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Human–Robot Collaboration and Lean Waste Elimination: Conceptual Analogies and Practical Synergies in Industrialized Construction

Author(s): ORCID
Medium: journal article
Language(s): English
Published in: Buildings, , n. 12, v. 12
Page(s): 2057
DOI: 10.3390/buildings12122057
Abstract:

The presence of robots in industrial environments is a well-established reality in Industry 4.0 and an absolute necessity in Industry 5.0, with human–robot collaboration (HRC) at the paradigm’s core. Concurrently, lean production remains one of the most influential production paradigms, which strives to eliminate Muda (non-value adding activities), Mura (unevenness), and Muri (people overburdening). However, what conceptual analogies and practical synergies are there between the lean production paradigm and HRC, and how do other Industry 4.0 technologies support this interaction? This research aims to answer this question in the context of industrialized construction, an ideal implementation field for both those approaches. The constructive research methodology is used to showcase, through evidence from the literature, that HRC aimed at the improvement of ergonomics, safety and efficiency has a positive contribution towards the elimination of all the lean wastes, while technologies like AR, VR, wearables, sensors, cloud computing, machine-learning techniques and simulation are crucially important for the intuitiveness of the collaboration between the human and the robotic partner. This is, to the author’s best knowledge, the first attempt to systematically record the commonalities between Lean and HRC, thus enhancing the very limited construction literature related to HRC.

Copyright: © 2022 by the authors; licensee MDPI, Basel, Switzerland.
License:

This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met.

  • About this
    data sheet
  • Reference-ID
    10700061
  • Published on:
    11/12/2022
  • Last updated on:
    10/05/2023
 
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