When machine tools communicate with each other

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Schaeffler Technologies AG & Co. KG

Using web services or apps, calculations can be initiated in the cloud.

Yet simply collecting and saving data does not create any added value for the operator. The decisive factor is intelligent evaluation of the data in the form, for example, of recommended action or an autonomous triggering of actions. And evaluation of this kind is based on the assumption that, besides the measured value itself, a sufficiently large quantity of data, which is correlated with other data, provides patterns. These offer a new quality of meaningfulness, for example in relation to the condition of the bearings and thus the status of the machine. With suitable algorithms, the patterns can be recognised automatically and the necessary action recommendations made and actions carried out.

For this, decentralised functional units are required, capable of functioning autonomously as well as in the network. The local intelligence can for example evaluate the data locally. Supplementary evaluations requiring a greater calculating capacity can be called up via the cloud link. Likewise, a holistic evaluation in the cloud is carried out on the basis of the data from all connected machines.

Schaeffler designed the horizontal networking along the value creation chain and also the vertical integration from the sensor to the cloud itself in order to learn how complexity and the requirements for products and services have to be adapted in production.

Production profits from digitalisation

The possibilities of digitalisation are not limited to production machines. The production environment, too, can profit from it. This enables the avoidance of an island solution which could make manual intervention necessary. Vertical integration providing a link to the ERP system continues to be necessary for automatic order processing.

Production: here unambiguous identification of the individual components is important. For this, a marking installation which gives each component an ambiguous identity via data matrix code is integrated. This identity accompanies the component throughout the entire production process and is included in the ID of any resulting component assembly. The history of the component can thus be analysed according to the principles of traceability.

• Process: the determination of the forces at the tool centre point (TCP) permits further optimisation regarding machine utilisation as well as for the process itself: it is quite conceivable, using a mathematical model, to determine the shift in the TCP due to the forces in operation and to send possible correction values to the control system in real time. In addition, the processing forces which will probably arise can be determined in advance using process simulations. This then provides a plan value which is not allowed to lie outside a set range, since this would indicate an incorrect status.

• Energy: besides measuring the current energy consumption, which can be linked to the processing step in question, it is possible to determine future energy requirements by process simulation. In combination with the empirical values, a more precise prognosis for the energy consumption can be made, which is of value not only in needs-oriented energy purchasing, but also in production planning in the sense of minimising energy peaks for the company as a whole.

• Machine status: the machine status is detected using the classical monitoring procedures with the help of vibration monitoring. In addition, the state of the lubricants in various bearings is measured and evaluated. With need-oriented lubrication, besides a conservational approach to resources, functionality is guaranteed without influence on the machine performance.

• Maintenance: maintenance serves to keep the production process stable. By classification of the production processes, the load spectrums of the machine are made transparent. For example, it is currently possible, using the Bearinx bearing calculation program, for the nominal remaining service lifetime of the bearings to be calculated online via a web service. The aim of this is to control the production, on the basis of a simulation of the planned production orders and the anticipated resulting service lifetimes of the individual components, in such a way as to keep the machine availability high.

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