Throughout history and mythology, twins have been represented as counterparts; mirror images highlighted as having unique relationships and even their own language. This level of deep connection between counterparts is seen in today’s digital twins, which are used in manufacturing to aid planning and improve functionality.
NASA was the first to experiment with digital twinning for its Apollo 13 mission, with the technology allowing the crew to be bought back safely after disaster struck. Over 35 years later, advances are being made to integrate digital twinning into manufacturing.
It is one of the latest technologies to emerge from the fourth industrial revolution, allowing plant engineers and managers to virtually replicate a physical asset, from planning through to operations. Sensors and smart equipment gather real time data that can incorporate variable factors, such as working conditions from the physical world, and use them to run complex predictive simulations that replicate the real working environment.
The technology has the freedom to test every process, feature and system without interrupting the physical process. Drawing from data sets held in industrial historian software packages such as those by GE Digital, the twin provides comprehensive insight into operations to help plant managers improve overall equipment effectiveness (OEE) and efficiency.
Effectively, managers can remotely control and monitor all aspects of their plant’s operations and simulate how process changes will affect production. This allows managers to avoid unnecessary repair and maintenance costs by using the software to predict breakages.
Novotek UK and Ireland distributes one such platform in the form of GE Digital’s Predix, which facilitates the building and mapping of digital twins with IoT devices. Twins can be introduced at any stage during development, but the sensors and systems must be applied and monitored correctly for the twin to be fully-functioning. Communication is key and with the developments in network communication, edge processing and security, this process is made slicker, allowing accurate analytics and reporting between your twin and physical asset.
Digital twins communicate with their physical counterpart in their own language, predicting trends and anomalies to enhance the workflow and productivity, providing manufacturers a unique opportunity to become agile, efficient and effective.