| Developers: | STAN Machine Tool Company |
| Date of the premiere of the system: | May 2021 |
| Branches: | Mechanical Engineering and Instrument Engineering |
Main article: Augmented Reality (AR, Augmented Reality)
2021: Announcement of platform for implementation of digital workshop technology based on AR
At the end of May 2021, the Russian machine manufacturer STAN announced the creation, according to the company, of the country's first industrial platform for the introduction of digital workshop technology based on augmented reality (AR).
The solution called "StAR" is a software and hardware complex to which you can connect AR glasses, tablets and smartphones. The platform received software that allows you to create interactive digital instructions for the operation and repair of industrial equipment or virtual simulators. You also have access to a library of finished 3D machine models. The system is compatible with all modern machine models of STAN.
On the basis of StAR, a virtual assistant for remote repair and maintenance of numerical control machines (CNC) has already been implemented. The program combines an interactive operation manual and an environment for training employees. The operator sees the key indicators of the machine using AR glasses or on the smartphone screen. After answering a number of clarifying questions, the specialist receives hints: the system visually highlights the necessary component or assembly of the machine that needs maintenance or repair. The interface provides the function of online communication with a specialist of the STAN service center.
In addition to the virtual assistant, the StAR platform implements the concept of the workplace of the future using virtual space. In the training mode, the operator will be able to go through all the stages of servicing the machine in augmented reality. It is noted that this approach will prepare personnel for work on Industry 4.0 standards.
According to the developer, StAR helps reduce the cost of servicing and repairing machine tools by 34%, as well as reduce the number of personnel errors by 87%.[1]
Notes
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