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Manufacturing Manufacturing

Edge Computer Vision in Manufacturing

Date Section Blog

Taking Smart Manufacturing One Step Further

Manufacturers face labor shortages and supply chain issues. That's why companies must focus on automation, resilience, and reshoring their supply chains. No wonder that even the most conservative manufacturers are exploring Smart Factory adoption. They want to enable predictive maintenance to boost efficiency. Others are also looking to integrate IoT and cloud technologies. One of the biggest challenges these manufacturers face? Getting AI operational – and keeping it operational – on the factory floor. Edge AI is key to that operational success in complex production environments.

Edge AI versus Cloud and Local AI

If you are unfamiliar with the Edge concept, we need to talk about AI deployment. Depending on your needs, you can deploy AI in various environments. Each comes with its own advantages and trade-offs.

  1. Cloud AI
    The data is centralized in remote centers. Cloud AI is scalable and has central updates. But, it often suffers from high latency and data privacy issues.
  2. Local AI
    On-premises AI systems run on dedicated servers. They have lower latency than cloud solutions. However, they are less scalable and more expensive.
  3. Edge AI
    AI models run directly on local devices or close to the source of data—such as cameras and sensors. This allows for real-time decision-making and reduced data transfer.

Tesla: A Real-world Example of Hybrid AI Deployment

In traffic, decision speed is a literal lifesaver. That's why Tesla cars need to be able to make decisions in real-time for Autonomous Driving. So they move the AI processing to the edge: onboard in their cars.

However, Tesla also needs its Autonomous Driving System to keep improving. The system continues to learn from hundreds of thousands of other Teslas around the world. So the cars upload their data to the cloud for large-scale data aggregation. When those data are processed, the system pushes the updated models back to the cars.

Thanks to this hybrid approach, Tesla can blend real-time performance with continuous learning.

Like with Tesla, most complex production environments need a hybrid approach. It is often a mix of Cloud and Edge AI.

Key Benefits of Edge AI for Manufacturing

1. Real-Time Insights

Processing data on the Edge gives manufacturers instant feedback and quick decisions. This ensures issues are addressed as they arise, minimizing defects and production errors.

2. Reduced Latency

Running AI models on the edge means there is no need to send data back and forth to the cloud. This eliminates delays caused by internet connectivity and enhances overall operational efficiency.

3. Enhanced Data Privacy

Since sensitive production data is processed on the edge, confidential information stays local. This is particularly important for industries where data privacy and security are top priorities.

How to implement Edge AI in production environments.

When it comes to actually implementing AI on the floor, manufacturers have an important choice to make. Either they opt for a custom solution tailored to their specific needs. Or they can opt for a platform that has all the required capabilities and supports Edge AI. While there are pros and cons to both approaches, a platform offers the fastest route to market.

Read more here: seven differences between a custom built solution and the Robovison Platform. Or discover the benefits of a platform here.

Robovision 5.7: Edge AI for manufacturers

With release 5.7, Robovision announced a groundbreaking Edge AI solution. It is designed to retrofit Vision AI into complex production setups. Due by the end of Q4 2024, the update will help manufacturers. It will make their production lines smarter and more agile. This will boost efficiency and lower the total cost of ownership (TCO).

It is built to integrate with existing hardware. It allows manufacturers to retrofit older machines or to implement new equipment. That reduces the need for costly overhauls.

Robovision 5.7 fits into complex manufacturing systems. It supports OPC-UA, GenICam, and REST API. The release allows easy data and model exchanges. It connects edge devices and central systems. This enables real-time updates and better coordination across the production line. Robovision believes release 5.7 is a milestone in the company’s history. For manufacturers who need to innovate to excel in a tough market, it might be a game changer.