Towards automated joining element design

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

doi:10.1016/j.procs.2019.09.163

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 journal › Conference article › Academic › peer-review

5 Citations (Scopus)

68 Downloads (Pure)

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 language	English
Pages (from-to)	87-96
Number of pages	10
Journal	Procedia computer science
Volume	159
Early online date	14 Oct 2019
DOIs	https://doi.org/10.1016/j.procs.2019.09.163
Publication status	Published - 2019

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1-s2.0-S1877050919313419-mainFinal published version, 605 KBLicence: CC BY-NC-ND

Cite this

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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",

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language = "English",

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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

M3 - Conference article

VL - 159

SP - 87

EP - 96

JO - Procedia computer science

JF - Procedia computer science

SN - 1877-0509

ER -

Towards automated joining element design

Abstract

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