DATA & ANALYTICS
in place to build their digital manufacturing operation ? Developing a data platform , or ‘ fabric ’, that connects the organisation ’ s systems on a hybrid cloud architecture is a key part of the data backbone that needs to be in place to enable a digital factory .”
As with any AI-enabled technology , there are vast amounts of data that organisations need to process , analyse and store . To accommodate this effectively , manufacturers need to either build or find infrastructure that ensures they process the data required for their AI and ML applications . This ensures that costs are controlled and unused data is continually assessed in case it has value for future use cases that may drive efficiencies .
Kostov offers a solution that many manufacturers have discovered to improve the production line with IIoT and AI devices : “ An ideal approach is to combine the data collection capabilities of the IIoT with modern Manufacturing Execution Systems ( MES ) to provide a powerful , robust framework to best manage complex operations .”
Adding to this , he explained : “ This type of strategy provides the performance promised by ‘ Industry 4.0 ’ strategies as an ideal foundation to start building a datasharing strategy that is current and accurate , with a single source of truth . An MES creates a common foundation to run and review production and quality processes that are augmented with the necessary data , delivered by the IIoT .”
Commenting on the future of the industry as this technology takes hold , Favilla concluded : “ Looking ahead , the next evolution in digital manufacturing will be the ‘ Industry 5.0 ’ era . This will be characterised by a greater focus on sustainability and expanding value beyond shareholders to ordinary workers and all of society , significantly contributing to the planet ’ s sustainability goals .” aimagazine . com 133