This paper presents a systematic review of Construction 4.0 in the context of the building information modeling (BIM) 4.0 premise. It comprises a review of the industry in the pre-fourth industrial revolution (4IR) age, the current and anticipated development of the 4IR, Construction 4.0’s origin and applications, and the synergy of its main drivers, i.e., the synergy of BIM with the internet of things (IoT) and big data (BD). The main aim of the paper is to determine the Construction 4.0 drivers and to what extent are they initialized by the 4IR, their development and their synergy with BIM, and the direction of BIM’s implementation in the construction phase. It was found that the main drivers of Construction 4.0, which originated from the 4IR, are BIM, IoT, and BD, but with specific implementations. The results of the analysis of BIM with IoT and/or BD revealed that the integrative approaches combining the aforementioned drivers show signs of project enhancement by providing significant benefits, such as improved real-time monitoring, data exchange and analysis, construction planning, and modeling. Furthermore, it was revealed that the main drivers are mostly applied in the project’s preconstruction phase, which is continuously developing and becoming more automated. The state-of-the-art review presented in this paper suggests that BIM is in transition, adopting Construction 4.0 to become BIM 4.0.

This paper reviews the recent literature on skill and labour shortages in the labour market with special emphasis on the construction sector in the European Union Member States, foreseeing the Construction 4.0 era. The free movement of people is one of the rights of all citizens of the EU which also includes the free movement of workers. Labour shortages in the EU are expected to increase in the future due to a declining population and an ageing workforce. In order to recognize and forecast labour shortages, EU Member states use a variety of instruments but they do not answer as to whether it is possible to use migrant labour to appease those shortages. There are several systems used to classify labour shortages in the EU Member states. Most of the countries classify labour shortages in relation to different sectors or occupation groups as well as by skill levels, but in some Member States, classification is made according to the type of employment. Instruments used to measure labour shortages significantly differ from country to country. Several criteria are used for creating lists of shortage occupations and most of the criteria include demand side and supply side criteria. A majority of the Member States are facing labour and skill shortages in various sectors and the construction sector is not an exception. As total employment in the construction sector decreased, so did the share of employed migrants. Labour shortages in the construction sector can be eased by the availability of a labour supply willing to accept unqualified and low-paying jobs. The construction sector seeks low-, medium-, and high-skilled individuals and is most likely the sector where most of the incoming migrants will be working, which has an impact on the development and implementation dynamic of Construction 4.0.

Construction scheduling, in practice, commonly relies on the usage of commercial project management tools (PMT) without specific optimization features. To obtain optimal schedules, planners often need to develop separate optimization models with special tools, which, however, demand further processing and editing of optimization results by PMT into forms expected for project management. In this regard, separation of optimization and PMT also requires considerable additional work for complete and harmonized updating of schedules during construction execution. Mentioned drawbacks and lack of available time may take to deficient construction scheduling during the implementation phase resulting in poor or even insufficient realization of project goals. Therefore, this paper presents an achievements survey on the integration of optimization and PMT that allow sustainable construction scheduling, particularly in terms of continuous optimal time and resource allocation throughout the project life cycle. Such work has not yet been comprehensively done up to now and the present contribution intends to fill a literature gap in the aforesaid area. Following a brief introduction, the optimization platform for construction scheduling is given in the article. Focusing on construction scheduling, an in-depth achievements survey on the integration of heuristics methods, mathematical programming and special solving methods with conventional PMT as well as optimization-based building information modeling (BIM) tools is then performed and findings are reported. The paper ends with conclusions and recommendations for further research.

This paper presents an active building information modeling (BIM) approach for work facilities and the optimal positioning of tower cranes on construction sites with repetitive operations. In this context, the metamorphosis of a passive BIM approach into an active approach is described. Here, the enhancement of the construction-ready BIM model starts with the export of the optimization input parameters, such as the 3D coordinates of the building, perimeter of the construction site, space for feasible solutions, relevant segment of the building with repetitive works, etc. Depending on the complexity of the problem, the user selects a suitable optimization approach and formulates the tower crane positioning optimization problem with the objective of minimizing the total duration of the operation’s cycle. Similarly, according to the model formulation, the user also chooses the optimization tool, including the search algorithm. The final step involves the post-optimal analysis and importing of the optimal solution into the BIM. An application example is demonstrated at the end of the paper to show the advantages of the proposed approach in which the optimization model has significantly improved the initial solution of the crane and depot positions.

The fourth construction industry revolution (i.e., Construction 4.0), driven by the fourth industrial revolution, introduces technological novelties to the construction industry in the direction of utilizing automation and digitalization potential. Various levels of maturity and adoption of these technologies have been identified separately in previous studies. In this study, a state-of-the art literature review is presented with the aim of determining the genesis and current levels of digitalization and automation, as well as their interoperability, among the main construction projects’ life-cycle phases. The results revealed that the construction project life-cycle phases are indeed at significantly different digitalization and automation levels. The initiation phase was found to be at a low level of digitalization and automation, the design and planning phase at a high level of digitalization with a low level of automation, and the execution phase at low-level digitalization with a higher level of automation. Since the topic is continuously developing, this research could be conducted in the near future to determine the advancements in comparison to the current conclusions.

During road construction, granular materials for the unbound base course (UBC) and cement-bound base course (CBC) are mostly compacted by vibratory rollers. A widespread laboratory test for determining the optimal moisture content (OMC) and maximum dry density (MDD) of the mixture for installation in UBC and CBC is the Proctor test. Considering that the Proctor test does not produce any vibrations during compaction, this paper compares the Proctor test and the vibrating hammer test. The examination was conducted on UBC and CBC with varying cement content and aggregate types. All mixtures were compacted by both methods with the aim of determining the compaction and strength characteristics. The results indicated the high comparability of the two test methods for mixtures with natural aggregate in terms of MDD, OMC, density and strength characteristics (California bearing ratio (CBR) for UBC and 28-day compressive strength for CBC). For mixtures with higher cement content, the OMC difference depending on the laboratory compaction method used can be significant, so the laboratory compaction method should be chosen carefully, particularly for moisture-susceptible materials. This paper also reveals that by increasing the proportion of rubber in the mixture, the compaction and strength characteristics differ significantly due to the compaction method. Therefore, when using alternative and insufficiently researched materials, the compaction method should also be chosen carefully.