Profit boost for Softronic

Charlie Taylor

This is how AI can change the playing field for the manufacturing industry

Published: April 12, 2022, 08: 43Updated: April 19, 2022, 15:42As in many other industries, data analysis and AI have crystallized as an indispensable part of the industry’s development and future-proofing – but how do you build a smart, secure and automated flow that manages to meet the requirements set in connection with Industry 4.0? fast forward, there are still many obstacles to overcome in order to take full advantage of all the new opportunities of development. So how can our industry players use data to drive efficiency all the way from innovation, design, manufacturing and assembly, through logistics to sales and predictive maintenance? – The main challenge with the huge amount of data generated from sensors, devices or people is to take care of, transport and secure all data, to make it useful for industrial applications, explains Peter Werdenhoff, CTO at HPE Sweden. Avoid downtime and prevent errorsIf you succeed in this, the rewards will be huge. With the help of applied AI models and analytics, data can form the basis for both better decision-making and real-time reactions during production, for example if a machine starts to malfunction or if a fault has crept into production. In this way, you can work preventively and avoid, for example, major downtime or production lines with thousands of defective products. In addition, processed data can be used to design new models, products or flows, which can be easily simulated by implementing what is called a digital twin. As a result, you can see what the effects will be if you adjust something in, for example, your production process – all the measuring points needed are already in place and a change or a new product can be tested both virtually and digitally, along the entire chain. Learn from the big pictureOn the other end of the spectrum, it is instead about the deal. If you can sync your profitability with your production, you can greatly increase your margins. Peter exemplifies through a salmon farm, whose chain includes everything from a genetic laboratory, breeding and slaughterhouse, to transport and sales. If the various units do not communicate, it will be almost impossible to learn lessons, to design new models or to find shortcomings along the chain. How does the fish get the right color for the right market, how do you optimize the transport routines and in which market do you get the best pay? – Almost everyone has a challenge in designing an intelligent data pipeline. However, it does not matter if it starts in a sensor, in a camera or in a fish in a fish farm, it is still just data. However, it is only when you can combine your data sources and learn lessons from the overall picture that is created, that it becomes really interesting. What we at HPE want to do is make sure that everyone who needs access and understands what insight is hidden in all data.Where needed, when neededWith a broad portfolio of IT infrastructure, services and solutions in, among other things, AI, HPE lays the foundation for companies to be able to do just that. One of the company’s customers is a large, Swedish telecom operator, which with the help of HPE smoothly analyzes and quality controls its data flow from edge to core to cloud. This is made possible as there is basically an advanced infrastructure, which generates the computing power required to handle these huge amounts of data in real time – in the place where the data is created. All this places high demands on the hardware. – The more measuring points we have, the more data is generated and the more power is needed to process it. That is why we collaborate with AMD; thanks to the efficiency of their processors, we can offer our customers the option of taking a distributed approach to their data processing. Properly adapted infrastructure for handling and analysis of data results in faster and more secure data transport and also the opportunity to make decisions near the units – where it is needed, when needed, Peter concludes. Read more how HPE and AMD improve analysis and secure data handling The article is produced by Brand Studio in collaboration with HPE and not an article by Dagens industri

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