How important is the role of artificial intelligence in Industry 4.0?

The concept of Industry 4.0 is making waves in the technology industry, as manufacturing companies seek to leverage technological advancements to make their operations faster and more efficient. Since its introduction in 2011, Industry 4.0 has been a buzzword for the wave of process and technological changes sweeping the manufacturing industry.

It is somewhat interchangeable with digital factory and smart manufacturing, and makes many different changes to traditional manufacturing. In particular, these new factories and factory systems are more efficient because they are deeply instrumented, highly networked, extensively automated and fully data-driven.

Why Artificial Intelligence is an Important Pillar of Industry 4.0

Industry 4.0 relies on a wide range of technologies, including robotics/cobots, IoT, 3D printing, additive manufacturing, digital twins and analytics. Digital factories are filled with smart instruments that monitor or control every aspect of production and with highly granular data ranging from material quality to sub-millisecond status updates on machinery.

Artificial intelligence, including machine learning and generative and discriminative artificial intelligence, can create compelling value in most technical aspects of Industry 4.0. The value of AI often comes from raising the bar for automation by bringing a human-like level of understanding to software.

This reduces the number of places in the manufacturing process where people evaluate information and make decisions, which both reduces costs and increases productivity. Machine speed understanding can guide the robot's operation, for example, by slowing down, speeding up, or modifying its behavior to respond to changes in raw material quality, or the speed of other parts of the process.

In addition to the automation of production lines, artificial intelligence still has countless uses in the same type of environment. First, it can help build digital twins, another technology that speeds up the product development life cycle.

Secondly, artificial intelligence systems help leverage industrial IoT infrastructure, for example, by filtering event information to discover and predict potential production issues based on sensor data. AI can also aid production data analysis by revealing previously unseen patterns in production and usage data and then using this information to recommend design or process changes.

Artificial Intelligence Use Cases in Industry 4.0

Since artificial intelligence can help throughout the manufacturing process, there are many use cases in the Industry 4.0 environment. Early in the product life cycle, generative AI can help in the design phase as well as in the prototyping of physical objects through 3D printing or computer-controlled machining and additive manufacturing.

Generative AI systems can optimize designs to make them more efficient in their use of materials. For example, in apparel manufacturing, these systems control the cutting layout of garment panels on fabric bolts in a way that minimizes waste of fabric.

In other types of factories, AI systems can optimize the simplicity of manufacturing and assembling complex items by reducing the number of parts required for a design. Additionally, to speed up production, AI can reduce the number of individual cuts required to produce finished chair legs on a moving walkway, for example.

Other specific use cases currently in factories include:

• Nutella uses generative AI to design millions of unique packages for its products;
• In 3D printing , ADDMAN uses hybrid modeling tools combined with artificial intelligence to more efficiently design and prototype machine parts;
• FANUC’s factory produces computer numerical control machine tools that can learn from mistakes and improve control while operating;
• Collaborative robots can allow humans to work on production lines without humans being present, especially in oxygen-free environments or extremely hot temperatures;
• 3D Fiberglass factories like this work by responding to real-time events Speed ​​up and slow down production lines or operations to monitor mechanical performance;
• Factories such as BMW use cameras and other sensors to monitor product quality and remove items as soon as a fault is detected to save energy and materials.

Computing capabilities, both on-site and in the cloud, will continue to increase, while artificial intelligence algorithms and technologies will not stop maturing. Manufacturers know this and understand they need the efficiency and responsiveness these tools provide in order to compete in the 21st century. As new manufacturers emerge and old factories are updated, AI will continue to expand its role in Industry 4.0.

The above is the detailed content of How important is the role of artificial intelligence in Industry 4.0?. For more information, please follow other related articles on the PHP Chinese website!