Greater productivity and enhanced efficiency in manufacturing

AI and deep learning have the potential to impact operations and processes and drive significant value for manufacturing companies. And AI isn't just for technology pioneers or academic organizations. The path to using advanced AI techniques like deep learning is now realistic (and realizable) for businesses from the enterprise on down.

How to tap into the true intelligence of all your machines

Manufacturing is primed for AI from a variety of perspectives. In core manufacturing operations such as the production line, AI can automate tasks, optimize capacity, reduce the number of defects and ensure machines are working.

With predictive maintenance, AI can help companies avoid machinery failure and the massive costs associated with that. Real-time monitoring leads to cost savings over scheduled maintenance and occasional sample checking. AI applied to materials optimization can reduce waste and further improve quality. Inventory forecasting is another area of AI that will allow manufacturing companies to lock up less capital in materials and stock at a time.

Process industries generate enormous volumes of data, but many have failed to make use of this mountain of potential intelligence

McKinsey

But by far the biggest benefit in manufacturing will be found in quality improvements. AI can pinpoint anomalies in production and use robotics and automation to make all kinds of processes quicker and better. 

Peltarion has expertise in the manufacturing sector, with a variety of proven use cases. The Peltarion Platform is set up to support deep learning methods, operationalize AI and enable non-experts to both understand and apply the deep learning process.

02/ Read more about the use case methods within manufacturing