igus® Launches AI-Powered igusGO App To Help Users Find the Right Motion Plastics Solutions for Their Industrial Application
igus®, a global manufacturer of motion plastics, has developed igusGO, a free mobile app that uses artificial intelligence (AI) to help users find the ideal motion plastics products and technologies for their application.
The app allows users to take a simple photo of their equipment or application — whether it's a coffee machine, bottling line or excavator. Using AI, the app then recommends suitable igus bearings, linear guides, cable carriers and other products to reduce costs and extend machine service life.
"Many of our customers are not aware of just how many application options there are for all our products. Therefore, we developed the igusGO app. It's an addition to our service offer and available 24/7," said Frank Blase, CEO at igus.
The igusGO app currently recognizes over 450 industrial applications, and its database continues to grow daily with each user submission.
"The igusGO app is intended to be a source of inspiration. At the same time, we want to open the app to a community where everyone can participate and share their projects with others," noted Blase.
The AI-powered igusGO app can also help customers easily reorder the igus e-chain® energy chain series of cable carriers. Once users photograph an installed e-chain using igusGO, the app identifies the correct replacement part number from 50 available product series.
Peter Wirth, Head of Digital Sales and Marketing at igus, said, "With our product recognition, we want to help all employees in companies order spare parts really quickly."
The igusGO app is available for free download in English and German on Android, iOS and as a web version at app.igusgo.cloud. Future updates will include the addition of an AI chatbot to answer common user questions.
https://www.igus.com/
Featured Product
How to overcome GNSS limitations with RTK correction services
Although GNSS offers ubiquitous coverage worldwide, its accuracy can be hindered in some situations - signals can be attenuated by heavy vegetation, for example, or obstructed by tall buildings in dense urban canyons. This results in signals being received indirectly or via the multipath effect, leading to inaccuracy, or even blocked entirely. Unimpeded GNSS positioning in all real world scenarios is therefore unrealistic - creating a need for supporting technologies, such as real time kinematic (RTK) positioning and dead reckoning, to enable centimeter-accuracy for newer mass-market IoT devices.