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AI Applications Within Cad Come Under the Spotlight at Solidworks World 2018

Articles Central Innovation 9 April 2018

AI Applications Within Cad Come Under the Spotlight at Solidworks World 2018

As Artificial Intelligence (AI) and machine learning continue to evolve and broaden in scope, speculation abounds as to their potential to improve efficiencies within CAD. At SOLIDWORKS World 2018 in Los Angeles, one of the main themes was the current state of play with regards to AI for CAD users.

AI’s application within CAD lies in its ability to “empower engineers and designers to solve problems intelligently” according to David Randle – senior business development manager at SOLIDWORKS. Artificial Intelligence embraces three technology types: machine learning, which is a system that learns and improves based on its experience, as opposed to having to be programmed; neutral language processing (NLP), a system which can understand and interpret human speech, facilitating greater communication between system components; and robotic agents, which work independently of human oversight.

AI currently supports various design goals within the SOLIDWORKS portfolio – the key focus is design optimisation, achieved through the creation of more intelligent designs which are lighter, stronger and more economical.

AI has similar applications in manufacturing: it can generate greater production efficiencies by identifying potential for improvements; find ways to lower costs such as through design modifications or use of alternate materials; identifying optimal manufacturing methodologies; and overseeing predictive maintenance.

As an example the AI Denoiser, a new tool in SOLIDWORKS Visualize which thanks to NVIDIA machine learning tech can anticipate, recognise and eliminate visual noise during rendering processes. This enables finished renderings to be produced up to ten times faster.

AI has the potential to enhance safety within manufacturing processes at the early stage of projects – a point at which it’s not typically given priority – by identifying relevant testing and determining any that may have otherwise been overlooked. It can also flag known points of failure to designers and even suggest design improvements from the data generated by the testing processes.

A further application for AI lies in its ability to sort through data whose potential value is obscured by its sheer breadth, such as sensor data. As an everyday Google’s Cloud Vision AI, which identifies image content by classifying images within categories and is able to detect faces, individual objects and even read words within images.

The continued evolution of AI is also set to create new employment opportunities, as Industry 4.0 will require human-machine interaction in ways yet to be identified, while AI cannot replace humans, it can be utilised for repetitive and taxing work, freeing us up to operate at a higher level.

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