Special Issue "Applications of Engineering Digitalization and Construction IT for Energy Projects"
Deadline for manuscript submissions: 31 May 2020
Prof. Dr. Eul-Bum Lee
Pohang University of Science and Technology (POSTECH) / Graduate Institute of Ferrous Technology & Department of Industrial Management and Engineering, Korea
Website | E-Mail
Interests: building information modeling (3D-4D-5D-BIM); construction IT; smart-engineering and digitalization; engineering project management (schedule-cost integration and PMIS); contract and risk management, engineering economics and financial sustainability, infrastructure and heavy construction management
Prof. Dr. H. David Jeong
According to the EIA 2018 outlook, the energy demand is expected to grow by about 27%, or 3743 million tons oil equivalent (Mtoe), worldwide, from 2017 to 2040.
More specifically, the energy consumption of petroleum, natural gas, and coal use combined is forecast to grow 16% from 2017 to 2040. On the other hand, the oil and gas sector has reduced its investments as a result of the fall in oil prices over the last few years, but the sector has recently shown a slow but consistent growth in investment. The Korea Export–Import Bank (KEXIM) predicted the global construction market to increase by USD 10.1 billion to USD 511.6 billion by 2019. This is largely because of a projected increase of plant orders from the Middle East as a result of rising oil prices.
According to recent studies, a large number of engineering, procurement, and construction (EPC) contractors on megaprojects in the energy sector have suffered from massive profit losses. There are many causes that can be attributed to the losses, but one of the major causes that has been pointed out is a poor understanding about project complexity, which the project creates as a result of its large size, and subsequently poor project management planning and execution during pre-construction and construction. Another challenge that the industry faces is the fact that the construction sector has had a labor-productivity growth rate of 1% per year in the global market over the past two decades, compared with 2.8% for the total world economy and 3.6% for manufacturing.
The rapid development of digital technology in recent years will provide an opportunity to overcome these limitations of management. Those technologies include, but are not limited to, the following: (a) unmanned aerial vehicles for surveying, quality assessment, and project progress monitoring; (b) remote sensing methods such as light detection and ranging for effective surveying; (c) point cloud-based surveying data creation; (d) building information modeling (BIM)-based design and engineering; (e) various sensing technologies to improve job site safety; (f) artificial intelligence-based project risk detection; (g) automated schedule monitoring and progress evaluation based on digitalized planned schedule; (h) texting mining and natural language processing (NLP)-based project document review, evaluation and compliance checking; and (i) digitalized design and engineering data-based project work flow re-engineering.
This Special Issue will collect the state-of the art advancements in these areas that may have significant implications to the construction industry, especially for the energy sector and academia. Both technical papers and case studies are welcome for publication in this Special Issue.
Prof. Dr. Eul-Bum Lee
Prof. Dr. H. David Jeong
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 papers will be 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. Energies 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 1800 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.
- Energy sector projects such as oil and gas (onshore and offshore), power plants, industrial plants, and iron and steel plants
- Innovation in EPC project management and engineering management
- Big data platform and solutions applications
- Use of unmanned aerial vehicles
- Surveying innovations such as remote sensing methods, point cloud creation, and any digital and electronical conversion, and the recognition of image drawings and documents
- 3D-BIM, 4D-BIM, and 5D-BIM application
- Innovation in safety management
- Artificial intelligence (AI) and machine learning (ML) application
- Automated and non-automated integration of schedule and cost engineering (estimation and control)
- Text-mining and contextual analysis
- Natural language processing (NLP)
- Advanced work packaging (AWP) and BIM-based engineering collaboration
- Virtual reality (VR), augmented reality (AR), and mixed reality (MR) applications
- IoT implementation, senor data, and smart-tracking with RFID and QR codes, and bar codes
- Engineering cloud service
- Project management information systems
- Information technology or big data-based engineering, procurement, construction, and/or general process improvements