What happened to the promise of AI in manufacturing?

McKinsey recently forecast that the global market for AI-based services, software and hardware will grow by up to 25% annually, but does AI live up to the hype? Where are all the self-driving cars we expecting years ago? Interestingly, AI in manufacturing is alive and well, and working its way in under the radar.

The use of AI-based technologies and robots in industrial environments is still in its infancy. But manufacturers are recognising its potential for increasing Overall Equipment Effectiveness (OEE). Healthcare and automotive sectors are leading the move to reduce costs and boost productivity.

As Omron’s Tim Foreman, Omron’s Research and Development Manager considers. “Manufacturing companies are conservative, as they often work with older machinery. But that does not mean they are behind when it comes to artificial intelligence. It is time for industrial producers to enjoy the opportunities offered by these technologies. Predictive maintenance is one area that demonstrates its advantages and potential.”

AI in manufacturing

Until recently, some SMEs thought that AI was too complicated and expensive. Learning experiences being difficult to transfer between machines or to apply to a complete system. But this is not always the case as many of the AI in manufacturing applications come as turnkey solutions.

AI offers SME the chance to keep their production costs down so that they can compete with larger firms. For example, to use robots and AI solutions like open-source software and applications that rely on machine learning.

The two cornerstones of AI are large amounts of data and advanced algorithms. These are both areas that organisations, their managers, and employees need training in. Robotics and automation providers are developing AI integrators that will help SMEs to make effective use of AI.

AI at the edge

AI-based technologies help to forge a new harmony between man and machine, or ‘factory harmony’. But this is only possible when AI projects are strategically planned and implemented.

Omron’s AI Controller is the world’s first AI solution that operates ‘at the edge’. It uses hardware from Sysmac NY5 IPC and the NX7 CPU) to recognise patterns based on process data collected from the production line. As part of the Sysmac platform, it is a complete solution for factory control, including motion and robotics, image processing and machine safety. Using it in the machine reduces efficiency losses to optimise gains across the whole production.

The Omron AI Controller is easier and faster to install at machine level than other solutions. This makes it ideal for predictive maintenance and machine control. It combines line control functions with real-time AI-based data processing. Companies can anticipate unforeseen situations in real-time and respond as required.

Edge v cloud computing

Cloud computing involves simple and uncomplicated access to data and systems. By implication, this means away from the point of activity, data collection and decision making.

Edge computing improves real-time control and responsiveness. Sensors collecting information at the machine enable deeper and more up-to-date data analysis. Consolidating and compressing important information further optimises oversight and transparency.

As more data become available, only AI in manufacturing will recognise the patterns and delivers the information needed. AI will become easier to use and companies must have more confidence in themselves to use it. In this context, business aspects are always more important than technological considerations.

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