Best Practice

Digital twin helps manufacturing companies to intercept and prevent anomalies

An advanced mix of edge and cloud computing to help companies carry out data-driven analytics and predictions, thus transforming the manufacturing process management strategy from reactive to predictive.

This is the offer from Brick Reply, the Reply Group company specialising in advanced solutions for manufacturing operation management. Brick Reply has extended its proprietary, cloud-based Brick Reply suite with an ad hoc application which, thanks to simulation and artificial intelligence technologies, provides staff in charge of monitoring and the shop-floor operating team (in other words, the entire factory) with a predictive analysis tool capable of proactively guiding them towards the optimal solution in the case of potential process-related derivations.

The new app, named Shop-floor Digital Twin, enables companies to take proactive action, thanks to the system’s ability to intercept abnormal situations that require attention and process corrections, even before they lead to an actual problem or a stoppage. A predictive function involves both the quality control of the material being produced and the maintenance of the machinery. The simulation techniques adopted, together with the predictive analysis functionality, make it possible to represent, in advance, situations that have the potential to become a deviation of the process over time.

The solution, therefore, supports the company, from an executive point of view, in the proactive management of the process and, in the long term, allows it to conduct ‘what-if’ analysis on different scenarios, also supporting changes related to new organisational models, the launch of new products or new business scenarios.

Thanks to the Digital Twin Shop-floor solution, companies are able to create a dynamic model capable of updating itself and aligning in real-time with the behaviour of the production line reproduced virtually on the Digital Twin, utilising real-time data captured from the machinery operating in the plant, going beyond the classic paradigm of simulations based on static data.

The model is therefore driven by the data and information collected in the field using the edge components which, thanks to the adoption of the new IoT gateway, facilitate the acquisition of large amounts of data (e.g. from sensors, machine tools, energy and safety control systems and self-driving vehicles). This data, appropriately filtered, pre-processed and prepared, is then transferred to the cloud where, together with the virtual representation of the shop-floor (geometric and physical characteristics, rules and operation), the data collected by the platform’s executive modules and data from external systems, feed the underlying shop-floor Digital Twin data lake.

The virtual representation system of the factory, which replicates current activity in real-time on its physical twin, can simulate future behaviour and detect any derivations of the standard process with a high degree of reliability, thanks to the application of machine learning technologies.

By adopting the Brick Reply platform and its Shop-floor Digital Twin component, companies can seize the opportunity offered by a change in the management strategy of their manufacturing process, leveraging the predictive capacity whose precision and accuracy is highly dependent on the extent to which the data is updated and cleaned. This data, collected from the edge, flows to the cloud as an essential, rapid and economical form, powering the digital twin.

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