Goto

Collaborating Authors

 engineering company


Using deep learning surrogates to improve new product development

#artificialintelligence

For decades, digital technology has been quietly revolutionizing the world of engineering design. Three-dimensional digital models have supplanted drawings, and the development of simulation software has allowed engineers to replace many physical tests with faster, cheaper virtual ones. Engineering companies have invested hundreds of millions to make these computationally and data-intensive solutions more efficient. As computers have become more powerful, engineering teams have been able to develop ever-more-detailed digital models that replicate more of a product's characteristics and expected behaviors. Today, digital twins are changing the way products are designed, operated, and maintained in a host of fields, from industrial machines to medical devices.


Profitable service business through big data?

#artificialintelligence

Mechanical engineering is the backbone of Germany's industry. But will it stay that way? What does digital transformation mean for engineering companies, and what role does the service business play? We spoke with Bianca Illner, Managing Director of Management Services at VDMA. Peter Gaide is a freelance writer and the editor in chief of Transformation Beats.


Rolls-Royce navigates Google deal on machine learning for shipping - Internet of Business

@machinelearnbot

Rolls-Royce has signed a deal with internet giant Google in a move intended to help the British engineering company to develop autonomous ships. Under the terms of the deal, Rolls-Royce will use Google's Cloud Machine Learning Engine to further train an AI-based object classification system that it has developed, for detecting, identifying and tracking the objects that a vessel might encounter at sea. The agreement, which the companies claim is the first of its kind in the marine sector, was signed today at the Google Cloud Summit event in Stockholm. Rolls-Royce has some 4,000 marine customers worldwide, including 70 navies. The Google Cloud Machine Learning Engine uses the same neural net-based machine intelligence software that powers many of Google's own products, such as image and voice search.


Digital Engineering: Convergence of Disruptive Technologies

@machinelearnbot

We constantly talk about next-gen manufacturing, Industrie 4.0, IIoT etc, but I think the underlying nervous system supporting all these is connectivity and convergence. Increased connectivity and computational power have converted hype to reality. Previously Cloud, IoT, Artificial Intelligence (AI), Big Data and analytics were like nebulous concepts at boardroom discussions; but now they are mature enough and ready to be fully integrated into the design, engineering, and operational environment. Digitalization is impacting every aspect of our lives because three forces are reinforcing one another: consumer pull; technology push; and economic benefits. This was the theme of the two-day NASSCOM 2017 edition of the Design & Engineering Summit for which ARC Advisory Group was invited.