions without having to rely on input from a centralized cloud network. Thus, delivering real-time analytics at the equipment level.

Edge computing relies on edge hardware which captures data, hosts analytical applications and handle the actual analytics needed for automation. The innovative designs of edge hardware such as human-machine interfaces, smart devices, and actuators now make capturing data from hard to reach places and legacy equipment in brownfield facilities easy. This means more data from shop floors and other facilities which can be used in making simulations and digital twin environments more accurate.

Edge Computing, Cloud Computing and The Digital Twin

While edge computing delivers real-time data analytics at the equipment level, more data from across a facility and scalable computing resources to handle large data sets are needed to deliver automation at the facility level. This is where cloud computing and digital twin solutions are useful. Edge devices can send data from the shop floor deemed not useful for edge analytics to the cloud and digital twin applications. In turn, these services use the data from edge devices to develop more accurate models of the entire facility.

The integration of edge computing into digital twin environments powered by the cloud enhances accuracy where the real-time analytics of facilities are concerned. The benefits of integrating edge computing with the digital twin include the following:

  • Increased Accuracy – To enhance the accuracy of digital twin models, integrating every data captured within a facility is required. Edge computing provides granular data that makes modelling assets and processes highly accurate.
  • Real-Time Risk Prevention – The complementary relationship between edge computing and the digital twin also applies to facility monitoring and management in service-based industries. This also applies to production facilities where workers are susceptible to accidents on the shop floor. Using the digital twin to monitor edge devices can serve as a preventive measure when dealing with potential risks and hazards in facilities.
  • Enhancing Edge Computing – Edge devices or assets can take advantage of the real-time simulations the digital twin offers to make better decisions. Using an automated guided vehicle (AGV) travelling through terrains as an example, integrating data from a digital twin of the terrain provides the edge AGV with more knowledge of its environment which leads to better decision making.

Simio Digital Twin and Edge Computing

The Simio software is equipped with the features needed to model and integrate edge devices or assets into your facility’s digital environment. This helps with extracting real-time insight from the shop floor and accessing the impact of deployed edge devices to a facility’s operation.

With the Simio software, digital representations of both the edge devices, the data it produces, and other assets within a facility can be developed and monitored in real-time. It also provides a high-performing environment for running simulations and devising new business cases for the implementation of edge computing. The benefits Simio brings to edge computing include the benefits outlined above, as well as, these:

  • Cloud-compatible simulations
  • Discrete event scheduling
  • Real-time scheduling

You can learn more about how Simio helps you accomplish more with your edge computing systems and data by speaking with a representative today.

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