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@PHDTHESIS{Sanders:1020748,
      author       = {Sanders, Mark Pascal},
      othercontributors = {Schmitt, Robert H. and Biermann, Dirk},
      title        = {{V}olumetric error model for online machine tool
                      compensation},
      school       = {Rheinisch-Westfälische Technische Hochschule Aachen},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {RWTH Aachen University},
      reportid     = {RWTH-2025-09212},
      pages        = {1 Online-Ressource : Illustrationen},
      year         = {2025},
      note         = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
                      University; Dissertation, Rheinisch-Westfälische Technische
                      Hochschule Aachen, 2025},
      abstract     = {Achieving high-precision machining in large-scale
                      manufacturing poses significant challenges, particularly due
                      to thermal effects that induce structural deformations in
                      machine tools. Addressing these errors is crucial both for
                      precise part production and for enabling closer
                      quality-control loops through On-Machine Measurements.
                      Current mitigation strategies often rely on extensive
                      climatization measures, which are both energy-intensive and
                      costly. At the same time, rising pressure to lower energy
                      consumption and costs threaten the competitiveness of
                      precision machining, which underscores the necessity of
                      accurate machine tool calibration and thermal compensation
                      techniques for machine tools. In this thesis, a system for
                      real-time static and thermal error compensation for machine
                      tools will be presented contributing to the realization of
                      “Virtual Climatization”. The approach includes research
                      on a flexible machine tool calibration model that can
                      incorporate heterogeneous measurement data. The model forms
                      the basis for a significantly faster and automated machine
                      tool calibration procedure using an “On-The-Fly”
                      approach. It leverages laser tracker measurements captured
                      during continuous machine movement. By acquiring data
                      without frequent standstills, it allows for measuring static
                      machine tool errors with negligible thermal drift in under
                      ten minutes. The method thereby enables investigating
                      transient thermal behavior of the machine tool with a high
                      temporal resolution. An experimental validation involved
                      testing this calibration method on four different machine
                      tools covering medium to large working volumes. An
                      “Abstracted Physical Body model” can subsequently be
                      used to predict thermally induced deformations of the
                      machine tool structure using efficiently solved spline-based
                      mechanics. This model is designed to be applicable to
                      retro-fit applications, as it does not require detailed
                      structural information or training datasets, while still
                      providing good predictions. A method for integrating these
                      predictions into the existing machine control infrastructure
                      using standard machine tool communication interfaces is
                      investigated. By updating the machine’s geometric
                      compensation data, real time compensation can be achieved
                      without extensive hardware or control-system modifications.
                      A formal uncertainty analysis of all components is
                      performed. In alignment with established standards, the
                      contributions of all system components are identified and
                      analyzed. This analysis thereby enables using the
                      compensation system for traceable On-Machine Measurements. A
                      thorough experimental validation of the combined system is
                      executed in two stages. First, the combined system can
                      reduce deviations by up to 75 $\%$ in tests referenced to
                      laser tracker data on a medium-sized machine tool. Secondly,
                      the measurement uncertainty can be reduced by up to 50 $\%$
                      in On-Machine Measurement validation experiments based on
                      the VDI/VDE 2617 standards for CMM qualification. This can
                      ultimately lead to improved precision and accuracy in
                      manufacturing and geometric inspection, resulting in higher
                      product quality and reliability.},
      cin          = {417510 / 417200 / 080067},
      ddc          = {620},
      cid          = {$I:(DE-82)417510_20140620$ / $I:(DE-82)417200_20140620$ /
                      $I:(DE-82)080067_20181221$},
      pnm          = {DFG project G:(GEPRIS)390621612 - EXC 2023: Internet of
                      Production (IoP) (390621612) / WS-B2.I - Connected Job Shop
                      (X080067-WS-B2.I)},
      pid          = {G:(GEPRIS)390621612 / G:(DE-82)X080067-WS-B2.I},
      typ          = {PUB:(DE-HGF)11},
      doi          = {10.18154/RWTH-2025-09212},
      url          = {https://publications.rwth-aachen.de/record/1020748},
}