M.F. Zah’s scientific contributions

... The dynamic structural behavior of machine tools greatly influences the success of cutting processes, making it the objective of numerous modeling efforts. Fundamentally, two modeling strategies can be distinguished [1]: On the one hand, there is the so-called experimental approach, which is based on measurements of the real system's behavior and results in a gray-box or black-box model replicating the input-output behavior (e.g., in the form of transfer functions [2,3]). Their identification, that is the process of determining values for the involved model parameters, is often referred to as "system identification" or, in case in situ machining measurements are used, as "rapid identification". ...

Reference:

Automated Identification of Linear Machine Tool Model Parameters Using Global Sensitivity Analysis

... In the past, many researchers used machine learning classifiers for condition monitoring of ball screw drives [10][11][12][13][14][15][16]. This approach can be followed when fault data is available (supervised anomaly detection). ...

Reference:

Application of machine learning for fleet‑based condition monitoring of ball screw drives in machine tools