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@PHDTHESIS{MendlHeinisch:1008873,
      author       = {Mendl-Heinisch, Michael Otto},
      othercontributors = {Schuh, Günther and Boos, Wolfgang},
      title        = {{B}ewertung technischer {P}roduktänderungen mittels
                      prädiktiver {D}atenanalyse; 1. {A}uflage},
      volume       = {2025,7},
      school       = {RWTH Aachen University},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {Apprimus Verlag},
      reportid     = {RWTH-2025-03209},
      isbn         = {978-3-98555-267-2},
      series       = {Ergebnisse aus der Produktionstechnik},
      pages        = {1 Online-Ressource : Illustrationen},
      year         = {2025},
      note         = {Druckausgabe: 2025. - Auch veröffentlicht auf dem
                      Publikationsserver der RWTH Aachen University; Dissertation,
                      RWTH Aachen University, 2024},
      abstract     = {Manufacturing companies face a variety of challenges when
                      managing changes along the product development process.
                      Strong market dynamics and the shortening of product life
                      cycles are increasingly exacerbating these challenges.
                      Against this background and in view of the increasing
                      transformation of the market from a seller's to a buyer's
                      market, the effective and efficient processing of technical
                      changes is now a mandatory task. However, modern data
                      analysis methods such as the Random Forest Algorithm are
                      generally not yet used for forecasting. With reference to
                      the initial situation described above, the aim of this work
                      was to efficiently design the handling of technical changes.
                      This includes in particular the selection of the technical
                      changes to be processed as well as minimizing the overall
                      change costs by bundling technical changes with similar
                      resource requirements. The methodology focused on the
                      allocation of technical changes using a description model
                      and the determination of basic types of technical changes.
                      Furthermore, the costs and benefits of technical changes
                      were described, whereby the costs were determined using
                      predictive data analysis. Finally, the technical changes
                      were bundled to minimize the overall change effort. In
                      chapter 1 of this thesis, the motivation for the work was
                      presented and the objectives were derived from this. Chapter
                      2 introduced the relevant principles and definitions. For
                      this purpose, the object area and the target area as well as
                      the solution hypothesis of the thesis were developed.
                      Technical change management was first described as part of
                      product development in order to then emphasize the
                      importance of technical changes. In chapter 3, theoretical
                      and practical deficits were identified in order to ensure
                      the relevance of the work. The findings of the first
                      chapters were used in Chapter 4 to design the methodology.
                      Chapter 5 detailed the methodology for evaluating technical
                      changes using predictive data analysis. To ensure the
                      applicability of the methodology, a validation of the
                      methodology was carried out in chapter 6. The insights
                      gained here were then critically reviewed and further
                      optimization potentials for the methodology were developed.},
      cin          = {417210 / 417200},
      ddc          = {620},
      cid          = {$I:(DE-82)417210_20140620$ / $I:(DE-82)417200_20140620$},
      typ          = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
      doi          = {10.18154/RWTH-2025-03209},
      url          = {https://publications.rwth-aachen.de/record/1008873},
}