Understanding the Role of AI in Industrial Robotics

Robotic arms inside of a factory

Artificial Intelligence (AI) is changing many industries with industrial robotics, a cross-section between the fields of Robotics and AI that is helping to spur a new labor force using machines on a global scale. 

Using Deep Learning, and other advanced AI technology, programmers are not only designing routine automation bots but also designing the future of factory manufacturing. As complementary technology, both AI and Robotics are shaping up to revolutionize vital aspects of the economy, rearranging the cost to produce goods.

Brief History of Industrial Robotics

Industrial robotics can first be traced back to the Unimate, a robotic arm developed by George Devol and Joseph Engelberger in the late 1950s under their company Unimation. The machine was a large success with companies like General Motors being among the first to purchase and install them in their factories.

Over the next few decades, industrial robots would become more common in manufacturing facilities, expanding the complexity of tasks they could perform with the introduction of computer numerical control. 

By the turn of the 21st century, new technology like sensors and computer vision systems allowed machines to be more cooperative with human workers. Cobots, or collaborative robots, were designed to work alongside humans, instead of replacing them. These intelligent machines can be seen in many modern warehouses today operating for companies like Amazon or UPS to transport items across massive complexes.

Defining Artificial Intelligence in Industrial Robotics

AI in industrial robotics works by integrating advanced algorithms that help machines interact with their environment. This requires a complex combination of AI systems within the machine’s software to ensure that it can operate properly in hazardous environments:

  • Machine Learning: Machine Learning algorithms can help industrial robots learn from operational data for training. This can help robots learn basic routines like installing car parts or manipulating materials. 

  • Deep Learning: Deep Learning can employ more advanced algorithms like reinforcement learning to train machines with more nuanced commands and data necessary for safely operating alongside humans. 

  • Neural Networks: Neural Networks can be used to help provide additional sensory inputs for machines, using techniques like convolution to analyze visual context. 

The Role of AI in Industrial Robotics

AI plays a significant role in industrial robotics, providing them with the “brain” for their “body.” There are many observable benefits:

  • Functionality: AI allows industrial robotics to perform complex tasks such as identifying objects and making real-time decisions which gives machines better abilities to learn new routines. 

  • Efficiency: Industrial robots can slowly learn over time, improving their performance results and reducing the amount of maintenance and oversight required by humans. 

  • Flexibility: Simple routines and tasks can help make industrial robots more interchangeable with other machines and components, giving factories more options for purchase. 

One of the most obvious examples of AI in an industrial working environment is automotive factories, but there are many other types of industries that can improve from AI robotics including electronics and agriculture where assembly lines and logistics are vital. 

Benefits of AI in Industrial Robotics

The integration of AI into industrial robots has made an immense impact on the productivity of manufacturing around the world. Machines are capable of operating 24/7, allowing manufacturers to produce goods more consistently. They can also perform more physically extreme tasks like lifting heavy metal objects and withstand higher temperatures. 

These benefits are scalable as well, increasing productivity with every new advancement in AI. These updates to the technology give machines more tasks that they can perform while also improving their safety measures for those around them. 

Innovations in AI and Industrial Robotics

Many modern factories and warehouses around the world, especially in countries like China, The United States, and Germany, are already deploying some of the most advanced industrial robotics available using innovative concepts:

  • IoT and Industry 4.0: The integration of Internet-of-Things devices is leading to the development of a new type of facility coined a smart factory that enables machines to communicate with each other, improving productive synergy and ushering in a fourth industrial revolution. 

  • AI-Powered Quality Inspection: Deep Learning is helping machines spot inconsistencies and defects on production lines by using computer vision and other sensors. 

  • Autonomous Mobile Robots (AMRs): AMRs are becoming increasingly popular in self-distribution centers, helping to transport goods across large facilities for shipping or manufacturing.  

  • Predictive Maintenance: AI can help humans detect which machines are close to failing so that they can be repaired without ceasing production.

Future of AI in Industrial Robotics

While the benefits of industrial robotics are clear, they do carry a concern of displacing large numbers of factory workers. This, coupled with the fact that many factory workers do not possess the higher education necessary for more advanced jobs, means that the full integration of AI in industrial manufacturing could threaten the livelihoods of many around the world. However, the development of cobots and AMRs is showing that humans and robots can still work together efficiently. 

With further innovation and greater autonomy, industrial robotics have the power to change how products and goods are manufactured and shipped around the world, completely reshaping supply chain management and how intelligent robotics are integrated into society. 

Keegan King

Keegan is an avid user and advocate for blockchain technology and its implementation in everyday life. He writes a variety of content related to cryptocurrencies while also creating marketing materials for law firms in the greater Los Angeles area. He was a part of the curriculum writing team for the bitcoin coursework at Emile Learning. Before being a writer, Keegan King was a business English Teacher in Busan, South Korea. His students included local businessmen, engineers, and doctors who all enjoyed discussions about bitcoin and blockchains. Keegan King’s favorite altcoin is Polygon.

https://www.linkedin.com/in/keeganking/
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