Advances in Construction Automation and Robotic Fabrication

A special issue of Buildings (ISSN 2075-5309). This special issue belongs to the section "Construction Management, and Computers & Digitization".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 705

Editors


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Guest Editor
School of Architecture, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea
Interests: construction automation; construction robotics; vision AI; automated construction

E-Mail Website
Guest Editor
Division of Architectural Engineering, Korea Cyber University, Seoul 03051, Republic of Korea
Interests: construction robotics; construction automation; robotic fabrication of building components

Special Issue Information

Dear Colleagues,

The construction industry is undergoing a critical transition driven by increasing project complexity, persistent productivity gaps, and the growing demand for data-informed decision-making. Traditional construction management approaches are no longer sufficient to address challenges such as fragmented workflows, limited real-time visibility, and inefficiencies across the project lifecycle. In this context, advances in computing and digitization are reshaping how projects are planned, executed, and managed.

This Special Issue Section, titled “Advances in Construction Automation and Robotic Fabrication,” aims to explore the integration of computational technologies with construction management practices. It focuses on how digital tools and data-driven methods can enhance coordination, improve productivity, and support informed decision-making throughout all project phases.

Topics of interest include, but are not limited to, the following:

  • Digital construction management and data-driven workflows;
  • BIM and digital twin integration for project lifecycle management;
  • AI and machine learning applications in construction planning and control;
  • Vision-based monitoring and automated progress tracking;
  • Data acquisition, processing, and visualization for construction sites;
  • Cloud-based collaboration platforms and real-time information systems;
  • Computational approaches to scheduling, risk management, and optimization.

We welcome contributions that advance the intersection of construction management and digital technologies.

Dr. Taehoon Kim
Prof. Dr. Minsu Cha
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Buildings is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • robotics
  • automation
  • digitalization
  • automated management
  • optimization

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Published Papers (1 paper)

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Research

16 pages, 756 KB  
Article
The Design of a Fireproofing Spray Robot Using Quality Function Deployment
by Kangmin Bae, Sebeen Yoon, Sangmin Lee, Minseung Cha, Hyunsoo Kim and Taehoon Kim
Buildings 2026, 16(10), 1890; https://doi.org/10.3390/buildings16101890 - 10 May 2026
Viewed by 425
Abstract
Fireproofing spray work at construction sites is still performed manually, making consistent spray quality difficult to maintain and exposing workers to dust and fall hazards during elevated work. This study applied Quality Function Deployment (QFD) to the design of a fireproofing spray robot [...] Read more.
Fireproofing spray work at construction sites is still performed manually, making consistent spray quality difficult to maintain and exposing workers to dust and fall hazards during elevated work. This study applied Quality Function Deployment (QFD) to the design of a fireproofing spray robot by translating field requirements into technical characteristics and identifying five major design conflicts: reach capability vs. stability, spray module flexibility vs. stability, sensor protection vs. sensing visibility, material supply reliability vs. stability, and material supply reliability vs. working range. Based on these conflicts, four designs were then proposed: sensor cover design, material supply continuity design, extended reach and stabilization design, and adaptive nozzle positioning design. A customer requirement-weighted evaluation showed that extended reach and stabilization design received the highest score because it most directly addressed accessibility to target surfaces at various heights, working range per setup, and stable operation at elevated positions. The other designs mainly addressed sensing reliability, material supply continuity, and nozzle adaptability to different member geometries and surface orientations. Accordingly, this study provides a QFD-based design for a fireproofing spray robot intended to address broader field requirements than previous systems developed for specific operating conditions. Full article
(This article belongs to the Special Issue Advances in Construction Automation and Robotic Fabrication)
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