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Siemens Machine Tool Fingerprinting Enables Process Quality Optimization

Siemens is extending its edge application Analyze MyMachine / Condition with a corresponding Mindsphere application and thus demonstrating how edge computing and cloud computing can be intelligently combined. The Sinumerik Edge Application Analyze MyMachine / Condition, which the company presented last year at the EMO exhibition, uses high-frequency CNC data to create the mechanical fingerprint of a machine tool. In the application, users can capture and evaluate various parameters such as stiffness, friction, and backlash in the individual axes with the help of flexibly configurable measurement series. The measurement results can then be visualized and compared with reference data.

The new complementary Mindsphere application to Analyze MyMachine / Condition now allows cross-machine comparisons and evaluations. Warning and service thresholds can be visualized individually for each asset and the states of several machines can be monitored and visualized over a longer period of time. This allows users to detect deviations over a longer period of time. Anomalies can also be detected across different machines. Analyze MyMachine / Condition for Sinumerik Edge and for Mindsphere thus contributes to the early detection of critical deviations and to avoid production downtimes due to needs-based maintenance measures. This increases the availability of machine tools and raises their productivity.

With edge computing, data is processed decentrally at the point of origin. The SINUMERIK Edge is a specification of the Siemens Industrial Edge platform, with which users can tap the full potential of their machine tools. It offers access to all available machine data, with up to 1000 values per second per variable. The intelligent processing of this data enables optimization of process quality, increased machine availability and higher machine productivity. The safe and scalable platform extends machine tools with additional functions and ensures the smooth operation of production.

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