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Available locations for new factories and the suitability of these locations changes, especially due to climate change. Long-term consequences and high costs entailed by factory location selection become more difficult to predict. The decision process for factory location therefore becomes more complex, uncertain and time-consuming. We aim to develop a data-driven digital decision support application for factory location selection. This paper presents the process to be implemented in that system. We research and refine established processes to enable data-driven, objective and sustainable factory location selection. Finally, we give an outlook on the decision support system to be developed.

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Process Design for Digitally Assisted Location Selection for Sustainable Factories

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年

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  • Günther Schuh,
  • Esben Schukat,
  • Siyuan Wang,
  • Felix Paßlick,
  • Carsten Engeln

摘要

Available locations for new factories and the suitability of these locations changes, especially due to climate change. Long-term consequences and high costs entailed by factory location selection become more difficult to predict. The decision process for factory location therefore becomes more complex, uncertain and time-consuming. We aim to develop a data-driven digital decision support application for factory location selection. This paper presents the process to be implemented in that system. We research and refine established processes to enable data-driven, objective and sustainable factory location selection. Finally, we give an outlook on the decision support system to be developed.