Smart 3D models for increasing productivity
The potential to boost productivity: Siemens research experts are developing an entirely new method for augmenting 3D CAD models with additional information. These 3D models then enable smart manufacturing with a consistent, integrated product creation chain from the material to manufacturing in the factory.
By Katrin Lange
On the shop floor of the Nuremberg motor factory, a tool is milling its way into the man-sized housing of a stator. What’s unusual here is that the program for the milling machine has automatically taken the information about the geometry, permissible tolerances, and surface specifications from a new (virtual) 3D model. This eliminates the complex programming of the milling machine that used to be necessary. Production manager Sebastian Grimm explains. “I think the 3D model-based method may well increase our productivity by 20 to 30 percent throughout the entire process chain.” This is made possible by the now consistent data chain, which digitalizes – and thus simplifies and speeds up – the planning process in manufacturing. Employees of Siemens’ research department recently developed the last piece of the puzzle. In particular, they’re helping make it possible to offer production departments solutions for small batch sizes and individual requirements while also meeting the ever higher quality and efficiency specifications.
Directly on site: functional information
Alexander Nowitschkow, an expert in machine programming, explains. “Our approach is aimed at augmenting the 3D CAD model used by many companies with information in such a way that the 2D drawing still in current use in many areas of design and manufacturing are rendered completely superfluous. This 3D model, known as a functional information model, or FIM for short, thus contains not only all geometric information as usual but also additional information, such as permissible tolerances, information about surface quality, and even material properties. The experts place this additional information in the FIM model directly on the particular geometric element, such as a bore hole, a milled pocket, or a recess. Production and assembly engineers can seamlessly use 3D models generated with this method in programming CNC machine controllers and measuring devices as well as in assembly planning.
Automatic: information transfer
And there are other benefits as well. Work schedulers, CNC programmers, and quality planners see a display of the exact product and process information they need for their own work steps. The experts have also paved the way for automation. The FIM model thus automatically transfers its information to follow-up systems, such as CAM (CNC 3D programming) and CMM (3D measuring device programming), where it is interpreted directly. This makes the functional information model machine-readable and transfers the information completely and in a targeted manner throughout the entire process chain. Design changes also affect all 3D models in the subsequent process steps, since the model can be called up in real time from the product lifecycle management system Teamcenter.
Implemented: Seamless process with an intelligent 3D model
At the end of the milling process, Grimm checks whether the motor housing has the desired quality. The measuring device has already received the right program with the aid of the FIM model and immediately feeds its measurement results back into the original design model. The quality expert can then very easily see whether all quality requirements have been met. Nowitschkow explains. “Our research results from the gas turbine, wind gearbox, and electric motor production show that we can implement a consistent 3D model-based process with the FIM method. This gives us consistent data, a smooth change management process, and uniform communication between logistics, quality, manufacturing, and producer systems.” In the future, data from 3D scans, for example of maintenance components, will also be integrated in this model and three-dimensional CAD files generated automatically from them. This process maps the entire product lifecycle, making it more accurately understandable.
Jan 17, 2019
Katrin Lange is an independent journalist based in Germany.
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