Table of contents:
- What the sensors can do
- A digital twin of the machine tool
- Smart engineering day
- Holistic picture of the machine
Video: With The Sensor To The Digital Twin
2023 Author: Hannah Pearcy | [email protected]. Last modified: 2023-05-24 11:12
Predictive Maintenance, or predictive maintenance, describes the process that sensors monitor a machine or machine parts by as register irregularities vibrations and share. The relevant part can then be replaced promptly on the basis of this warning.
The example of machine tools shows how useful this maintenance can be. These precision devices mill, turn and grind workpieces with millimeter precision, they have to work with high precision and smoothly. Slight vibrations can lead to errors and inaccuracies in the finished workpiece. Sensors can perceive and warn these vibrations in good time.
Rethinking product development
However, these predictive maintenance systems are usually isolated solutions. The information that a component should be replaced is rarely used. Researchers at the Fraunhofer Institute for Production Systems and Design Technology IPK have developed a new solution here: They integrate the sensors into an internet platform that stores the entire life cycle of one or more machine tools. This makes extensive data analysis possible, with which machines or entire work processes can be optimized.
What the sensors can do
The heart of the new system is a sensor board that contains a commercially available sensor chip, a Micro Electro Mechanical System (MEMS). These MEMS are small silicon components, on the surface of which various technical components are linked. For example, they can measure environmental stimuli such as vibrations and process them with a processor connected to them. The MEMS and processor together form a sensor node.
Claudio Geisert from Fraunhofer IPK explains: “These kinds of MEMS are installed millions of times in cars and smartphones. They are inexpensive and yet sufficiently precise for our purposes.” Important: The processing of the sensor signals takes place directly on the sensor node. The processor automatically detects a fault and can forward this information.
The researchers are showing how this solution can look at the Hanover Fair 2020 at the Fraunhofer joint stand in Hall 6, Stand A26. To do this, they chose a central element of a machine tool: a ball screw drive with which a workpiece carrier in the machine is moved extremely precisely on a spindle. If this spindle wears out, it causes unwanted vibrations that can cause defects on the workpiece.
A digital twin of the machine tool
The information is sent to an Internet of Things platform (IoT platform), which alerts the service center, which then decides what to do. For example, it specifies a good time to replace the spindle so that production downtimes due to downtimes are avoided. Secondly, this IoT platform contains a so-called digital twin of the machine tool - a digital copy that contains the history of the machine and all states and operating parameters.
If the defective spindle is finally replaced, the digital twin also receives the information that it now contains a new component. The operators of the machines could, for example, recognize whether certain processes in the systems significantly increase wear. This makes it possible to adapt the work processes accordingly. And machine tool manufacturers can, for example, receive valuable information on how to further optimize their systems.
Smart engineering day
The digitization of production requires a rethink in product development. The Smart Engineering Day offers decision support for the selection of the most suitable methods for the conception, design and development of smart products and machines.
Holistic picture of the machine
The coupling of the real machine with the IoT platform also has advantages for the service staff on site at the machine. With the solution, the technician first scans a QR code on the machine to check whether he is working on the correct machine. This is particularly important in companies where entire machinery can be found. The component can also be scanned and compared with the data in the digital twin - so that another component is not accidentally replaced. The employee can also use a tablet to call up instructions for removing and installing the component.
Once the repair has been carried out, a test run can be started directly from the machine. If everything went well, the employee presses an OK button - and thus gives the signal to update the component in the digital twin as well.
"With the coupling of the machine and the sensors to the IoT platform, we get a holistic picture of a machine or the entire fleet for the first time, " says Claudio Geisert. This would enable large companies to keep an eye on their entire machine park across individual locations. The Fraunhofer IPK solution has already been developed to such an extent that it can be used in industry.