AI in manufacturing: revolution or restructure?

Chris Smith Date published: May 03, 23

Artificial intelligence (AI) is rapidly becoming a big part of everything, so it would seem. And if we look at how AI is transforming the manufacturing industry, it is no different.

AI-powered technologies are being used to automate tasks, improve quality control, and optimise production schedules. As a result, manufacturers are seeing significant improvements in efficiency, quality, and profitability.

So, it’s a good thing, right?

Let’s take a look at how AI in manufacturing is currently taking place, and how it might shape up in the future.

How is AI in manufacturing being used?

While AI might be a bit of a ‘buzz-word’ just now, it’s been around longer than you think, and takes many different forms other than LLMs.

Here are some of the ways that AI is currently being used in the manufacturing industry:

Predictive maintenance

AI can be used to analyse data from sensors and machines to predict when they are likely to fail. This allows manufacturers to schedule maintenance before a failure occurs, which can save time and money.

Quality control

AI can be used to inspect products for defects which can help to improve quality and reduce the need for rework.

Demand forecasting

AI can be used to analyse historical data and predict future demand for products helping manufacturers plan production more effectively.

Supply chain management

AI can be used to optimise the flow of materials and products through the supply chain, potentially reducing costs and improve efficiency.

Robotics and automation

AI is being used to develop robots that can perform tasks that are currently done by humans, such as welding, assembly, and inspection improving end-product and production times.

What are some real-world examples of AI in manufacturing?

One of the most prominent ways that AI is already being used in manufacturing is to automate tasks. Robots are now being used to perform a wide range of tasks that were once done by humans, such as welding, assembly, and inspection.

For example, General Electric is using AI-powered robots to automate the assembly of jet engines. The robots are able to perform the assembly tasks more quickly and accurately than humans, which has led to an increase in productivity.

AI is also being used to improve quality control. AI-powered systems can inspect products for defects more accurately than humans, and they can also identify potential problems in the manufacturing process before they cause defects. This is leading to a significant reduction in the number of defective products being produced.

Ford is currently using AI-powered systems across multiple areas, even to inspect the welds on its cars. The systems are able to identify potential problems in the welds that humans would miss, which has led to a reduction in the number of defective cars being produced.

In addition to automating tasks and improving quality control, as touched on before, AI is also being used to optimise production schedules. AI-powered systems can analyse data from sensors and machines to predict when they are likely to fail. This allows manufacturers to schedule maintenance before a failure occurs, which can save time and money.

Rolls-Royce is using AI-powered systems to predict when its jet engines are likely to fail. Its systems are able to identify potential problems in the engines that humans would miss, which has led to a reduction in the number of engine failures.

What are the benefits of AI in manufacturing?

So, we know that AI is already having a profound impact on the manufacturing industry. AI-powered technologies are automating tasks, improving quality control, and optimising production schedules. As a result, manufacturers are seeing significant improvements in efficiency, quality, and profitability.

Improved efficiency

AI can help to automate tasks, optimise production schedules, and improve quality control. This can lead to significant improvements in efficiency.

Reduced costs

AI can help to reduce costs in a number of ways, such as by reducing the need for human labor, improving quality control, and optimising production schedules.

Improved quality

AI can help to improve quality by identifying and preventing defects. This can lead to a reduction in the number of products that need to be reworked or scrapped.

Increased innovation

AI can help manufacturers to innovate by providing new insights into data and processes. This can lead to the development of new products and services.

Improved customer service

AI can help manufacturers to provide better customer service by providing real-time information about products and orders. This can lead to increased customer satisfaction.

The future of people and AI in manufacturing

The future of manufacturing is looking very bright thanks to AI. As AI technology continues to develop, it is likely that its use in manufacturing will continue to grow. This will lead to even more improvements in efficiency, quality, and profitability for manufacturers.

However, this doesn’t mean that we don’t need to keep improving our production teams, maintenance teams etc. As advanced as AI is getting, and as useful as it is, we still need traditional teams involved in the manufacturing industry. AI is still not able to replicate the human brain's ability to think outside the box and come up with new ideas. Humans are also needed to monitor and maintain AI systems, and to make decisions when necessary.

Creativity and problem-solving

Humans are able to think creatively and solve problems in ways that AI is not yet able to. This is important in manufacturing because it allows for innovation and the development of new products and processes.

Monitoring and maintenance

AI systems need to be monitored and maintained by humans. This is because AI systems are not perfect and can make mistakes. Humans are able to identify and correct these mistakes, which helps to ensure the quality of the products being manufactured.

Decision-making

Humans are also able to make decisions based on their own judgment and experience. This is important in manufacturing because it allows for flexibility and adaptability. AI systems are not able to make decisions in the same way as humans, which can lead to problems if the situation changes unexpectedly.

Overall, humans are still needed in manufacturing because they have the ability to think creatively, solve problems, and make decisions. AI is still not able to replicate the human brain's ability to do these things, which is why humans are still essential in the manufacturing process.

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