Two prototypes have been built based on the 4th generation of the DMG Mori DMC 80 FD duoBLOCK machining centre. One prototype will be put into volume production in a precision bearing cell at the Schaeffler plant in Höchstadt. The other was unveiled on the DMG MORI stand at the EMO 2015 exhibition.
In this project, the two prototypes have additional sensors integrated into almost every bearing position relevant to the machining process. This enables vibrations, forces, temperatures and pressures to be measured, which provides valuable information about the condition of the machine; this information can help predict component failure, and so help plan maintenance intervals.
In order to make all the measurement data accessible, the machine is provided with an internal network to which all additional sensors, actuators and evaluation units are connected. A gateway provides a link to a cloud-based distributed data storage platform. In order to ensure that data can be exchanged with the machine control system, a Profibus industrial data network connection is integrated into the PLC for time-critical and process data. Further information was taken from the human machine interface (HMI). The data from the machine is saved locally in the gateway and copied into the Schaeffler cloud. This ensures the machine’s data history is available without having to connect to the network. Schaeffler explains that according to the Industry 4.0 idea, these data can be mined for trends using software algorithms (web services or apps) and any necessary recommended actions taken.
- The machine also includes a marking unit to provide each component with a unique data matrix code that remains with the components throughout the manufacturing process and forms part of the unit ID. The code provides traceability and enables a component’s history to be analysed.
- Sensors on the machine determine the forces on the tool centre point (TCP) to allow further optimisation of machine loading, as well as the process itself. Displacement at the TCP due to loads that occur during machining can be determined using a mathematical model and potential correction measures can be fed back to the control system in real time.
- In addition to measuring actual energy usage, the system also determines future energy demands through process simulation. This enables the system to create a more accurate prediction of energy requirements.
- The condition of the machine is recorded using traditional vibration monitoring techniques. The condition of the lubricant is also measured and evaluated at different points. Doing so guarantees functional capacity on one hand, whilst conserving resources on the other.
