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Technology and Management Applied in Construction Engineering Projects II

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Civil Engineering".

Deadline for manuscript submissions: 18 December 2024 | Viewed by 919

Special Issue Editors


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Guest Editor
Construction Institute, CONSTRUCT/GEQUALTEC, Faculty of Engineering, Porto University, 4200-465 Porto, Portugal
Interests: project management; education 5.0; worker 4.0; digital twins; digitalisation; OpenBIM; data-driven start-ups; workforce build-up-skills; circular economy

E-Mail Website
Guest Editor
Construction Management Program, Faculty of Engineering Sciences, Ben-Gurion University of the Negev, POB 653, Beer-Sheva 84105, Israel
Interests: building information modeling; construction engineering and management; construction safety; facilities management; risk assessment and management in critical infrastructures; seismic risk analysis; fragility curves

Special Issue Information

Dear Colleagues,

The utilization of technologies is crucial in the efficient management of Construction Engineering Projects. Trends such as Digital Twins and Construction 4.0 and 5.0 have intensified the deployment of innovations across the whole life cycle of projects. However, management practices continue to represent the backbone of construction project deployment and performance. At the same time, novel means of construction are becoming more affordable and feasible, being based on robotization and 3D printing, for example. However, such engineering projects will demand labor-intensive endeavors. Data interoperability and process integration are essential in the provision of accurate information for decision-making. This scenario sets a primary challenge: the management of both people and data using technology that aims to provide a mutual benefit for enterprises and society. Human-centered benefits and environmental protection are non-negotiable principles in the future of industry. In this, human–data interaction is fundamental to the implementation of technology in construction engineering projects. Finally, research in the field of innovation for construction management should target solutions for all phases, from concept design, manufacturing/construction, and use to deconstruction. The scope of this Special Issue therefore includes, but is not limited to, the following topics:

  1. The use of Digital Twins in buildings, infrastructure or industrial projects;
  2. Three-dimensional printing: concepts and use cases;
  3. Blockchain for Smart Contracts;
  4. Lean construction using sensing technologies;
  5. AI-based management decision-making;
  6. Electronic Performance Monitoring (EPM);
  7. Circular Economy and Project Management;
  8. Data-driven projects, and the implementation of CDE (Common Data Environment), DBL (Digital Building Logbook), DPP (Digital Product Passport);
  9. Human–Data Interaction (HDI).

Dr. Diego Calvetti
Dr. Igal Shohet
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 100 words) can be sent to the Editorial Office for announcement on this website.

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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences 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 2400 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

  • project management
  • digitalization
  • decision-making
  • artificial intelligence
  • data-driven
  • human-centric
  • environment

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Published Papers (1 paper)

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Research

26 pages, 6837 KiB  
Article
Optimising Maintenance Planning and Integrity in Offshore Facilities Using Machine Learning and Design Science: A Predictive Approach
by Marina Polonia Rios, Rodrigo Goyannes Gusmão Caiado, Yiselis Rodríguez Vignon, Eduardo Thadeu Corseuil and Paulo Ivson Netto Santos
Appl. Sci. 2024, 14(23), 10902; https://doi.org/10.3390/app142310902 - 25 Nov 2024
Viewed by 556
Abstract
This research presents an innovative solution to optimise maintenance planning and integrity in offshore facilities, specifically regarding corrosion management. The study introduces a prototype for maintenance planning on offshore oil platforms, developed through the Design Science Research (DSR) methodology. Using a 3D CAD/CAE [...] Read more.
This research presents an innovative solution to optimise maintenance planning and integrity in offshore facilities, specifically regarding corrosion management. The study introduces a prototype for maintenance planning on offshore oil platforms, developed through the Design Science Research (DSR) methodology. Using a 3D CAD/CAE model, the prototype integrates machine learning models to predict corrosion progression, essential for effective maintenance strategies. Key components include damage assessment, regulatory compliance, asset criticality, and resource optimisation, collectively enabling precise and efficient anti-corrosion plans. Case studies on oil and gas platforms validate the practical application of this methodology, demonstrating reduced costs, lower risks associated with corrosion, and enhanced planning efficiency. Additionally, the research opens pathways for future advancements, such as integrating IoT technologies for real-time data collection and applying deep learning models to improve predictive accuracy. These potential extensions aim to evolve the system into a more adaptable and powerful tool for industrial maintenance, with applicability beyond offshore to other environments, including onshore facilities. Full article
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