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It has enhanced the performance of a CNC milling machine by fitting several dozen new sensors, in addition to those with which it is equipped as standard, in order to collect large volumes of data that can be evaluated in the cloud.
“The machine is now equipped with sensors in more than 60 positions that record measurement values for pressures, vibrations and forces,” says Sebastian Mergler, digital services project manager at Schaeffler.
The machine records much more data than previously, but crucially it does so in a real production context, and as such is the prototype of how a CNC machine tool would operate in a genuine I4.0 environment. Appropriately, the rolling bearings it makes are used as components in machine tools and as such must comply with stringent specifications for accuracy. Their diameter and roundness must comply with the target values to within two microns.
Off to the cloud
The data generated at these measuring points is saved not only on the machine itself but also in pre-analysed form in the company’s own cloud computing system. Communication with central servers takes place via a secure gateway. The condition of individual components on the machine tool can be viewed at any time either using the operating terminal on the machine or via a device connected to the internet, such as a tablet.
Each component made on the machine receives its own ID through the application of a unique data matrix code. All data generated during milling or subsequent machining processes can therefore be assigned to a specific component. By comparing the data for the individual components, Schaeffler can detect deviations, correct them and optimise the manufacturing processes. The implications range from achieving higher precision to reducing energy consumption and lubricant supply.
But the benefits are perhaps most immediately apparent at shopfloor level, as Mergler made clear. “The machine tool’s condition is effectively transparent at any time,” he stated. “Everyday production processes become more efficient and easier to plan. The machine operator can schedule bearing replacement, which avoids unplanned machine downtimes.”
Mergler said that crucial parameters that are now recorded include “the load data, particularly for the main spindle, the linear guidance and the tool centre point,” since these allow potential overloads to be made evident. “The user interface is central,” he added. “It provides the user with precise data about the status of the production process. Determining the forces then allows us to further optimise the load conditions in the machine.”
Monitoring loads
The operating panel at the machine allows the correct main spindle operating load to be set and the current loads to be monitored. If the load limit is exceeded, an active warning occurs, and the load can be adjusted immediately. The same is true for vibrations on the machine components.
The sensors also allow analysis of the condition of the lubrication film at critical points in the machine. If the condition is no longer sufficient, the required quantity of fresh grease is automatically delivered to the bearing position. Machine downtime caused by insufficient lubrication can therefore be eliminated.
Schaeffler believes it will benefit from the project not only by using the knowledge within its own production processes but also by being able to present itself to machine-tool manufacturers as an I4.0 solutions provider.
“The project has demonstrated how significant the productivity gains are through the improved use of data,” said Mergler. “All process and quality data for parts can now be traced. Data analyses will even make it possible to predict quality results whereby machine operators can proactively influence the process.”
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Content published by Professional Engineering does not necessarily represent the views of the Institution of Mechanical Engineers.