ISSN:2630-5771
Journal of Construction Engineering, Management & Innovation
ARTICLES
Levent Sumer
Housing affordability is a rising problem all around the world. Türkiye is also tackling with this issue seriously. Türkiye is ranked at the top of the list among the most refugee-hosted countries, the United Nations Refugee Agency reports. After the Civil War started in Syria in 2011, millions of Syrians migrated to different countries. Türkiye, which is struggling with many socioeconomic problems, hosts 4.6 million officially confirmed refugees, and 3.6 million of them are Syrians. Immigration of many Russian and Ukrainian citizens after the Russia-Ukraine war started in the first quarter of 2022, and their choice of living in Türkiye by way of purchasing housing units also had an impact on the Turkish housing sector in terms of supply-demand balance and sales and rental prices of housing units. By conducting a questionnaire, this study investigates the Turkish people's perception of the impacts of refugees and immigrants on Turkish housing sales and rental prices. The effects on unemployment rates, inflation rates and level of tax revenues were also analyzed as other macroeconomic factors. The results of responses of 157 respondents were analyzed by using R programming. The analysis revealed that 89% of the participants had the perception that the tax revenues had decreased due to unregistered work. This was followed by an increase in housing rental prices and unemployment rates. The analysis showed that age, gender, location, or industry had no statistically significant impact on the results. As one of the pioneer studies in this area, this research suggests some policies to overcome refugee-related problems, especially in the housing sector.
https://doi.org/10.31462/jcemi.2024.04266280
Ibrahim Karatas
Abdulkadir Budak
Calculating the productivity of workers in traditional construction projects can be a daunting and time-consuming task. However, thanks to the advancements in technology and scientific research, measuring labor productivity can be automated. Therefore, this study aims to determine the productivity of gypsum plaster workers by collecting motion data with a sensor on their arms and using the support vector machine algorithm for analysis. Based on the estimation results, motion productivity is determined by calculating the ratio of the worker's working time to the total time. On the other hand, labor productivity is calculated by determining the ratio of the amount of work completed to the product of the number of workers and the total working hours. Finally, theoretical productivity is calculated by dividing motion productivity by the calculated labor productivity. According to the results of the analysis, whether the worker is working or not has been estimated correctly by 95.8%. On the other hand, the mean daily theoretical productivity has been determined to be 10.20 m2/man-hour. In this way, workers' activities can be automatically detected with a certain accuracy and their productivity can be calculated. This helps in the effective management of the construction site.
https://doi.org/10.31462/jcemi.2024.04281290
Sercan Baş
Ozan Eray Aydın
Gursans Guven Isın
Zeynep Başaran Bundur
The on-site integration of 3D printing and Building Information Modeling (BIM) has shown the potential to improve the production processes of digital fabrication with concrete. BIM can be used in the site planning and optimization of the digital fabrication process by optimally posi-tioning the 3D printers on the construction site. In this work, a BIM-based 3D-printer position optimization and path planning tool was developed using the Dynamo plugin of the Autodesk Revit software. This tool works similarly to the BIM-based site layout optimization tools for the operation and positioning of major construction equipment (e.g., cranes). The developed tool considers the physical properties of a robotic arm 3D printer, such as its dimensions and print-ing range, as well as the geometry and location of the elements to be printed on-site. It suggests the optimum path for the 3D printer to fabricate a project. The position optimization and path planning tool are validated for a case study of a real-world 3D-printed single-floor office build-ing and successfully reduced the number of steps required for printing the walls of the case study building, enabling significant time and energy savings.
https://doi.org/10.31462/jcemi.2024.04291309
AYNUR KAZAZ
ENDER YETİM
The research focuses on the improvement of lighting systems and the impact of photovoltaic applications on the energy efficiency of buildings, with the aim of increasing the energy efficiency of buildings in response to global challenges such as population growth and urbanization. The study, conducted in Antalya, located in the Mediterranean climate zone, evaluates the impact of upgrading the lighting system and integrating photovoltaic panels in three selected blocks within an island settlement. Energy efficiency assessments include a variety of factors such as building location, orientation, and energy use scenarios, including both natural gas and electricity for heating. Hourly analyses using DesignBuilder simulation and PVsyst software show that annual energy savings of up to 33.00% in lighting system energy consumption and 7.20% in total building energy consumption can be achieved by improving lighting systems. In addition, up to 14% of the energy demand can be met by integrating PV systems into the buildings. These results underscore the significant potential for reducing energy expenditures and environmental impacts. By demonstrating the effectiveness of an island-based strategy for improving building energy efficiency, this study expands the scope of energy conservation initiatives from floors, rooms, and buildings to an island-based approach.
https://doi.org/10.31462/jcemi.2024.04310335
Abdikarim Said Sulub
Fatemeh Mostofi
Vedat Toğan
The time-cost trade-off problem (TCTP) presents a significant challenge in construction management, requiring a balance between project duration and associated costs for successful completion. This study evaluates the performance of an arithmetic optimization algorithm (AOA) for solving the TCTP. AOA integrates non-dominated sorting (NDS) to generate Pareto-optimal solutions that address both time and cost objectives. The methodology involves testing the AOA on three case studies representing small- and medium-scale construction projects with 18, 29, and 63 activities. Comparative analyses with traditional metaheuristic algorithms, such as ant colony optimization, genetic algorithms, and particle optimization algorithms, reveal that NDS-AOA delivers competitive results, particularly in smaller projects that achieve lower costs and faster computation times. However, its effectiveness decreases in medium-scale projects, indicating scalability limitations. Numerical tests suggest that while AOA is well-suited for small to medium projects, it requires further enhancements, such as hybridization with other techniques, to effectively handle larger-scale problems.
https://doi.org/10.31462/jcemi.2024.04336353