Towards automated joining element design

Derk Hendrik Dominick Eggink*, Marco Wilhelm Groll, Daniel F. Perez-Ramirez, Johannes Biedert, Christoph Knödler, Patrick Papentin

*Corresponding author for this work

    Research output: Contribution to journalConference articleAcademicpeer-review

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    Abstract

    Product variety and its induced manufacturing complexity remains to increase and therefore greatens challenges for design of joining elements. Historically, joining element design was a paper-based process with incomplete variety documentation and is digitalized only by replacing paper for 3D space. Currently, joining element design remains an ambiguous manual task with limited automation, resulting in long iterative, error prone development trajectories and costly reworks. Thus, processes in practice conflict with required capabilities. Artificial intelligence helps to solve such conflicts by taking over repetitive tasks, preventing human errors, optimizing designs and enabling designers to focus on their core competencies. This paper proposes a novel artificial intelligence method toolbox as a foundation to automate joining element design in manufacturing industries. The methodology aims to incorporate multiple lifecycle requirements including large product variety.
    Original languageEnglish
    Pages (from-to)87-96
    Number of pages10
    JournalProcedia computer science
    Volume159
    Early online date14 Oct 2019
    DOIs
    Publication statusPublished - 2019

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    Eggink, Derk Hendrik Dominick ; Groll, Marco Wilhelm ; Perez-Ramirez, Daniel F. ; Biedert, Johannes ; Knödler, Christoph ; Papentin, Patrick. / Towards automated joining element design. In: Procedia computer science. 2019 ; Vol. 159. pp. 87-96.
    @article{6dcb65bcdc8c4bbdbdcff360fd3c7a0e,
    title = "Towards automated joining element design",
    abstract = "Product variety and its induced manufacturing complexity remains to increase and therefore greatens challenges for design of joining elements. Historically, joining element design was a paper-based process with incomplete variety documentation and is digitalized only by replacing paper for 3D space. Currently, joining element design remains an ambiguous manual task with limited automation, resulting in long iterative, error prone development trajectories and costly reworks. Thus, processes in practice conflict with required capabilities. Artificial intelligence helps to solve such conflicts by taking over repetitive tasks, preventing human errors, optimizing designs and enabling designers to focus on their core competencies. This paper proposes a novel artificial intelligence method toolbox as a foundation to automate joining element design in manufacturing industries. The methodology aims to incorporate multiple lifecycle requirements including large product variety.",
    author = "Eggink, {Derk Hendrik Dominick} and Groll, {Marco Wilhelm} and Perez-Ramirez, {Daniel F.} and Johannes Biedert and Christoph Kn{\"o}dler and Patrick Papentin",
    year = "2019",
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    language = "English",
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    Eggink, DHD, Groll, MW, Perez-Ramirez, DF, Biedert, J, Knödler, C & Papentin, P 2019, 'Towards automated joining element design', Procedia computer science, vol. 159, pp. 87-96. https://doi.org/10.1016/j.procs.2019.09.163

    Towards automated joining element design. / Eggink, Derk Hendrik Dominick; Groll, Marco Wilhelm; Perez-Ramirez, Daniel F.; Biedert, Johannes; Knödler, Christoph; Papentin, Patrick.

    In: Procedia computer science, Vol. 159, 2019, p. 87-96.

    Research output: Contribution to journalConference articleAcademicpeer-review

    TY - JOUR

    T1 - Towards automated joining element design

    AU - Eggink, Derk Hendrik Dominick

    AU - Groll, Marco Wilhelm

    AU - Perez-Ramirez, Daniel F.

    AU - Biedert, Johannes

    AU - Knödler, Christoph

    AU - Papentin, Patrick

    PY - 2019

    Y1 - 2019

    N2 - Product variety and its induced manufacturing complexity remains to increase and therefore greatens challenges for design of joining elements. Historically, joining element design was a paper-based process with incomplete variety documentation and is digitalized only by replacing paper for 3D space. Currently, joining element design remains an ambiguous manual task with limited automation, resulting in long iterative, error prone development trajectories and costly reworks. Thus, processes in practice conflict with required capabilities. Artificial intelligence helps to solve such conflicts by taking over repetitive tasks, preventing human errors, optimizing designs and enabling designers to focus on their core competencies. This paper proposes a novel artificial intelligence method toolbox as a foundation to automate joining element design in manufacturing industries. The methodology aims to incorporate multiple lifecycle requirements including large product variety.

    AB - Product variety and its induced manufacturing complexity remains to increase and therefore greatens challenges for design of joining elements. Historically, joining element design was a paper-based process with incomplete variety documentation and is digitalized only by replacing paper for 3D space. Currently, joining element design remains an ambiguous manual task with limited automation, resulting in long iterative, error prone development trajectories and costly reworks. Thus, processes in practice conflict with required capabilities. Artificial intelligence helps to solve such conflicts by taking over repetitive tasks, preventing human errors, optimizing designs and enabling designers to focus on their core competencies. This paper proposes a novel artificial intelligence method toolbox as a foundation to automate joining element design in manufacturing industries. The methodology aims to incorporate multiple lifecycle requirements including large product variety.

    U2 - 10.1016/j.procs.2019.09.163

    DO - 10.1016/j.procs.2019.09.163

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    SP - 87

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    JO - Procedia computer science

    JF - Procedia computer science

    SN - 1877-0509

    ER -