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How to optimize your manufacturing processes with AI

In order to remain competitive in the international market place, it is important that you adopt artificial intelligence technology (AI), and recognise it as the next major factor in manufacturing while there is still time to remain in the wave of early adopters of the technology. AI is crucial to manufacturing and is rewriting what the future of the industry will look.

Computer vision

 

A machine has the possibility to identify problems the human eye would have no chance at. A camera can be far more sensitive than the iris of an eyeball. That’s not to say that humans will be completely eliminated from the flaw-finding processes of development - judgements and corrections to design flaws still lies within the scope of only-human expertise. But overall, AI and computer vision will help humans through this process, allowing for much more in-depth and fastidious checking and testing processes, allowing for a much greater scale of design optimisation.

 

Generative Design

 

Engineers and designers can input design parameters and goals for materials, manufacturing methods and even cost restrictions into generative design software. This software then goes and runs an exploration into a vast number of different solutions, quickly generating a design solution, or alternative to the previous ones. It utilises machine learning technology to test and learn from each run, working out what is favourable, and what isn’t. This process is not only time effective, but has the power to significantly cut down on design, prototyping and manufacturing costs. You can in essence hire the power of 50,000 computers for a single day, to do work which would equate to 50,000 days of engineering.

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Leading innovation using new technologies

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Leading innovation using new technologies

Digital Twins

 

The virtual pairing with the physical world allows for the analysis of data and for you to monitor systems, to predict problems and resolve them before they even occur. Downtime can be easily cut out of daily run schedules, and future planning and development opportunities can be run using digital twin simulations. Working in tandem with the Internet of Things, machine learning and artificial intelligence, digital twinning technology has a lot to offer to the world of engineering. When working physically distanced from a plant or from manufacturing lines for example, digital twinning collects data in real-time from anywhere, and provides lessons and opportunities in the virtual environment that can be discovered and then translated into the physical world. The potential to completely transform your business while optimising your manufacturing processes lies within these technologies.

 

Predictive Maintenance

 

Bid farewell to guesswork, machines now report their own conditions in real-time to you, allowing you to prevent lost time in your business, and maximising on your resources. Labour costs and optimal manufacturing processes are made possible through digital twins, sensors and analytics in manufacturing equipment, making them their own watchful eyes, and reporting to your workers whilst examining their own internal workings. Maximise on your resources by ensuring that every element in your business is as technologically advanced as possible, and through this you open up your business to new opportunities.

 

Summary

 

Adopting AI across your processes internal and external is key to staying abreast with the rest of your competitors, who will be optimising every aspect of their organisation’s work flows using new technologies like these. The scope of possible applications range from real-time maintenance of equipment to virtual design processes that accommodate new, improved and customised products - opening up the possibility of creating new and more efficient supply chains, and the opportunity for the creation and adoption of new business models.

Carl-Eric Ryberg

Carl-Eric Ryberg

Department Manager
Technical Documentation Solutions, AIM
0703556774
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Carl-Eric Ryberg
Carl-Eric Ryberg
Department Manager