Stefan Rink’s scientific contributions

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Publications (3)


Komplexität und wirtschaftlicher Nutzen künstlicher Intelligenz zur automatisierten und industrialisierten Erkennung additiv gefertigter Bauteile
  • Chapter

July 2021

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36 Reads

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1 Citation

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Walied Nasser

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Stefan Rink

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[...]

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Gerd Witt

Figure 2: Simplified overall AM process chain using HP MJF technology with percentage duration of operations for manual component identification (Time measurement by AM-Flow)
Figure 5: Complexity factors leading to a challenge for AI based AM component identification in the automotive industry
Figure 6: left: AM-VISION pilot setup (two-way conveyor belt) for pre-test study right: Operator interface "AM-LOGIC" with touch-screen and 3D rotating objects
Figure 9: Overview of cost increase-decrease comparison for manual and automated identification
Comparative expert evaluation of methods for component detection and differentiation

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Complexity and economical value of Artificial Intelligence for automated and industrialized recognition of additive manufactured components
  • Conference Paper
  • Full-text available

June 2021

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1,147 Reads

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1 Citation

Additive manufacturing (AM) is at a turning point towards industrialization and automation. Due to the ever shorter product development time in the automotive industry, the need for flexible production methods is increasing, and with it the need to manufacture larger quantities of prototype components. Therefore, there is a growing effort to further optimize and increase the efficiency of AM technologies and their process chain, which decisively shortens the way to series production. The current identification of AM components at the end of the overall process chain represents a non-scalable and cost-intensive manual, labor intensive process. The variety of geometries in prototyping leads to complex challenges where existing automation solutions cannot be implemented. AI- based image recognition can be an improvement in this regard. An analysis with regard to complexity, functionality and deployment will provide information about the economic efficiency of the automatic identification of prototype components.

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Citations (1)


... One critical subtask of part sorting is the recognition of parts. In [9], manual part recognition was identified as the primary time factor during the part sorting process, accounting for 40% of the total sorting time. Part recognition for sorting is particularly relevant for One critical subtask of part sorting is the recognition of parts. ...

Reference:

Recognition of Additive Manufacturing Parts Based on Neural Networks and Synthetic Training Data: A Generalized End-to-End Workflow
Komplexität und wirtschaftlicher Nutzen künstlicher Intelligenz zur automatisierten und industrialisierten Erkennung additiv gefertigter Bauteile
  • Citing Chapter
  • July 2021