Skip to main content
We gratefully acknowledge support from the Simons Foundation, member institutions, and all contributors. Donate
arXiv logo
Cornell University Logo

Computer Science > Artificial Intelligence

arXiv:2204.12908 (cs)
[Submitted on 26 Apr 2022 (v1), last revised 4 Nov 2022 (this version, v2)]

Title:Capabilities and Skills in Manufacturing: A Survey Over the Last Decade of ETFA

Authors:Roman Froschauer, Aljosha Köcher, Kristof Meixner, Siwara Schmitt, Fabian Spitzer
View PDF
Abstract:Industry 4.0 envisions Cyber-Physical Production Systems (CPPSs) to foster adaptive production of mass-customizable products. Manufacturing approaches based on capabilities and skills aim to support this adaptability by encapsulating machine functions and decoupling them from specific production processes. At the 2022 IEEE conference on Emerging Technologies and Factory Automation (ETFA), a special session on capability- and skill-based manufacturing is hosted for the fourth time. However, an overview on capability- and skill based systems in factory automation and manufacturing systems is missing. This paper aims to provide such an overview and give insights to this particular field of research. We conducted a concise literature survey of papers covering the topics of capabilities and skills in manufacturing from the last ten years of the ETFA conference. We found 247 papers with a notion on capabilities and skills and identified and analyzed 34 relevant papers which met this survey's inclusion criteria. In this paper, we provide (i) an overview of the research field, (ii) an analysis of the characteristics of capabilities and skills, and (iii) a discussion on gaps and opportunities.
Comments: \c{opyright} 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Subjects: Artificial Intelligence (cs.AI); Systems and Control (eess.SY)
Cite as: arXiv:2204.12908 [cs.AI]
  (or arXiv:2204.12908v2 [cs.AI] for this version)
  https://doi.org/10.48550/arXiv.2204.12908
Related DOI: https://doi.org/10.1109/ETFA52439.2022.9921560

Submission history

From: Aljosha Köcher [view email]
[v1] Tue, 26 Apr 2022 17:15:25 UTC (583 KB)
[v2] Fri, 4 Nov 2022 08:01:31 UTC (587 KB)
Full-text links:

Access Paper:

  • View PDF
  • TeX Source
  • Other Formats
view license
Current browse context:
cs.AI
< prev   |   next >
new | recent | 2022-04
Change to browse by:
cs
cs.SY
eess
eess.SY

References & Citations

export BibTeX citation

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)