The manufacturing industry often sets the trends for technology adoption in industrial settings. For example, the automation journey began a half-century ago with the first industrial robot — a 2,700-pound behemoth Unimate prototype — installed in a GM factory in 1959. Since then, robotics technology has significantly evolved and expanded beyond traditional manufacturing. Today, robots are integral to various industries, undertaking tasks like automated bricklaying in construction, efficient goods handling in logistics and warehousing and critical functions such as dispensing medication within hospitals.

It’s common to hear the metaverse described as a 3D experience layer of the internet. The “industrial metaverse” is a more difficult concept to define. According to Forrester, it’s an umbrella term for a collection of different technologies. Some of those technologies have existed for years just waiting to come together.

Following a previous blog on the topic, Understanding the Industrial Metaverse, in this blog Stephen Graham, executive vice president and general manager, Nexus, takes an introductory look at the four building blocks, highlighting some of the key issues.

For this paper, the digital twin refers to a digital asset that exists alongside the physical asset during its operational life, providing insight into and feedback on the physical asset’s performance and health. Thus, the focus is on the DTI, with the potential to aggregate data into a DTA for the gearbox design being considered, and within the DTE set up by Hexagon.

In respect of the physical asset across its life, nothing is more important about its performance than its ability to function, i.e., reliability, and for CAE, nothing is of greater importance than to be able to predict the reliability of a product being designed. Thus, for this study, whilst gearbox noise, efficiency, and thermal behavior may be of interest, the primary interest is fatigue and reliability.

Hexagon’s Manufacturing Intelligence division recently introduced Elements, new simulation software that helps engineering teams understand the behavior of systems that are becoming increasingly complex in modern products. Using the software, teams can evaluate the performance and feasibility of new design concepts quickly to inform more efficient product development and reduce risk and cost.

Hexagon’s Manufacturing Intelligence division has introduced Elements, a new simulation software that helps engineering teams understand the behavior of systems that are becoming increasingly complex in modern products. Using the software, teams can evaluate the performance and feasibility of new design concepts quickly to inform more efficient product development and reduce risk and cost.

Hexagon’s Manufacturing Intelligence has released a comprehensive report entitled "Recharging the Automotive Market." The body of work was produced by Hexagon and draws from the original research conducted with Wards Intelligence and Informa Tech Automotive Group (ITAG).