Within the new generation of technologies that are transforming the industry, ‘digital twins’ are emerging as a popular application on the production line.
As more organisations invest in smart equipment and digital capabilities to maintain a competitive advantage, digital twins are gaining importance in the industrial environment.
They act as software equivalents to computers with their real-time and historical data and sensor analysis. They have the ability to virtualise and simulate maintenance tasks and work, taking industrial maintenance to a higher level.
We invite you to read our post about digital twins to understand how they work in depth.
Uninterrupted asset management
Organisations, through digital twins, can determine the intervention and maintenance required to optimise the performance of an asset and maximise its life, before any work is carried out on the asset itself.
Unlike other types of maintenance, it avoids disruption and downtime, allowing for more informed decision-making regarding the asset. If you want to learn more about the types and techniques of industrial maintenance, don’t miss our post about the importance of industrial maintenance in intelligent factories.
The digital twins of the assets are able to read real-time feedback from IOT sensors placed on key factory equipment and sites to transparently assess the impact of alterations that future actions may have on factors such as product quality, production rate, environmental or temperature changes, wear and tear etc.
In addition, Digital Twins have the ability to calculate potential KPIs related to scheduled maintenance changes. By combining historical data on failures, risk factors, machine configuration and operational scenarios, a digital twin can calculate these KPIs in advance to evaluate, in a quantitative way, the performance of a certain activity, asset or department.
How do Digital Twins work in the context of industrial maintenance?
Through the information collected by sensors and stored on a Big Data platform, the Digital Twins use all this information to continuously monitor the operation of the machines and, based on their observations, estimate the current state of the system and predict how it will behave in planned maintenance actions.
A neural network is responsible for detecting abnormal patterns in the incoming sensor data and reflecting the patterns in predictive models. These models are then used to predict failures and reduce problems in future work. Or on specific assets, to simulate and predict their performance.
In this way, if a scheduled configuration or change in an asset is likely to cause a failure, the digital twin’s software will locate the problem, assess its criticality, notify technicians and be able to re-plan the change avoiding disasters, it can also recommend and simulate mitigation actions.
In this way, with the DTs, the operator of a machine can also determine the optimal time for its maintenance, avoiding the cost of both major repairs and premature or unnecessary maintenance.
Benefits of DTs for industrial maintenance
- Real-time, contactless performance evaluation: The ease of managing assets remotely provides a level of flexibility and control never before seen. Maintenance routines are adapted to the real-life cycle of your equipment.
- Uninterrupted asset management: The level of adaptability of production systems increases considerably, making it easier to schedule maintenance activities to adapt to changing production requirements.
- Cost savings throughout the production cycle: engineering resources are optimised, critical repairs are avoided by anticipating them and losses due to production downtime are avoided.
- No more need for additional back-up production lines: the reliability of the equipment is optimised, and the Digital Twin acts as a virtual version of the asset, so no more extra production lines are needed and the life of existing ones is extended.
- Less waste and endless possibilities for innovation in the industrial sector: DTs offer higher performance, less maintenance and the possibility of focusing efforts on environmental and innovation issues that bring real value to production.
Nexus Integra for the industrial maintenance of your Smart Factory
Nexus Integra is the Big Data platform that helps you make the best maintenance decisions thanks to its digital twin and Machine Learning applications, as it allows data scientists to compare historical trends and real-time data. Thanks to the ingestion and structuring of the data in real and historical time, it allows the implementation of reliable Digital Twins that allow the control, simulation and efficiency in the maintenance and extension tasks of the installations.
Furthermore, it is a powerful tool for carrying out the maintenance strategy effectively and automatically, thanks to the Nexus Integra data presentation layer that allows control and maintenance in real time.
With Nexus Integra, you will be able to achieve an integral operation environment that combines the control of the process with its analysis. Contact us and we will explain you how.