Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
skip to main content
10.1145/2968219.2971368acmconferencesArticle/Chapter ViewAbstractPublication PagesubicompConference Proceedingsconference-collections
demonstration

Automatic capturing and analysis of manual manufacturing processes with minimal setup effort

Published: 12 September 2016 Publication History

Abstract

The ongoing development of industrial manufacturing towards more individualization and smaller lot sizes opens up a new range of challenges. Not only do the processes in the factories need adaptation, but the workers need more support as well. We showcase a system that is able to address both aspects: an instrumentation of a manual workplace provides direct feedback for planning engineers, while at the same time acquiring data that is helpful for giving the worker feedback. Within this demo we focus on bi-manual picking and assembly processes observed by a lightweight optical recognition system enhanced by ultrasonic sensors, but also give an outlook on other possible modules.

References

[1]
Jake K. Aggarwal and Michael S. Ryoo. 2011. Human Activity Analysis: A Review. ACM Comput. Surv. 43, 3, Article 16 (April 2011), 43 pages.
[2]
Henning Kagermann, Johannes Helbig, Ariane Hellinger, and Wolfgang Wahlster. 2013. Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0: Securing the Future of German Manufacturing Industry; Final Report of the Industrie 4.0 Working Group. Forschungsunion.
[3]
Vladimir Pavlov, Sönke Knoch, and Matthieu Deru. 2015. CEPBoard: Collaborative Electronic Performance Board and Editor for Production Environments in Industry 4.0. In Proc. PerDis '15. ACM, 239--240.
[4]
Thomas Stiefmeier, Clemens Lombriser, Daniel Roggen, Holger Junker, Georg Ogris, and Gerhard Troester. 2006. Event-Based Activity Tracking in Work Environments. In Proc. IFAWC '06. 1--10.
[5]
Daniel Weinland, Remi Ronfard, and Edmond Boyer. 2011. A Survey of Vision-Based Methods for Action Representation, Segmentation and Recognition. Computer Vision and Image Understanding 115, 2 (Feb. 2011), 224--241.
[6]
Felix Wenk and Udo Frese. 2015. Posture from Motion. In Proc. IROS '15. IEEE.

Cited By

View all
  • (2019)Sensor-based Human–Process Interaction in Discrete ManufacturingJournal on Data Semantics10.1007/s13740-019-00109-z9:1(21-37)Online publication date: 13-Dec-2019
  • (2019)Enhancing Process Data in Manual Assembly WorkflowsBusiness Process Management Workshops10.1007/978-3-030-11641-5_21(269-280)Online publication date: 29-Jan-2019
  • (2018)Technology-Enhanced Process Elicitation of Worker Activities in ManufacturingBusiness Process Management Workshops10.1007/978-3-319-74030-0_20(273-284)Online publication date: 17-Jan-2018
  • Show More Cited By

Index Terms

  1. Automatic capturing and analysis of manual manufacturing processes with minimal setup effort

      Recommendations

      Comments

      Information & Contributors

      Information

      Published In

      cover image ACM Conferences
      UbiComp '16: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct
      September 2016
      1807 pages
      ISBN:9781450344623
      DOI:10.1145/2968219
      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Sponsors

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 12 September 2016

      Check for updates

      Author Tags

      1. ergonomics
      2. industrie 4.0
      3. manual assembly
      4. production planning
      5. timekeeping

      Qualifiers

      • Demonstration

      Conference

      UbiComp '16

      Acceptance Rates

      Overall Acceptance Rate 764 of 2,912 submissions, 26%

      Contributors

      Other Metrics

      Bibliometrics & Citations

      Bibliometrics

      Article Metrics

      • Downloads (Last 12 months)5
      • Downloads (Last 6 weeks)1
      Reflects downloads up to 11 Feb 2025

      Other Metrics

      Citations

      Cited By

      View all
      • (2019)Sensor-based Human–Process Interaction in Discrete ManufacturingJournal on Data Semantics10.1007/s13740-019-00109-z9:1(21-37)Online publication date: 13-Dec-2019
      • (2019)Enhancing Process Data in Manual Assembly WorkflowsBusiness Process Management Workshops10.1007/978-3-030-11641-5_21(269-280)Online publication date: 29-Jan-2019
      • (2018)Technology-Enhanced Process Elicitation of Worker Activities in ManufacturingBusiness Process Management Workshops10.1007/978-3-319-74030-0_20(273-284)Online publication date: 17-Jan-2018
      • (2017)Unconstrained Person Identification from Ceiling Using Multiview Learning for Tabletop UsersJournal of Information Processing10.2197/ipsjjip.25.88925(889-900)Online publication date: 2017
      • (2016)Identification from ceilingProceedings of the 15th International Conference on Mobile and Ubiquitous Multimedia10.1145/3012709.3012715(273-284)Online publication date: 12-Dec-2016

      View Options

      Login options

      View options

      PDF

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader

      Figures

      Tables

      Media

      Share

      Share

      Share this Publication link

      Share on social media