PACKAGING AUTOMATION
Artificial intelligence at the edge
Cloud computing is defined as the storage, management and analysis of data saved remotely on a server. Although invaluable in many instances, is it always the best solution for the production line? Food Manufacturing spoke to Victor Marques country general manager of Omron Industrial Automation to find out.
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NOTHER PROMISING ALTERNATIVE is edge computing. This system enables data storage, applications and analysis to be carried out at the edge of a machine. Lines and devices are monitored and real time sensors and data at machine level can be processed in microseconds. A machine’s condition can be monitored in real time, but data volume is limited. Data processing at the edge enables an immediate response. Industrial manufacturers need to think carefully before deciding which of these two options will be the most effective. They must consider the recent arrival of solutions involving artificial intelligence
(AI) and machine learning (ML). Although AI offers some great benefits, care needs to be exercised before incorporating it into industrial applications WHAT’S YOUR PROBLEM? The biggest challenge companies face is that they often can’t identify the problem they want to solve. The solution is to start collecting and cleaning data first, before thinking about introducing AI. You can then obtain information from the data and start visualising this in a smart way. Basic data science will help your company to start realising a range of benefits. A lot of existing data isn’t suitable for
analysis, however. If you’re thinking about AI, you must think in a broader sense about data science - what and how much data you need. You will require a substantial amount if you want to reach the right conclusions. You can apply AI at various levels, depending on the problem you want to solve. If you want to compare the performance of two factories, you can gather the data and put it into the cloud (inside or outside your enterprise) and compare, analyse and draw conclusions. The main challenge remains: what problem do you want to solve? Do you need to look at a lot of data? If you want to compare a large amount of data from 20 factories, this is where AI in the cloud can play a key role. If
2020 Quarter 1 | Food Manufacturing Africa
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