IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v27y2016i1d10.1007_s10845-013-0862-7.html
   My bibliography  Save this article

Interoperability requirements for automated manufacturing systems in construction

Author

Listed:
  • Andrej Tibaut

    (University of Maribor)

  • Danijel Rebolj

    (University of Maribor)

  • Matjaž Nekrep Perc

    (University of Maribor)

Abstract

Multi-disciplinary software interoperability in the Architecture, Engineering, Construction and Operations industry is becoming a new and widely adopted business culture. Technical advances in interoperability architectures, frameworks, methods and standards during the last decade resulted in higher maturity of product and process models. Mature models, in effect, enable data exchange by an increasing number of software applications in the industry. This establishes trust in data exchange and results in the lower cost impact of inefficient interoperability. The negative cost impact increases with advancing life-cycle phase, from planning and design phase to construction phase and to operation and maintenance phase. Interoperability in the planning and design phase is most mature and well published, while interoperability in the construction phase and for automated manufacturing is less researched. This paper reviews state-of-the art automated manufacturing systems in construction and researches interoperability requirements for automated construction in context of the entire building lifecycle. Our research is based on experimental free-form clay building, designed with embedded simple HVAC components, and manufactured with additive layer technology. Conclusions provide valuable results for interoperability research and practice in construction projects with automated manufacturing systems in place.

Suggested Citation

  • Andrej Tibaut & Danijel Rebolj & Matjaž Nekrep Perc, 2016. "Interoperability requirements for automated manufacturing systems in construction," Journal of Intelligent Manufacturing, Springer, vol. 27(1), pages 251-262, February.
    • Handle: RePEc:spr:joinma:v:27:y:2016:i:1:d:10.1007_s10845-013-0862-7
    DOI: 10.1007/s10845-013-0862-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-013-0862-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10845-013-0862-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wurong Fu, 2021. "Macroscopic numerical model of reinforced concrete shear walls based on material properties," Journal of Intelligent Manufacturing, Springer, vol. 32(5), pages 1401-1410, June.
    2. Finn G. Feldmann, 2022. "Towards Lean Automation in Construction—Exploring Barriers to Implementing Automation in Prefabrication," Sustainability, MDPI, vol. 14(19), pages 1-22, October.
    3. Jiaxing Wang & Sibin Gao & Zhejun Tang & Dapeng Tan & Bin Cao & Jing Fan, 2023. "A context-aware recommendation system for improving manufacturing process modeling," Journal of Intelligent Manufacturing, Springer, vol. 34(3), pages 1347-1368, March.
    4. Robert Guamán Rivera & Rodrigo García Alvarado & Alejandro Martínez-Rocamora & Fernando Auat Cheein, 2020. "A Comprehensive Performance Evaluation of Different Mobile Manipulators Used as Displaceable 3D Printers of Building Elements for the Construction Industry," Sustainability, MDPI, vol. 12(11), pages 1-17, May.
    5. Madeleine Hoeft & Marianne Pieper & Kent Eriksson & Hans-Joachim Bargstädt, 2021. "Toward Life Cycle Sustainability in Infrastructure: The Role of Automation and Robotics in PPP Projects," Sustainability, MDPI, vol. 13(7), pages 1-23, March.
    6. Omid Davtalab & Ali Kazemian & Xiao Yuan & Behrokh Khoshnevis, 2022. "Automated inspection in robotic additive manufacturing using deep learning for layer deformation detection," Journal of Intelligent Manufacturing, Springer, vol. 33(3), pages 771-784, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:joinma:v:27:y:2016:i:1:d:10.1007_s10845-013-0862-7. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.