BIM (building information modeling) is a kind of technology that has great potential to enhance the level of automation in architecture, engineering, and construction (AEC) projects. The created virtual model of the facility allows coordinating all industries during the entire life cycle of the building. The possibility to save the data related to the given facility in one place, namely in the BIM model, enables control and management of the AEC projects at every stage. During the design and implementation phase, BIM models facilitate the optimization of time, costs, and quality, and in the operational phase, they support effective management of the facility. The use of BIM for building energy modeling (BEM) is the next step of evolution in architecture and engineering design practice. The benefits of using the BIM approach are widely discussed in the literature; however, they may be hard to achieve if appropriate attention is not directed to minimizing the barriers to the implementation of this technology. Observing Europe, one can notice that western and northern countries successfully use BIM for their needs, while the countries of the Eastern Bloc, including Poland, introduce it at a slower pace. In the present paper, the authors conducted a cause-and-effect analysis of the identified barriers to the implementation of BIM technology in the construction process. For this purpose, the authors applied the Ishikawa diagram, which is a tool that helps to recognize the actual or potential causes of failure. The analysis conducted showed that one of the weakest links in the successful BIM implementation is people and, in particular, their lack of knowledge and reluctance to change. The authors indicated the need to introduce and strengthen preventive actions, mainly through education: training, courses, and studies focused on BIM technology.
Proper quality assessment of ready-mixed concrete, which is currently the principal material for construction, land engineering and architecture, has an impact on the optimisation and verification of correct functioning of individual stages of the production process. According to the European Standard EN 206 “Concrete–Specification, performance, production and conformity”, obligatory conformity control of concrete is carried out by the producer during its production. In order to verify the quality of concrete, investors generally commission independent laboratory units to perform quality assessment of both concrete mix and hardened concrete, which guarantees a high quality of construction works. One of the essential tools for ensuring the quality of test results is the participation of laboratories in the so-called proficiency testing (PT) or inter-laboratory comparisons (ILC). Participation in PT/ILC programmes is, on the one hand, a tool for demonstrating the laboratory’s performance, on the other hand an aid for maintaining the quality of available concrete tests and validating test methods. Positive evaluation is a confirmation of the laboratory’s capability for performing the tests. The paper presents the results of laboratory proficiency tests carried out by means of inter-laboratory comparisons, as shown in the example of quality assessment of ready-mixed concrete for nine participating laboratories. The tests were performed for concrete of the following parameters: strength class C30/37, consistency S3, frost resistance degree F150, and water resistance degree W8. This involved determining consistencies, air content and density of the concrete mix, and compressive strength of hardened concrete. For the evaluation of laboratory performance results, z-score, ζ-score and En-score were applied. The innovation of the proposed study lies in employing both classical and iterative robust statistical methods. In comparison with classical statistical methods, robust methods ensure a smaller impact of outliers and other anomalies on the measurement results. Following the analyses, clear differences were found between the types of detected discrepancy of test results, which occurred due to the nature of individual parameters. For two laboratories, two scores revealed unsatisfactory results for concrete mix consistency. The main reasons can be pouring into the cone-shaped form a concrete mixture that is too dry, or incorrect use of a measuring tool also creating a possibility that the obtained value can be wrongly recorded. Other possible reasons are discussed in the paper. Participation in inter-laboratory comparison programmes is undoubtedly a way to verify and raise the quality of tests performed for concrete mix and hardened concrete, whereas individual analysis of the results allows the laboratory quality system to be improved.
External facades of buildings and other structures shape the image of every building, creating the architecture of cities. Traditional concrete forms, as a symbol of durability and stability, have been replaced by lightweight enclosures—for example, in the form of aluminium–glass facades and ventilated facades. In this paper, the authors attempt to verify the strength of influence and relations between the identified factors shaping the costs of facade system implementation using structural analysis. On the basis of the collected quantitative and qualitative data obtained as a result of research on design documentation and cost estimates of implemented public buildings, as well as on the basis of interviews conducted among experts, factors which have a real impact on the costs of facade systems in the form of aluminium and glass facades and ventilated facades were identified. The indicated factors were analysed and classified using the method of structural analysis, namely the MICMAC method (refers to the French acronym for Cross-Impact Matrix Multiplication Applied to Classification). Particular influences and relations between factors were examined. Finally, six groups of factors influencing the costs of facade systems were identified, including regulatory factors that do not have a very strong impact on the level of costs, but which show a strong correlation with other factors; determinants that have a very strong impact on the costs; and a group of external factors that show the smallest influence on the estimation of façade cost.
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