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Home Artificial Intelligence

Unlocking manufacturing potential: The convergence of AI and edge computing with universal automation

by Jack Lloyd
October 16, 2024
in Artificial Intelligence, Features, Robotics & Automation
Reading Time: 5 mins read
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Image: Art_Photo/stock.adobe.com

Image: Art_Photo/stock.adobe.com

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Revolutionising the manufacturing industry, the convergence of universal automation, AI, and edge computing marks a pivotal shift.

Today’s global manufacturing landscape thrives on ongoing disruption as the ‘new normal.’ Just a couple of years back, manufacturers grappled with pandemic-induced upheavals, compelling substantial process and infrastructure adaptations to stay ahead amidst unparalleled workforce and supply chain hurdles.

Recent times have witnessed a proliferation and intersection of technological advancements such as artificial intelligence (AI), edge computing, and universal automation within the industry. Plant managers and their teams are now tasked with the formidable challenge of integrating these emerging trends into their operations. New technology means more than just disruption and their rewards for investment and change can include:

  • Increased productivity
  • Lower development and production costs
  • Improved product quality
  • New product innovation
  • Enhanced competitiveness

Three universal automation technologies leading the future of manufacturing.

Key technology innovations contribute to achieving new industry manufacturing productivity and competitiveness goals and can complement each other:

  • Artificial intelligence – AI and machine learning (ML) algorithms enhance real-time data analysis for more accurate predictions and minimize problems like product defects. Repetitive tasks prone to human error are now easily automated. AI learns production patterns and behaviours so staff can manage output more quickly and efficiently, reserving time and skills for complex problem-solving and innovation. For instance, manufacturers can use AI to evaluate plant equipment conditions and predict when maintenance should be performed, lowering unanticipated downtime.
  • Edge computing: Edge computing implies a network of geographically distributed computing devices that, while capable of cloud connection, are not exclusively supported by cloud services. For low-latency applications, a centralized cloud computing model may struggle to process all remote data with acceptable response times. For this reason, much of the data produced across manufacturing lines will never be transmitted to the cloud. Still, they will be processed at the network’s edge, providing flexible computation, data storage, and communication to large numbers of users who work close to their machines. Instant access to machine data helps to drive faster and more accurate production decisions.
  • Universal automation – Universal automation represents “plug and produce” automation software components — akin to an industrial app store. It decouples hardware from software to create portable, interoperable, and software-centric industrial automation systems. These systems can drive significant improvements across the entire operational lifecycle.

Harnessing the collaborative power of the three technologies

Using the Food and Beverage industry as an example, let’s consider how AI, edge computing, and universal automation converge to boost productivity and lower costs. Software platforms like Schneider Electric’s EcoStruxure Automation Expert, a universal automation tool with a hardware-agnostic virtual controller, can help streamline machine design for OEM engineers by integrating AI and edge computing capabilities more efficiently.

Imagine an online packaging machine for assorted gourmet chocolates. If it fails to place the chocolates precisely in the correct locations in the box, the box will be rejected and require manual repackaging, slowing down output and reducing profitability.

However, by integrating AI into the machine (by training cameras to differentiate between a good box of chocolate and a bad one) and using an attached edge computer for real-time decision-making on the conveyor belt path, the machine becomes more autonomous. The machine can make the package and detect its quality without human intervention. EcoStruxure Automation Expert’s event-driven nature helps machine builders more easily integrate the benefits of AI, edge computing, and universal automation. EcoStruxure Automation Expert works with AI to enhance productivity for plant floor workers by reducing error management time and allowing more focus on boosting output and lowering downtime.

For more information

Check out this video demonstration to learn how universal automation platforms like EcoStruxure Automation Expert can drive digital transformation benefits in your manufacturing facility.

Explore industrial software to enhance manufacturing efficiency.
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