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Causal Models and a Prototypical Implementation of a Pipeline for Causal Analysis in Manufacturing

  • 2026
  • OriginalPaper
  • Chapter
Published in:
Authors
Henrik Russell
Henry Himmelstoß
Fabian Böttinger
Simon Kern
Thomas Bauernhansl
Published in
Product Lifecycle Management. PLM in the Age of Model-Based Engineering in Industry
Publisher
Springer Nature Switzerland

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Abstract

This chapter delves into the application of causal models to enhance the production of electrolyser stacks, a critical component in the hydrogen economy. The authors present a prototypical implementation of a pipeline for causal analysis, which aims to identify and address quality issues in manufacturing processes. The chapter covers several key topics, including the importance of causal methods in manufacturing, the challenges of data collection and processing across different processes, and the use of emulated data to validate causal relationships. The authors also discuss the system architecture that enables this causal analysis, highlighting the role of digital twins and the Asset Administration Shell (AAS) in data management. The chapter concludes with a discussion on the potential of this approach to optimize manufacturing processes and reduce costs, paving the way for more efficient and reliable production of electrolyser stacks.
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previous chapter Design and Optimization of Facility Layouts Using 3D Models and Reinforcement Learning
next chapter Object Detection in Engineering Drawings: An End-to-End Conversion Pipeline from 2D Drafting Annotations to 3D Product Manufacturing Information
Title
Causal Models and a Prototypical Implementation of a Pipeline for Causal Analysis in Manufacturing
Authors
Henrik Russell
Henry Himmelstoß
Fabian Böttinger
Simon Kern
Thomas Bauernhansl
Copyright Year
2026
Book
Product Lifecycle Management. PLM in the Age of Model-Based Engineering in Industry

Print ISBN: 978-3-032-09699-9

Electronic ISBN: 978-3-032-09700-2

Copyright Year: 2026

DOI
https://doi.org/10.1007/978-3-032-09700-2_18
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