Siemens has just issued details of the latest release of its flagship NX system which sees the beginning of the development team adding some features that take advantage of Machine Learning (ML) and Artificial Intelligence (AI).
Whereas most ML and AI references in the world of 3D design software usually focus on the generative design subject (and are mostly nonsense), in this instance, this is about helping the user to be more productive – specifically, having the system predict next steps the user might take when conducting an operation, then update the user interface to help users more efficiently use software to increase productivity.
What does that mean? Essentially, you begin a modelling or detailing activity in NX, then the system knows, through analysis and prediction (the machine learning part) what you’re most likely to do next, so brings up the most commonly used operations or commands.
The Siemens Digital Innovation Platform is continually expanding to enable customers to create the most comprehensive digital twin of the product, the production environment and of the performance of the product.
Integrating ML and AI into NX software offers the benefits of speed, power, efficiency and intelligence through learning, without having to explicitly program these characteristics.
This offers many opportunities for customers to enhance design process improvement and ultimately their product offerings and all with a reduced time to market.
The NX Command Prediction module is the first introduction of the machine learning-enabled NX adaptive user interface architecture to the market, and will be the basis for, and lead to, additional machine learning-driven UI solutions.
“Although extensive research conducted in the field of human-computer interaction has resulted in an excellent static interface, we still lack the perfectly-tailored dynamic interface that can suit all users,” said Bob Haubrock, senior VP, Product Engineering Software at Siemens PLM Software.
“The latest version of NX uses machine learning and artificial intelligence to monitor the actions of the user, and their successes and failures, so now we can dynamically determine how to serve the right NX commands or modify the interface to make the individual user more productive.
“Leveraging this learned-user interface knowledge for CAx environment personalisation can help our customers improve overall usage and adoption rates, ultimately leading to a more efficient product development processes.”