Steel Construction 4.0: Systematic Review of Digitalization and Automatization Maturity in Steel Construction

Abstract

Construction 4.0 is propelling the construction sector towards a digital, automated, and sustainable framework. This paper reviews advancements in automation and digitalization within the steel construction industry, framed by the principles of Construction 4.0. An analysis of the existing literature indicates that previous review studies have explored the technologies and concepts associated with Construction 4.0. However, none have consolidated these technologies and concepts (T&C) specifically within the context of the steel construction industry to evaluate their impact on steel manufacturing and assembly processes which was the main criterion for article selection. Therefore, this paper aims to consolidate various Construction 4.0 technologies and concepts to explore their integration into the steel construction industry. Based on data from the Web of Science and Scopus, a thorough screening process identified 56 out of 161 articles for analysis regarding their applicability to the steel construction industry. The evolution of various technologies in the steel construction industry has been examined over the years, starting with the initial references to each technology. In addition to discussing the advancements of these technologies and their influence on contemporary digitalization and automation within the steel sector, the authors seek to identify which T&C are most commonly utilized in manufacturing and assembly processes. The graphical results of this review indicate that each type of T&C can serve as a tool for quality control throughout the manufacturing and assembly processes. However, it is noteworthy that most research remains concentrated on enhancing material tracking and identification during these stages of production.

1. Introduction

Construction 4.0 represents a significant milestone in the architecture, engineering, and construction (AEC) industry. Although the initial reference to Construction 4.0 emerged in 2016 [1], its comprehensive implementation within the AEC industry has not yet been fully realized, preventing the achievement of its numerous potential benefits such as efficient information transfer, faster work execution, digital reality of building, smart cities, improved construction quality, etc. For Construction 4.0 to achieve its full potential in the AEC industry, it is necessary to review and define which technologies and concepts (T&C) make up Construction 4.0, and how they are integrated. In this review paper, technologies are defined as the technological achievements, devices, or drivers required for the realization of a concept, while concepts referred to a combination of these technologies. A clear example of this is the Internet of Things (IoT), which is a concept that exists through various technological integrations, including smart devices, various sensors, RFID (Radio-frequency identification) technology, and more. In summary, concepts require a variety of technologies for their realization, while technologies themselves can function independently. Technologies that are analyzed in this paper are: barcode, QR-code, RFID technology, and immersive technology, while analyzed concepts are: Building information modeling (BIM), Digital twin (DT), Internet of Things (IoT), Robotics and Deep Learning (RDL). With this division, the authors want to show the current state of achievements within the AEC industry and potential future research.

In addition to the potential of Construction 4.0 to enhance the AEC industry, it is important to focus on efficient construction. This encompasses the effective execution of work, the reasonable use of materials, the potential for building reconstruction (repurposing structural components), among other factors. Given these considerations, steel stands out as a particularly compelling choice of material. Steel construction involves large structural components such as columns, beams, trusses, plates and as a whole in constructions such as bridges, chimneys, transmission line towers, etc. Each of them must undergo three fundamental processes: (1) manufacture; (2) installation; (3) operation and maintenance. Within these processes, various sub-processes are involved, including design, material ordering, material preparation and cutting, assembly, welding, installation, maintenance, and quality control. Among these sub-processes, quality control (QC) is paramount to ensure that the final steel product meets the required standards. It is also vital to implement QC after each sub-process to maintain compliance with these standards. This highlights QC as the most frequent and critical sub-process necessary for the successful execution of the broader manufacturing, installation, and maintenance activities of the building. Given the regularity with which QC is performed, it is evident that this sub-process is time-intensive. Additionally, since QC in many production facilities and construction sites is typically conducted manually, the automation and digitalization of QC processes lag significantly behind those of other sub-processes. Thus, there is a pressing need to advance the digitalization and automation of quality control within the framework of Construction 4.0. With this context in mind, a strong emphasis will be placed on quality control, along with an exploration of the interconnections among various analyzed technologies and concepts related to it.

Through an analysis of published literature concerning Construction 4.0 [2,3,4,5,6] within the AEC industry, the authors determined that no existing article synthesizes the relevant T&C to illustrate their effects on the automatization and digitalization of the steel construction processes. Therefore, this paper aims to provide a comprehensive review of the literature, with an emphasis on these T&C and their application in steel manufacturing and installation. Such a review can facilitate an understanding of the current development regarding the discussed T&C and their integration. To accomplish this, the authors initially outline the uses of various T&C as reported in the reviewed articles and subsequently formulate three research questions based on this analysis.

• Q1—What are the advantages and limitations of using technologies and concepts related to Construction 4.0 for the manufacturing and installation of steel construction?
• Q2—What are the guidelines for future research and advancement of technologies and concepts related to Steel Construction 4.0?
• Q3—Which technologies and concepts are at the cutting edge of digitalization and automatization in the context of quality control in steel construction?

The remaining part of the paper is structured as follows: Section 2 outlines the methods employed in the study, while Section 3 presents the results obtained from the T&C review. In Section 4, the authors discuss the implications of the highlighted T&C findings, and finally, Section 5 concludes the study by addressing the research questions.

2. Materials and Methods

PRISMA-2020 (Preferred Reporting Items for Systematic reviews and Meta Analyses 2020) is used as the primary research method in this paper. Following PRISMA guidelines, a three-phase approach was adopted: (1) the data collection, (2) the inclusion and exclusion criteria, and (3) literature analysis. Figure 1 shows the complete flow of research paper selection through each phase.

2.1. First Phase—Data Collection

The planning phase began with article research based on the chosen variable and fixed keywords categorized according to the T&C being analyzed. For instance, to explore the implementation of RFID technology in the steel construction industry, the following keywords were utilized: RFID, Construction 4.0, steel structure, and steel construction. The terms “Construction 4.0”, “steel structure”, and “steel construction” serve as fixed keywords for each T&C, while the rest of the variable keywords are shown in

Table 1. Articles overview.

T&C	Variable Keywords
Barcode and QR code, RFID	Barcode, QR code, RFID
Immersive technology	AR, MR, VR, Immersive technology
Blockchain technology	BTC, Blockchain
BIM	BIM, 3D modeling, Steel detailing
Digital Twin	Digital twin
Internet of Things	IoT, sensors, monitoring
Robotics and Deep Learning	Robotics, Machine learning, Deep learning

. There were no restrictions on the publication dates of selected articles for this study since the aim is to show how the T&C have been developed over the years. There were no restrictions based on the type of steel construction. Still, it was important that one of the three main processes (manufacture, assembly, maintenance) were presented in searched articles.

2.2. The Second Phase—Inclusion and Exclusion Criteria

The second phase consists of screening the articles. The first step of the screening process was to exclude duplicated and review articles. The second step commenced with a detailed examination of the abstracts for each article. This filtering process removed articles that did not pertain to technological advancements in steel construction manufacturing, the assembly process, and construction site monitoring. For articles related to BIM and immersive technologies, the database for this category was expanded to include those that applied these technologies in the design and management of steel construction projects.

Table 2. Articles database—overview.

T&C	N1	N2	N3
Barcode and QR code, RFID	31	28	13
Immersive technology	42	42	13
Blockchain technology	16	11	4
BIM	33	31	12
Digital Twin	11	8	3
Internet of Things	17	8	5
Robotics and Deep Learning	11	7	6

presents the number of relevant articles alongside the total number of articles searched in both phases, after which we proceeded with the analysis of the research articles.

2.3. The Third Phase—Literature Analysis

The third phase began with bibliometric analysis conducted using bibliometrix [7]. The report of the bibliometrix analysis is illustrated in Figure 2. Subsequently, the articles were organized chronologically according to the T&C to provide a clearer understanding of their evolution over the years. This method of organizing the articles provides clarity on the initial challenges faced by researchers. Ultimately, this analysis offers specific insights into the current state of these T&C. Furthermore, each T&C group is described in this article in terms of steel construction processes and sub-processes that have been implemented. Finally, a summary of each article is presented in table format at the end of each sub-section in the results, which includes five key elements: year, author, utilized T&C, the processes and sub-processes in which these T&C are applied, and the technologies that influence on quality control referred as “QC 4.0”.

3. Results

The following chapter will provide an overview of the articles, categorized by technologies and concepts. Each subsection will include a brief theoretical background, followed by an analysis of the development of these T&Cs as they have been implemented in the AEC industry.

3.1. Building Information Model (BIM)

Building information modeling (BIM) is the holistic process of creating and managing information for a built asset. Based on an intelligent model and enabled by a cloud platform, BIM integrates structured, multi-disciplinary data to produce a digital representation of an asset across its lifecycle, from planning and design to construction and operations [8]. The implementation of the BIM concept is crucial for advancing Construction 4.0 within the AEC industry, particularly in the context of steel construction processes, which increasingly rely on smart machines, automatization, and digitalization.

The initial emphasis of BIM in the steel construction process primarily relates to design. According to Li et al. [9], the implementation of BIM software—Tekla structures has a significant impact on the modeling and design of steel construction. The benefits of utilizing BIM are clear, featuring advantages such as collision detection, check of bolt spacing, and automatic generation of 2D drawings derived from a 3D model, and more. A strong example of utilizing BIM for design is presented by Avendano and Zlatanova [10], where a comparison is made between traditional design methods and BIM-based design in terms of the necessary time involved. The traditional design relies on 2D drawings produced in AutoCAD 2019, while the Tekla Structures 2022 is utilized as BIM software. The comparison focuses on three key processes: planning, designing, and manufacturing. In terms of planning, using BIM has resulted in a time savings of 60 h compared to traditional design methods. This is primarily due to the ability of BIM to visualize a 3D model, which reduces the amount of time spent in meetings to interpret 2D drawings, which is an important factor for clients who have less experience with reading technical drawings. During the design stage, significant time savings are achieved through the use of BIM. In the case of traditional design, creating workshop drawings took 450 h, while utilizing BIM required only 65 h. The final comparison focuses on production efficiency. Manufacturing that employs BIM concepts spends 9.9 h per ton, compared to the 12.5 h per ton needed by manufacturing using traditional design methods. This study highlights the advantages of implementing BIM, demonstrating its benefits not only in the design phase but also throughout the planning and manufacturing processes. Another approach to utilizing BIM in the design process is described by Laefer et al. [11]. Their article integrates terrestrial laser scanning (TLS) technology with the BIM concept. This integration aims to address the challenges of time constraints and insufficient documentation when creating a 3D model of existing steel construction. The proposed integration automatically identifies cross-sections from TLS point cloud data using kernel density estimation and generates those cross-sections in a BIM-compatible format. The success rates for identifying cross-sections and structural members were 92% and 81%, respectively. However, despite the high accuracy rates, data acquisition and registration errors were one of the problems. To address these issues, the implementation of intelligent procedures is suggested as a future guideline. Additionally, another integration of TLS and BIM is discussed by Yang et al. [12], who employs an algorithm based on principal component analysis and cross-section fitting techniques. This integration was validated through geometry extraction of steel bridge components, successfully extracting and automatically generating BIM data for 39 out of 41 members, resulting in a success rate of 95%. Concerning the promising results, there is potential to extend the developed technique to accommodate L-shaped and T-shaped profiles. While those two articles discuss modeling existing steel construction, Pereiro et al. [13] focus on reusing steel members by applying reconfigurable joints (clamp-based connection). The clamped connections allow for the assembling of the steel profiles without previous drilling or welding. This approach seeks to lower CO₂ emissions while obtaining economic savings. Although only cutting and anti-corrosion protection are required in manufacturing, the initial costs of these joints are higher than weld joints. In this article, BIM is utilized to analyze economic profitability over time for reconfigurable joints compared to welded joints. Experiments conducted on construction projects demonstrate that while the upfront costs of reconfigurable joints exceed that of welded joints, the financial, energy, and carbon footprint savings become more advantageous after several reuses. Despite the positive findings, it is essential to analyze a broader range of case studies, including real-world applications, as future work. Similarly, Basta et al. [14] present a framework for the estimation of SS-DAS (steel structure deconstructability assessment scoring) index. Calculation of SS-DAS is achieved with the integration of BIM and Dynamo applications. The proposed index evaluates seven distinct joint types, identifying the most suitable solutions for construction regarding deconstructability. The joint with the highest SS-DAS value is deemed the most appropriate for element connections in the project. Moreover, Galić et al. [15] analyze a practical example of employing BIM for deconstruction planning. In this article, BIM is utilized to simulate the entire process, providing visual feedback and cost estimations for each sub-process throughout the deconstruction. Additionally, leveraging BIM can improve the management of delays. Wang and Lu [16] further explore the application of BIM in design processes. Their article presents a BIM platform specifically designed for single-story steel structures, incorporating REVIT for modeling, SQL Server 2019 for data exchange, and SAP2000 v23 for structural analysis. This platform aims to minimize data loss during software transitions, significantly reducing the time required for both BIM and structural analysis while maintaining a high level of accuracy. However, its exclusive integration with SAP2000 poses a limitation, as it lacks compatibility with another finite element software. Beyond design processes, BIM integration also plays a critical role in quality control. Zhou et al. [17] propose an innovative method of virtual preassembly for large steel structures that utilize BIM, the PLP (Plane-Line-Point) algorithm, and 3D measurement techniques. This approach seeks to reduce the costs and time associated with current preassembly methods. The core principle of this method involves comparing the actual dimensions of elements, measured by a total station, with the coordinates of the BIM model. Findings indicate that this method can substantially lower operating costs, particularly for welders, by enabling the prediction and correction of manufacturing errors. Additionally, Wang et al. [18] present a framework that implements the virtual trial assembly (VTA) of a steel structure utilizing a BIM platform (Revit). In line with the previous article, the proposed VTA relies on the comparison between theoretical and real coordinates, implemented through a VTA program developed in Revit Dynamo. This approach facilitates the identification and rectification of manufacturing errors before the elements are dispatched to construction sites. While the implementation of this framework has proven successful, the authors caution that the accuracy of measurement data is influenced by the workshop environment, as steel is sensitive to temperature changes, which can impact VTA results. Additionally, the paper references a quality control process during the lifecycle of building usage, as outlined by Ying Xia [19]. It focuses on the monitoring of deformation in steel structures, achieved through sensor technology. The collected data on deformation is incorporated into the BIM, e.g., a BIM-based monitoring system. A comparative analysis revealed that the deformation-displacement curve derived from the BIM-based system more accurately reflected the actual values when compared to those obtained through a back-propagation (BP) neural network. In relation to assembly processes, Liao et al. [20] highlight the advantages of employing BIM in the installation of steel structures. On construction sites, BIM can be effectively utilized for: (1) material tracking via the integration of RFID technology, (2) construction management, (3) space management, and (4) business calculations. Their findings suggest that the implementation of BIM can significantly enhance operational efficiency, which ultimately leads to cost reductions. The integration of BIM into management is further explored in the work of Pote [21], which discusses how BIM aids in project planning and scheduling. The notable benefits of utilizing BIM in project management encompass improved onsite collaboration and communication, enhanced visualization of projects, and more effective scheduling, among various others.

Table 3. BIM concept—summary of process, sub-processes, and quality control.

Year	Author	T&C	Process and Sub-Process	QC
2012	[20]	BIM	Assembling	-
2015	[15]	BIM	Deconstruction	-
2016	[9]	BIM	Design	-
2017	[11]	BIM + laser scan	Design	-
2019	[17]	BIM	QC	Data analysis; VTA
2020	[19]	BIM	QC	Sensors
2020	[12]	BIM + laser scan	Design; QC	Point Cloud data
2020	[14]	BIM	Design	-
2022	[18]	BIM	Assembling; QC	Data analysis; VTS
2022	[21]	BIM	Management	-
2023	[13]	BIM	Design	-
2023	[10]	BIM	Design	-
2024	[16]	BIM	Design	-

summarizes previous mention articles in regard to the BIM concept. It describes each article and corresponding processes and sub-processes in which BIM has been integrated. Furthermore, the use of BIM concepts related to quality control (QC) is also indicated in the table.

3.2. Barcodes, QR Codes, and RFID Technology

Barcodes, QR codes, and RFID technology are relatively older technologies, especially when it comes to the barcode that has been used since the early 1960s. A QR code is a two-dimensional barcode designed to facilitate the rapid storage and retrieval of data through the use of light waves. In contrast, RFID technology consists of tags (passive or active), a reader, and an antenna. In contrast to the light waves, the RFID operates on the principle of radio frequency to transmit information. This subsequent section will describe the advancement of these technologies within the AEC industry, alongside a discussion of their principal differences.

Material tracking and labeling were among the initial sub-processes in which advanced technologies were implemented, with barcodes prevailing due to their early appearance. The QR code was developed in the 1990s, while the implementation of RFID began in the early 2000s. The initial implementation of barcode technology within the AEC industry was established in 1989 by Lundber and Beliveau [22] who created the Automated Lay-Down Yard Control (ALYC) system. This system integrates barcode with Computer-Aided Design (CAD) to facilitate comprehensive inventory identification and tracking on construction sites, ultimately leading to a possible reduction in the cost of construction projects through improved management of materials and equipment. Implementation of QR codes into the material tracking and identification is, furthermore, elaborated in the work of Riueran [23], which presents an efficient and cost-effective solution for raw material identification. An initial database of various types of carbon steel was developed, and post-cutting, each raw material was labeled with corresponding QR codes. This system provides real-time tracking of the location of raw materials, significantly enhancing the speed of locating materials within manufacturing halls and storage. Moreover, Chen et al. [24] have integrated QR codes with BIM to establish a web-based platform for the management and visualization of manufacturing processes. This platform facilitates real-time tracking of steel construction production. Its web-based nature allows all authorized participants to access and monitor the status of ongoing projects. Alongside the tracking of production, QR codes are utilized for labeling the individual elements, and scanning these codes directs users to a website where quality control information can be recorded. Consequently, it is feasible to retrieve product information at any time during and after the installation. Another integration of QR codes and BIM for enhanced tracking is presented by Jung et al. [25]. Their study utilizes QR codes for material tracking, complemented by BIM for 3D and 4D visualization to enhance the management purpose. Upon scanning a QR code, a website is accessed for users to enter relevant information regarding the status of installed elements. The color of corresponding elements in the BIM model varies based on the recorded status. Additional integration for real-time tracking is presented in Tsern et al. [26]. They present a system known as M-ConSCM (Mobile Construction Supply Chain Management) aimed at enhancing information collection from construction sites. This system utilizes QR codes and integrates a web-based platform along with a PDA (Portal Digital Assistant) for scanning. The PDA scans the QR codes to collect relevant information, which is subsequently stored in a database. This seamless transfer of data from the PDA to the database facilitates real-time tracking of materials. Furthermore, Cheng and Chen [27] have demonstrated an example of integrating barcode technology in assembly and control processes through their development of the ArcSched system. This system is designed to track the installation processes of steel elements, providing a visual representation of installation progress. As a result, it reduces the need for project managers to visit construction sites to verify completed installations. Besides material tracking, an example of the integration of QR codes and safety management is presented by Kim et al. [28]. They introduce the method known as “You Only Look Once” (YOLO-V3), which focuses on worker monitoring through image processing obtained from a construction site. This method utilizes a video camera and QR codes printed on workers’ safety shirts. By scanning the QR code alongside the captured image, the coordinates of the workers can be determined, enabling effective monitoring of their safety. Similarly to this article, the QR code is implemented in personal management [29]. In this article, the use of QR codes is for workers’ applications. The QR code is attached to the safety helmet of each worker, from which, after scanning the QR code, the necessary information about the worker during the inspection is shown.

The initial reference to RFID technology was made by Jaselskis [30], who implemented passive RFID tags for material identification and quantification. In summary, the use of RFID resulted in a 30% reduction in the time required for manual identification. Additionally, Wang [31] integrated RFID technology with a PDA device and developed a web-based platform aimed at quality control for elements delivered to construction sites. This integration demonstrated increased efficiency in information transmission in regard to the control quality and provided real-time tracking. A similar integration of RFID technology and PDA device is presented in the work of Yin et al. [32]. A notable finding from his investigation was the time recorded using this technology compared to manual inspection. The use of RFID technology took 0.57 min per inspected element, in contrast to 11.01 min required for manual inspection, which indicates a significant advantage of these technologies in the AEC industry. An early implementation of RFID in conjunction with BIM is described by Chin et al. [33], who developed an RFID + 4D PMS system. The objective of this system was to track assembly and manufacturing processes. By utilizing BIM, the visualization of installed elements was achieved, with color changes indicating each assembled component installation. Furthermore, Kasim [34] presents another integration of RFID technology in tracking processes through the Intelligent Material Tracking System (I-MATRACS). Unlike the approach taken by Jaselskis [30], this study employed active RFID tags, which automatically recorded information captured by the RFID reader and transmitted that data directly to a database.

Table 4. Barcode, QR code, and RFID—summary of processes and quality control.

Year	Author	T&C	Process and Sub-Process	QC
1989	[22]	Barcode	Material ID and tracking	-
2002	[27]	Barcode + RF + GIS	Material ID and monitoring	Automatization; data analysis
2003	[30]	RFID	Material ID and tracking
2005	[26]	Barcode	Material tracking	Data analysis
2008	[31]	RFID	QC	Data analysis
2008	[33]	RFID + BIM	Material tracking	-
2009	[32]	RFID	Material ID	-
2014	[29]	QR code + BIM	Management	Data analysis
2015	[34]	RFID	Material ID	-
2019	[23]	QR code	Material ID	-
2020	[24]	QR code + BIM	Material ID	Data analysis
2020	[25]	QR code + BIM	Material ID	-
2021	[28]	QR code + image processing	Safety management	-

summarizes the aforementioned articles concerning the applications of barcode, QR code, and RFID technology. It outlines each article along with the associated processes and sub-processes in which these technologies are implemented. It is important to note that the integration of these technologies is also applied in other concepts, such as the IoT and DT, which will be discussed further in subsequent sections.

3.3. Immersive Technology

Virtual reality (VR), augmented reality (AR), and mixed reality (MR) are not new technologies to the industry because their origins date back to the 1990s. However, they have recently garnered significant attention within the AEC industry. One of the primary reasons for their adoption is that these technologies provide a detailed visualization of buildings as they will appear after construction. This helps investors’ better understanding of 2D drawings and makes quicker decisions. VR is a technology that creates computer-generated environments, allowing users to feel a sense of presence within these virtual spaces. In contrast, AR technology overlays digital objects or information onto the real environment at precise spatial locations and in real time. The latest immersive technology, known as MR, combines elements of both AR and VR, creating a hybrid environment that allows interaction between the real and virtual worlds. The remainder of this subsection will explore the advantages and challenges that the AEC industry has faced regarding immersive technologies since 2000.

Immersive technology is frequently referenced within various processes and sub-processes, of steel construction, with project planning and design being the most prominent applications. Waly and Thabet [35] developed a prototype known as the Virtual Construction Environment (VCE) aimed at enhancing project visualization and comprehension. Parallel to this, Robert Lipman [36] introduced a virtual reality display for steel construction, where initial steel elements are recorded in CIMSteel Integration Standards (CIS/2) format. This article draws parallels with Building Information Modeling (BIM), particularly in the adoption of the “family” concept. In regard to this developed prototype, identification of potential clashes can be detected in an early stage of the project. Additionally, the integration of AR technology into project design is explored in preliminary research by Cote and Beauvais [37]. Their study employs a combination of tablet computer and head-mounted systems to display 3D positioning of elements from 2D drawings. This initiative addresses the challenge of accurately understanding the 3D locations of specific elements in traditional 2D representations. Although this implementation aids project clarity, certain limitations remain, such as restricted rendering speed and the necessity for improved perception through additional environmental elements. Furthermore, Prabhakaran [38] presents another approach to visualize 3D elements derived from 2D drawings by integrating MR with BIM in the design process. The Microsoft HoloLens, a wearable holographic computer equipped with advanced sensors capable of mapping the physical environment, serves as the hardware for projecting these elements. The visualization of models utilizing MR technology enables designers to gain a clearer understanding of client requirements throughout the project. Consequently, the application of MR ultimately leads to decreased time and cost expenditures. Further implementation of MR into the BIM is presented by Woodward and Hakkarainen [39]. One of the primary challenges addressed in this article is the implementation of complex models within mobile applications through a client-server solution. The authors develop a mobile application designed to visualize models from BIM, integrating them with scheduling information and precisely aligning them with geographic locations.

After implementing immersive technology into the design sub-processes, the next step is to incorporate it into quality control processes. Do Hyoung Shin et al. [40] developed the ARCam application, which utilizes AR technology. The purpose of this application is to compare the accuracy of AR technology with that of a total station. The experiment assesses the measuring accuracy of installed steel columns concerning project positioning. The results indicated that while AR is less precise than the total station, it still meets standard tolerances. Another finding highlighted the significantly faster setup of AR devices compared to the total station. Two additional articles related to the quality control process are presented by Park et al. [41,42]. These articles introduce a defect management application (DM-AR). Although the focus is primarily on reinforced concrete structures, clear parallels can be drawn to steel construction. The articles detailed the integration of AR markers, image-matching techniques, and BIM for the automatic detection of dimensional errors. While this integration can enhance the current manual defect management processes, certain limitations must be addressed, such as the time-consuming setup of AR markers on the job site and the need to capture real images from specific angles for effective image processing. The next integration of AR technology and BIM is presented by Mirshokraei et al. [43], wherein a quality management system is developed for the installation phase. In addition to this integration, a predefined web-based checklist has been established to address challenges associated with manual data collection and data entry errors. The outcomes of the experiments indicated potential improvements in quality, cost optimization, and delay reduction. Furthermore, Um et al. [44] developed a low-cost mobile AR platform that is integrated with BIM, designed to facilitate inspection support, workflow management, and data reduction in building maintenance. The developed platform enhances data transfer between construction sites and offices, enabling site operators to make prompt decisions regarding maintenance tasks. Further implementations of immersive technology within other sub-processes of steel construction are documented in studies [39,45,46] wherein these technologies are employed in the processes of installation and construction site organization. Blum [46] integrates mixed reality (MR) technologies, utilizing devices such as HoloLens, to exhibit the installation processes of steel elements. This implementation highlights each step in the assembly of column-beam joints, correlating them with the corresponding drawings. This approach provides users with all necessary information, including dimensions, material properties, positioning, and the names of corresponding elements, pertaining to the installation process without the need for model reviews or printed drawings. Nainggolan et al. [45] employ virtual reality (VR) to simulate worker education, particularly in operating cranes. This implementation addresses the needs arising from the presence of less experienced workers and aims to reduce accident rates. Within this developed virtual reality environment, users can simulate crane movements and operations. This integration has the potential to enhance worker experience significantly; however, due to the complexity of construction sites, ongoing development is required to ensure the simulation closely resembles real-world conditions. In conclusion, Gheisari et al. [47] have developed a semi-augmented reality system known as Panorama, which is integrated with BIM. Panorama aims to tackle one of the primary challenges encountered when utilizing AR, specifically the registration of virtual information to the correct position in the real world. This system offers a semi-augmented reality experience, substantially improving registration accuracy and creating highly realistic and detailed representations of the environment. Nevertheless, despite overcoming registration issues, the limitation of Panorama remains its reliance on offline panoramic images or videos, which cannot be updated in real time Cote et al. [37].

Table 5. Immersive technology—summary of processes and quality control.

Year	Author	T&C	Process and Sub-Process	QC
2003	[35]	VR	Management	-
2003	[36]	VR + CIS/2	Management	-
2009	[40]	AR	QC	Digitalization
2011	[39]	BIM + AR	Management	-
2013	[41]	AR + BIM	QC	Digitalization
2014	[37]	AR + BIM	Management	-
2016	[47]	Panorama + BIM = Semi AR	Management	-
2019	[43]	AR + BIM	QC	Digitalization
2020	[38]	MR + BIM	Design	-
2020	[45]	VR	Assembling	-
2023	[44]	AR + BIM	QC	Data analysis, Digitalization
2023	[46]	MR + BIM	Assembling	-

provides a comprehensive summary of the examined articles concerning immersive technologies and their implementation into the quality control process. In addition to detailing these processes, the table also delineates the types of technologies utilized in conjunction with immersive technology integration.

3.4. Internet of Things (IoT)

The term “Internet of Things” (IoT) was first introduced at the Massachusetts Institute of Technology in 1999. Although this concept has been present in the construction industry for some time, it has gained significant attention only in recent years. According to [48], IoT can be defined as “the interconnection of sensors and actuators that facilitates the exchange of information through platforms.” The technologies that enable IoT encompass a range of components, including sensors, identification systems, communication methods, algorithmic and software solutions, cloud platforms, data processing capabilities, energy storage, and security mechanisms, among others [49]. This concept integrates various technologies, and below, it will be explored how IoT is applied within steel construction and the production process itself.

Zhong and Peng [50] introduce a multi-dimensional BIM platform with IoT, enabling real-time visibility and traceability of manufacture through RFID technology for data collection. This platform provides contractors with immediate access to all information regarding the assembly process. Digitalizing all manual processes significantly enhances logistics and reduces paperwork by 40% and 48.3%, respectively. Similarly, Li et al. [51] present another integration of IoT with BIM concepts, having developed an IoT-enabled platform for real-time data collection, progress monitoring, supervision, quality control, visibility, traceability, and error alerts. Quality management is facilitated by equipping construction elements with RFID tags, allowing for the sharing of vital information such as delivery arrivals and assembly delays between contractors and clients. Despite the numerous benefits offered by this platform, it has only been tested on one practical project, indicating the need for further implementation across additional projects to conduct a more comprehensive analysis and draw conclusions regarding its effectiveness. More detailed quality control is presented by Liu et al. [52]. Their article proposes a health monitoring system for steel construction that tracks various parameters, including stress, cable forces, temperature, and deformations. Monitoring these factors enables a real-time assessment of the construction’s health. Additionally, the authors have developed an automatic evaluation system that assesses the structure’s condition based on data collected from different types of sensors. This implementation enhances safety and improves steel construction’s operational and management standards. Another utilization of IoT for digitalization and automation of the steel construction process is demonstrated by Dai et al. [53]. In their paper, IoT is integrated with MQTT (Message Queuing Telemetry Transport), a protocol for information sharing between machines. This implementation addresses the increasing the demand for automation in manufacturing. The article details the use of IoT in the material-cutting process with plasma. The operational flow of the developed protocol includes transporting the material to the plasma, cutting it, welding it, and comprehensive monitoring. Notably, after each action, an automatic message is sent to the next operator, signaling that the previous task has been completed and the next can commence. This approach has effectively facilitated digitization within the manufacturing process through enhanced communication between machines. In the article by Abrishami [54], the integration of IoT and BIM concepts, along with blockchain and RFID technology, is explored within the context of supply chain management. This approach aims to enhance the optimization, efficiency, and transparency of supply chain processes, thereby facilitating decision-making based on real-time data. The developed model enables continuous monitoring of all operations and transactions, which are meticulously documented regardless of time, ensuring that all participants have access to accurate information. Additionally, the implementation of blockchain technology within this model ensures that devices are encrypted, thereby enhancing security during communication.

Table 6. Internet of Things—summary of processes and quality control.

Year	Author	T&C	Process and Sub-Process	QC
2017	[50]	IoT + BIM + RFID	Material tracking	-
2018	[51]	IoT + BIM + RFID	Material tracking	Automatization
2020	[52]	IoT	QC, monitoring	Sensors, Data analysis
2020	[53]	IoT + MQTT	Production, QC	Automatization
2024	[54]	IoT + BIM + BCT + RFID	Material tracking

summarizes the IoT concept and its implementation in manufacturing and assembling processes, highlighting the impact on quality control within the context of Construction 4.0.

3.5. Blockchain Technology

While the term “blockchain” is often linked to cryptocurrencies and finance, it also has the potential to enhance the AEC industry. In construction, blockchain is primarily utilized for management purposes, including transactions, smart contracts, and material tracking, among other applications. The following overview will discuss the implementation of blockchain technology related to steel constructions.

Ye Sun et al. [55] propose the implementation of blockchain technology for the purpose of tracking information related to projects. The authors identify the motivation for employing this technology as stemming from slow and inefficient management, isolated information systems, and challenges in tracking various elements. They conceptualize each company involved in a project as a “node” within the blockchain. To facilitate the unification of operations across companies, data is updated in the blockchain through a process of data mapping. The authors conducted tests that involved large volumes of transactions to assess the stability of blockchain technology in meeting the substantial informational demands of the construction industry. A similar application of blockchain technology is discussed by Data and Bhattacharje [56], where they developed the SteelChain system for tracking orders from the initial processing of steel from iron ore. The necessity for this system is underscored by the fact that customers often lack visibility regarding the status of their orders from the moment they are placed until the items physically reach the production facility. Moreover, Basher et al. [57] present another example of material and inventory tracking based on blockchain technology. Their research focuses on how blockchain can address issues such as material delays, legal disputes within the supply chain, high material costs, and storage space limitations. The authors propose a system that allows all project participants to exchange information in real time, thus potentially enhancing productivity and expediting information sharing. Another innovative solution, presented by the authors to reduce the significant number of repetitive orders and the automatic imposition of penalty charges, is the use of “smart contracts.” Beyond just material and order tracking, Da Sheng et al. [58] have integrated blockchain technology into the quality control process. They developed the Product Organization Process (POP) Quality Chain, which facilitates the automatic generation of information regarding non-conformance reports (NCR) during the installation of steel construction. Within this application, information about NCRs can be updated in real time at construction sites. The utilization of blockchain technology ensures that this information is secure and immutable, thereby preventing contractors from altering data to absolve themselves when an NCR arises.

Table 7. Blockchain—summary of processes and quality control.

Year	Author	T&C	Process and Sub-Process	QC
2020	[55]	Blockchain	Material tracking
2021	[56]	Blockchain	Material tracking	Automatization
2020	[58]	Blockchain	QC	Data analysis
2024	[57]	Blockchain	Management

summarizes the aforementioned articles related to blockchain and their distribution in terms of processes and sub-processes within the production facility and quality control.

3.6. Robotics and Deep Learning

In this section, several papers will be presented on the topic of the application of robotics and the deep learning concept within the production plant, but also in the assembly of steel constructions.

The implementation of robotics in the assembly process is discussed in two articles: Jung et al. [59] and its continuation in Chu et al. [60]. These works aim to address challenges such as a shortage of experienced workers, workplace safety, and the time required for assembly processes. The robotic mechanism introduced is specifically designed for the assembly of bolts on beams, following a two-step procedure. In the first step, the bolts are assembled with a low torque moment, while the second step involves full bolt tightening. Once the tightening is complete, the robotic mechanism moves on to the next joint to repeat the process. Throughout this operation, the worker remains safe in a control cabin. To gain insight into the effectiveness of this mechanism, an experiment was conducted to compare manual labor with robotic operations. The results demonstrated that the robotic mechanism was able to save 14% of the time compared to human work. With this principle in mind, the robotic mechanism has the potential to replace human labor in situations that involve risky environments or hard-to-reach areas. The next example of digitalization in steel construction is presented in the paper by Kim et al. [61]. In this article, deep learning is employed for damage detection in steel frames as part of the quality control process. The developed concept, known as Deep Convolutional Neural Network Damage Location (DCNN-DL), is compared to similar models such as MobileNet and ResNet. The DCNN-DL approach addresses the challenges associated with visual inspection, which can be time-consuming, and it has been designed to visualize the location of deflection using Grad-CAM (Gradient-weighted Class Activation Mapping). A comprehensive analysis comparing these concepts revealed that the DCNN-DL method delivers the highest accuracy when compared to MobileNet and ResNet.

Another example of implementing the deep learning concept into the quality process is presented by Chen et al. [62]. In their article, deep learning is used to create a mobile application known as YOLO-V4, which is designed for element counting based on images. For instance, when a group of steel elements or reinforcements arrives at a storage or construction site, a worker can take the image and upload it to the mobile application. As a result, the application will automatically count the number of elements with an accuracy above 90% based on the carried-out tests. Notably, the accuracy is influenced by the number of elements in the group; smaller groups yield better accuracy. Additionally, the work presented by Lee et al. [63] utilizes point cloud segmentation to develop an automated inspection system that recognizes the dimensional and geometrical properties of tested steel frames by utilizing BIM and MR for synthetic data generation. Experimental results evaluating the efficacy of synthetic data derived from BIM models, in conjunction with actual as-built MR capture data, yielded an accuracy of 86.15%. This finding indicates the potential of using deep learning techniques with a relatively low cost of data acquisition in the construction monitoring process. Another BIM implementation into the quality process is presented in Pablo Martinez et al. [64]. In this article, BIM is integrated with the deep learning concept for automatic supervision of light-gauge steel frames. The proposed integration utilizes a vision-based approach to analyze information collected from the 2D images. Key information, including element positions, metrics, and intersection points, is extracted from these images and compared with the corresponding BIM model. The decision-making module developed as part of this process possesses the capability to identify discrepancies and issue a warning. This integration facilitates the automation of the quality process, particularly in the identification of errors, which is a fundamental aspect of quality control in the context of Construction 4.0.

Table 8. Robotics and deep learning—summary of processes and quality control.

Year	Author	T&C	Process and Sub-Process	QC
2013	[59,60]	Robotics	Assembling
2019	[64]	BIM + deep learning	QC	Automatization; Vision-based module
2021	[61]	Deep learning	QC	Automatization; Data analysis
2024	[62]	Deep learning	QC; material ID	Automatization
2024	[63]	BIM, point cloud, MR	QC	Point Cloud Data; Automatization

summarizes the articles related to robotics and deep learning and their distribution in terms of processes and sub-processes within the production plant, assembly, and quality control of steel constructions.

3.7. Digital Twin

The concept of a Digital Twin (DT) encompasses the integration of technologies associated with Construction 4.0 and constitutes a set of virtual information designed to fully describe a potentially or actually physically produced product [65]. The idea was first introduced in 2002 at the University of Michigan under the term Product Lifecycle Management (PLM) [65]. By 2005, the PLM concept evolved and was rebranded as the Information Mirroring Model. It was not until 2011 that the term Digital Twin emerged in a published work [66], originally stemming from the field of aeronautics. The main characteristic of the DT concept is real-time reflection, and in addition, DT enables up-to-date information about the physical space to be reflected in the virtual space with high precision and synchronization [67]. To prevent confusion across various articles, any discussion related to the implementation of DT—regardless of the associated technology—will be organized within this subchapter rather than the preceding sections. The following content will provide a concise overview of this concept and its application in the management of steel constructions.

Kosse et al. [68] present a theoretical approach in their article that integrates a computer-vision tracking system for locating construction equipment on sites. This tracking system consists of a stereo vision camera, a real-time capable detector, and an asset administrator shell (AAS) as the platform for the DT. The data collected through this digital recording makes it possible to enhance control and coordination of work processes. Furthermore, the authors emphasize the cost-effectiveness of this approach compared to laser sensors or wireless sensors. Additionally, Liu et al. [69] introduce a digital twin-based quality control method for monitoring bolt torque. Using the data gathered by the digital twin, the Markov method can make predictions regarding bolt torque. This method demonstrates an accuracy rate of 80%, validating the precision of the Markov method and showcasing the viability of a DT construction quality control approach. Liu and Lin [70] discuss the implementation of digital twins in manufacturing and assembly processes. They outline three phases essential for establishing a digital twin: (1) the collection and transmission of physical data; (2) the creation of a virtual model of the digital twin; and (3) the exchange of information within the digital twin model. The proposed concept incorporates various strategies such as Building Information Modeling (BIM), the Internet of Things (IoT), and smart platforms to enhance project management. Based on the implementations of the digital twin concept, several conclusions were drawn: (1) rapid and direct transfer of information; (2) safety and quality concerns can be illustrated through images and videos; and (3) improvements in efficiency and cost reduction.

Table 9. DT—summary of processes and quality control.

Year	Author	T&C	Process and Sub-Process	QC
2024	[68]	DT + CV	Material tracking	-
2023	[69]	DT	QC	Automatization
2024	[70]	DT	Management	-

summarizes the DT concept and its implementation in processes and sub-processes, highlighting its impact on quality control within the context of Construction 4.0.

Following the overview of each technology and concept (T&C) concerning their implementation in various steel construction processes, Figure 3 illustrates the frequency of utilization for each T&C. The steel construction processes described in Figure 3 are derived from Table 3, Table 4, Table 5, Table 6, Table 7, Table 8 and Table 9. The x-axis represents each T&C, while the y-axis shows the percentage of frequency for each steel construction process. For instance, in relation to Table 9, there are three aforementioned processes where DT is utilized (material tracking, quality control, and management), meaning each process accounts for 33%. Material tracking is predominantly supported by QR codes, barcodes, and RFID technology, with 80% of research articles employing this process, followed by IoT and Blockchain. Additionally, the expanding database for design processes and management is significantly influenced by BIM and immersive technology, with utilization rates of 50% and 40%, respectively. A crucial point mentioned in the introduction can be summarized from the graph: quality control is the most frequently employed process that can be utilized with each T&C. It is clear that robotics and deep learning lead in quality control. This finding stems from the repetitive nature of control processes, making deep learning an excellent choice for automating these tasks. Although those percentages vary based on the number of researched articles, this graph clearly indicates which processes are frequently utilized for each T&C, especially for T&C with a higher number of searched articles.

Following a concise overview of the previously mentioned technologies, the paper proceeds to discuss the T&C integrated within Construction 4.0, drawing upon the knowledge acquired thus far. The questions posed in Section 1 will also be addressed, and the authors will strive to derive guidelines and insights for future research based on the analyzed articles.

4. Discussion

Following a comprehensive review and analysis of articles, this discussion presents a comparative examination of the technologies noted within the AEK industry. This comparison aims to highlight the technologies and concepts most frequently employed in the manufacture and assembly processes of steel constructions, with a particular focus on their application in quality control.

4.1. Building Information Model (BIM)

The concept of Building Information Modeling is a key element for efficient, rapid, and precise design. Analyzing various articles reveals that BIM is implemented across all processes involved in the manufacturing and installation of steel construction, with its most significant representation found in the design process. In terms of design, BIM can automatically generate workshop drawings from 3D models [10,16], optimizing project costs. Additionally, it facilitates collision detection, reducing the need for construction site revisions [9,18]. Utilizing BIM for reconstruction projects also accelerates the modeling process [11,14]. Beyond design, BIM serves as a valuable tool for cost estimation [20]. In quality management, BIM, with the utilization of various sensors, can be a good tool for deformation control [19]. Furthermore, BIM supports virtual pre-assembly, aimed at minimizing project costs by the timely identification of defects. The implementation of BIM across all manufacturing and installation processes is critical for automatization, digitalization, and the use of smart machines. However, several limitations may hinder full integration, such as the AEC sector’s conservatism and the potential cost of BIM software licenses for smaller companies. Besides the analyzed benefits and limitations, the main guidelines extracted from the analyzed article for future BIM research include: (1) establishing standards for BIM; (2) developing automatic point-cloud extraction; (3) exploring VR application in pre-assembly; (4) integrating deep learning and optimization of algorithms within manufacturing processes; (5) conducting further research on the BIM application.

4.2. Barcode, QR Code, and RFID Technology

The analysis of the articles and the insight from Table 2 highlight significant advancements in material tracking and identification. The use of technology for information sharing among project participants increases efficiency, leading to faster decision-making [26,27,31] and reducing project delays. In the comparison between RFID technology and QR code technology, several advantages of RFID have been identified. RFID tags exhibit greater robustness and resistance to challenging environmental conditions. Moreover, RFID technology enables the storage of more information than QR codes and allows for the simultaneous scanning of multiple items [30]. While RFID tags are comparatively more expensive than QR codes, their reusability offers a favorable economic justification over time. However, one notable concern regarding RFID technology is its susceptibility to hacking, as it operates through radio waves. Nonetheless, recent advancements in RFID chip technology, as discussed in paper [71], present improved security features that mitigate the risk of hacking. Furthermore, it is essential to recognize that when dealing with steel constructions, the proximity of metal surfaces may interfere with RFID signals, potentially complicating the reading of tags [30]. In the realm of quality control, this technology primarily enhances the automatization of processes such as data collection, data analysis, and facilitating coordination of information among participants during the construction and maintenance of the building. Based on the reviewed articles, several directions for future research can be identified: (1) further investigation and comparison of the implementations of RFID tags and QR codes; (2) utilization of passive RFID tags on construction projects.

4.3. Immersive Technology

Immersive technologies, as demonstrated by the reviewed articles, significantly enhance the initial understanding of projects and 2D drawings [37,38,46]. The data presented in Table 3 reveals that immersive technology is most extensively utilized during the project planning phase, followed closely by its application in quality control. Moreover, immersive technology significantly enhances decision-making by allowing for the visualization of projects that have yet to be realized [36,38,44]. This capability greatly facilitates and accelerates communication among construction participants, thereby minimizing the need for revisions. The use of immersive technology in quality control began with utilizing AR technology for the precise positioning of structural elements [40], while in [43], the use of immersive technology was implemented in the automatic recognition of geometric errors. Additionally, the study [43] emphasizes cost optimization and faster communication between participants through the use of immersive technology. The limitations and challenges associated with the application of immersive technology include the accuracy of immersive devices, the precision of aligning virtual models with real-world environments, the high costs of the devices, and the requirement for additional training for employees. Future research directions in immersive technology, based on the reviewed articles, include: (1) the development of web-based AR tools; (2) the integration of tracking methods with sensor data and photorealistic rendering technology in AR; (3) exploring how 3D models can be adaptively displayed during construction of the building; (4) the creation of a simulator that closely resembles real-world scenarios; (6) enhancing immersive technology within the quality control process.

4.4. Internet of Things

This concept facilitates rapid and precise data transfer among all participants in a project [50]. In addition to enhancing data collection efficiency on construction sites, the IoT concept extends to manufacturing, allowing for communication between machines, which significantly accelerates processes involved in the production of steel construction [53]. Furthermore, IoT enables system automation, decreasing the time needed for manual, repetitive tasks, thereby reducing employee labor costs. When considering integration with other T&C, it is evident that IoT predominantly connects with BIM and RFID technology, aiming for more efficient development of these two systems. Despite the advantages outlined, one of the primary challenges associated with the IoT concept lies in the interoperability of IoT devices with existing devices and analytical software within facilities. Furthermore, the reliability of IoT devices in offline mode is something that still needs to be investigated, and in the case of Wi-Fi network connectivity, security against hacker attacks is also something that needs attention. Additionally, the reliability of IoT devices in offline mode remains an area requiring further exploration, and concerns about security against hacker attacks in cases of Wi-Fi network connectivity also warrant attention. The future directions for the IoT concept include: (1) the integration of industrial standards into developed IoT platforms; (2) the installation of smart objects during construction; (3) the development of a real-time display system; (4) the integration of IoT-BIM-RFID and BTC; and (5) utilizing cloud-based approaches to enhance data access.

4.5. Blockchain

The application of Blockchain as a technology in the AEC sector is predominantly observed in material tracking and management processes. Utilizing blockchain shows a notable increase in data transparency and immutability, along with enhanced security protocols [55]. One of the primary advantages of this technology lies in its ability to improve traceability and facilitate transparent information sharing [58]. Despite the limited amount of conducted research, existing studies suggest that blockchain can lead to cost reductions [57]. Furthermore, based on a relatively small number of articles, several guidelines for future research have emerged: (1) exploring the integration of BTC with IoT technology; (2) conducting studies to validate the long-term benefits of blockchain-based material management; and (3) combining Digital Twins (DT) and BTC technology for more transparent material visualization. It is important to note that BTC has not yet seen widespread implementation in the AEK industry, largely due to a conservative approach and a lack of experience and knowledge regarding BTC within the AEC industry.

4.6. Robotics and Deep Learning

Robotics and deep learning can significantly enhance the efficiency of industrial facilities by optimizing the time needed for repetitive tasks, allowing human resources to concentrate on other processes of steel manufacturing. In studies [59,60], productivity and time savings are markedly improved compared to manual labor; more importantly, the use of robots for assembly tasks enhances worker safety under challenging working conditions. Regarding deep learning, time savings are achieved not only during repetitive actions but also in minimizing errors during visual inspections [61]. In quality management, deep learning can be useful for the automatic identification of errors [64]. The analysis of these articles has led to the identification of several guidelines for future research on these topics: the development of automated robotic systems; (2) the creation of autonomous systems for detecting damage to steel constructions; (3) the formulation of models for counting various components; and (4) the advancement of automated inspection systems for recognizing dimensional and geometric properties of structural elements.

4.7. Digital Twin

Digital monitoring of all processes and sub-processes involved in the production, assembly, and maintenance of buildings is a goal that the current industry is actively pursuing. However, the limited number of articles offering specific guidelines for the development of Digital Twins (DT) or merely providing theoretical overviews of their impact on construction presents significant challenges for the industry. The concept of DT allows the physical structure of a building to undergo an enhanced safety process in the realm of virtual reality. In essence, this concept enables the making of timely and informed decisions by simulating all potential actions related to the project’s future. This leads to more concise decision-making, allowing the resources and costs required for implementation to be utilized efficiently. Among the key advantages highlighted by this concept are enhanced quality control, improved work coordination, and increased safety on construction sites [68]. As presented in [67], real-time quality control utilizing the Markov method can automate various quality control processes. The study in [70] highlights how DT enhances the accuracy of decision-making. Based on the analyzed articles, future directions for research that can be implemented within DT are: (1) validation of the proposed DT models in real-world projects; (2) autonomous communication among machines; (3) a platform for real-time data collection; (4) the development of a quality control management platform based on DT; (5) the creation of intelligent algorithms for project control and management; and (6) guidelines for construction practices supported by DT.

4.8. General Remarks

Following a thorough examination of the discussed technology, it is evident that the ongoing integration of Building Information Modeling (BIM) with other technologies is crucial for advancing Construction 4.0. Recent years have shown substantial progress in this area. Over the past 5 to 10 years, BIM has been successfully combined with RFID, immersive technologies, and the Internet of Things (IoT). Ultimately, the synergy between BIM and these complementary technologies is vital for achieving the objectives of Construction 4.0. As illustrated in Figure 4, BIM is the most frequently referenced term in relation to Construction 4.0 and the application of advanced technologies and construction practices.

Furthermore, Figure 5 illustrates the relative relationships among keywords in terms of their development and relevance degree. As can be seen, basic themes are dominantly covered by steel construction, BIM, and automation methods, while RFID technology is the link between basic and motor themes. Motor themes are building information projects overlapped by structural methodology, and digital twin control. Niche themes are considered monitoring process and manufacturing traceability, while planning, inspection and materials modeling are considered emerging and developing.

Following the sub-chapters from the discussion and considering integration between T&C, BIM stands as the most important technology in the context of Construction 4.0 and the steel construction industry. BIM is significantly utilized in project design, which enables making higher-quality decisions, automatic generation of 2D drawings, and helps predict potential collisions. Furthermore, BIM offers a robust visual representation of the project that can be compared to immersive technology. In addition to enhancing project visualization, immersive technology also supports improved quality control and a more precise understanding of 2D drawings. Next, QR codes, RFID, IoT, and BTC are particularly notable for enhancing information transfer. Among these, IoT deserves special attention, as it employs various sensors to facilitate complete automation and digitization of processes, ultimately leading to reduced project costs. Moreover, IoT plays a crucial role in overall project oversight, as the integration of different sensors and compatibility of smart devices allows for the effective monitoring of production facilities, assembly structures, and maintenance of buildings. In addition to facilitating information transfer, QR and RFID technologies lead the way in improving material identification, significantly automating the retrieval of elements within manufacturing facilities as well as on construction sites. However, it is important to consider certain limitations associated with these technologies, such as data security concerns, potential interference from radio waves due to steel construction, and the effects of weather conditions on QR codes. In contrast, blockchain has demonstrated its superiority in terms of information transfer. Nonetheless, the complexity of blockchain, coupled with corporate conservatism and the insufficient research regarding its long-term costs, means that QR codes and RFID technologies currently remain at the forefront of data analysis and information flow processes compared to blockchain.

Additionally, several important guidelines for future research can be derived from Figure 6. In this figure, the future research directions proposed by the authors of the selected articles are categorized according to each T&C. Each color represents a specific guideline; however, it is important to note that these colors are not correlated across different T&C categories. The size of the pie chart segments reflects the number of guidelines from the selected articles relevant to each T&C. The charts indicate that the development of platforms is one of the most frequently mentioned guidelines. Following this, automation is highlighted, along with technologies such as robotics, deep learning, and building information modeling (BIM). Furthermore, some guidelines focus on the quality control process, underscoring the thesis presented in the introduction emphasizes the need for the digitalization of quality control. Guided by these findings, the author intends to adhere to these guidelines in the next stage of research.

5. Conclusions

This conclusion presents the evolution of technology over the past year and examines its effects on the processes and sub-processes involved in the production and assembly of steel construction. After reviewing the relevant articles and analyzing emerging technologies and concepts, the authors will address the three questions from the introduction.

Question Q1 is best understood through Section 4. When considering the advantages of new technologies and concepts, a common theme emerges: improved information transfer, enhanced speed of design, and a reduction in overall project costs. Moreover, Construction 4.0, combined with emerging T&C, has the potential to significantly improve steel manufacturing processes by leveraging automatization and digitalization, resulting in a higher quality of steel construction. Although the integration of new T&C into the steel construction can improve various processes, challenges such as conservatism, the costs associated with adopting new technology, and a lack of experience remain significant barriers to achieving full Construction 4.0.

Question Q2 can be addressed for each technology individually, but within the context of Construction 4.0, future guidance should focus on their integration with other T&Cs, as well as their implementation in manufacturing and assembly processes. Important guidelines are presented in detail in Section 4. It can be concluded that future research should focus on the automation of manufacturing and assembly processes. With this in mind, the reduction in manual labor could be significantly achieved, which also has advantages in terms of safety measures on manufacturing and construction sites.

In response to question Q3, and with reference to the technologies employed in quality control, the information from Figure 3 offers valuable insights. Response to this question provides an understanding of the T&C that can automate, digitize and speed up quality control processes in the context of Construction 4.0. In the realm of steel constructions and quality control, T&C such as BIM, immersive technology, RFID, IoT, and deep learning are leading the way, although immersive technology requires further exploration, particularly concerning the precision and deviations associated with the devices utilized.

Based on this review and the responses to the questions, it is clear that a significant turning point in the realm of Construction 4.0 is the integration of Building Information Modeling (BIM) with various technologies and concepts. While BIM is primarily employed as a standalone technology during design processes, its integration with other technologies and concepts can extend its application to all manufacturing and assembly processes in steel construction. Furthermore, it has been demonstrated that technologies and concepts such as digital twin (DT), deep learning, robotics, and the Internet of Things (IoT) play a crucial role in synchronizing devices within manufacturing, thereby enhancing automation and enabling comprehensive monitoring through sensors. This integration can lead to improved quality control processes. In regard to immersive technology within the steel construction industry, it remains in the early stages of implementation, particularly concerning quality control processes. As for RFID and QR code technologies, a chronological examination of the literature reveals that their primary purpose has remained consistent over the years. Initially utilized mainly for material tracking and identification, there is potential to further explore the application of these technologies in manufacturing and assembly processes, including enhancements in quality control.

Currently, the industry is making efforts to merge BIM with other aspects of Construction 4.0. However, it has not yet reached its full potential. Nevertheless, the recognition of the synergy between BIM and these other technologies presents a promising opportunity for advancing all processes and sub-processes involved in the production and assembly of steel construction, particularly in terms of quality control.