When it comes to the engineering and manufacturing sectors, the pressure is well and truly on. Not only must businesses seek competitive advantage through reduced costs and increased productivity, they must do so in an environmentally conscious way.
In this context data really is king, allowing businesses to not only survive in the current climate, but thrive. Having access to the real-time data, and – critically, the knowledge and training to understand and interpret it, can facilitate greater confidence in business decisions, more accurate forecasting, and higher operational efficiency.
The food manufacturing sector is a case in point. Worth some £30bn to the UK economy, food and drink manufacturing accounts for 20 per cent of total UK manufacturing, giving it a top spot position when compared with other manufacturing sectors.
As such, the sector has a vital opportunity, and responsibility, to operate at its optimum capability. This requires consideration of not just how operational data can be made more readily available, but critically how it can be used and applied for maximum benefit.
The use of diagnostic sensors and wireless communications technology, that can monitor and control operations remotely, is already having a significant impact. In the food sector, for example, this can help manufacturers with liquid nitrogen consumption, as part of cryogenic freezing operations.
Specifically, using data to track liquid nitrogen usage in real time can facilitate proactive and ‘in the moment’ decisions on when more or less is needed and if usage is in line with the projected plan. This moves the dial from retrospective analysis (which of course remains helpful in identifying trends) to real time analytics, ensuring anomalies in the production line can be immediately flagged, and addressed, in turn reducing downtime.
Conveniently, thanks to smart technology, much of this work can now be done remotely, and without requiring operatives on the manufacturing floor to moderate behaviours, or manually input changes to production line controls. The data collected can be used for future troubleshooting and to compare productivity week on week, and year on year.
This approach is applicable across all engineering and manufacturing sectors and supply chains, and can significantly enhance business operations, removing the need to pause production to analyse performance and efficiency data.
The secondary aluminium sector, which provides a key resource for engineering businesses, is another industry increasingly exploring this smart technology approach. Traditionally, the sector relies heavily on an operator’s skills and experience to predict when aluminium has reached tapping temperature. But this approach, combined with the significant variability that is inherent in the remelting process, can often lead to suboptimal performance and inconsistent results. This, in turn, contributes to longer cycle times, reduced energy efficiency and increased aluminium losses.
By contrast, the introduction of smart technology – such as equipment sensors and associated analytics – can make a significant amount of data available that can help to accurately predict when the aluminium has reached tapping temperature. This means less likelihood of the metal overheating, which in turn can lead to the dual benefit of improved yield and reduced carbon emissions.
With new technology surfacing every day and existing technology continuing to improve, being equipped to translate the available data into valuable commercial insight in this way is key. Whatever the industry at hand, the business priorities ahead are clear. Better and more intelligent use of data can help future-proof against challenges and ensure continued economic and environmental progress.
Neil Hansford, UK&I freshline applications product line manager at Air Products
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Good comment. I think these reports are different from many others , in that they were prepared outside the government and the issues, they raised, of...