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Production Engineering
Article . 2020 . Peer-reviewed
License: CC BY
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Production Engineering
Article
License: CC BY
Data sources: UnpayWall
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https://dx.doi.org/10.14279/de...
Article . 2020
License: CC BY
Data sources: Datacite
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Modeling of vacuum grippers for the design of energy efficient vacuum-based handling processes

Authors: Felix Gabriel; Markus Fahning; Julia Meiners; Franz Dietrich; Klaus Dröder;

Modeling of vacuum grippers for the design of energy efficient vacuum-based handling processes

Abstract

AbstractVacuum-based handling is widely used in industrial production systems, particularly for hand-ling of sheet metal parts. The process design for such handling tasks is mostly based on approximate calculations and best-practice experience. Due to the lack of detailed knowledge about the parameters that significantly influence the seal and force transmission behavior of vacuum grippers, these uncertainties are encountered by oversizing the gripping system by a defined safety margin. A model-based approach offers the potential to overcome this limitation and to dimension the gripping system based on a more exact prediction of the expected maximum loads and the resulting gripper deformation. In this work, we introduce an experiment-based modeling method that considers the dynamic deformation behavior of vacuum grippers in interaction with the specific gripper-object combination. In addition, we demonstrate that for these specific gripper-object combinations the gripper deformation is reversible up to a certain limit. This motivates to deliberately allow for a gripper deformation within this stability range. Finally, we demonstrate the validity of the proposed modeling method and give an outlook on how this method can be implemented for robot trajectory optimization and, based on that, enable an increase of the energy efficiency of vacuum-based handling of up to 85%.

Keywords

prediction model, vacuum-based handling, 600 Technik, Medizin, angewandte Wissenschaften::600 Technik::600 Technik, Technologie, energy efficiency

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    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    23
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
23
Top 10%
Top 10%
Top 10%
hybrid