LEE- Proje ve Yapım Yönetimi Lisansüstü Programı

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http://hdl.handle.net/11527/19431

Gözat

Yazar "Çakmak, F. Pınar" ile LEE- Proje ve Yapım Yönetimi Lisansüstü Programı'a göz atma
  • Öge
    Artificial intelligence influence for digitalized construction project management during planning phase
    (Graduate School, 2024-11-12) Karcı, Mahmut Emre ; Çakmak, F. Pınar ; 502211407 ; Project and Construction Management
    Digitalization has become mandatory considering the efficiency and productivity criteria reached in the 21st century and the developments in the construction industry in the last decade. Considering the size and employment rate it occupies in the world economy, the revolutionary digitalization adventure, which continues but has a long way to go, is far from being completed. The most valuable potential of Artificial Intelligence (AI) is that all industry components that play a role in the project life cycle can understand and benefit from it, even at different levels. AI is a set of sciences, theories and techniques whose purpose is to reproduce the complex tasks that a human can perform and the cognitive abilities of a human done by a machine. Additionally, these systems can process data and information like intelligent behavior, often including reasoning, learning, perception, prediction, planning or control elements. However, like many technologies in the construction industry, where the digital revolution is not completed, AI has not yet been fully adopted. In the construction industry, which differs negatively from other industries by starting digitalization late, digitalized practices can be observed at every stage of the project life cycle. Still, they cannot be significantly differentiated at any stage. However, various studies have noticed the greatest potential hidden in the planning phase. For this reason, this thesis aims to convey valuable information about AI to the sector components, shed light on the digital project and construction management planning phase from AI's perspective, contribute to its adaptation. (1) "What are the characteristics of Artificial Intelligence technologies in the construction industry?", (2) "What are the functions and applications of Artificial Intelligence in the construction industry?", (3) "What are the key criteria to be considered for the performance and impact of adopting Artificial Intelligence?", ( 4) "To what extent and how can Artificial Intelligence, subsets and technologies support the management of the construction project planning phase?"; Answers to these questions were sought to achieve the aims of this research. When the project construction literature is examined comprehensively, although the potential of AI technologies in the project planning phase is revealed, a lack of information and research on digital adaptation is noticed. Research conducted in the search engines of various databases focused on studies on "artificial intelligence features and subfields", "artificial intelligence applications", "relationship between artificial intelligence and the construction industry", and "artificial intelligence applications in the planning stage". As a result of the literature review, six major artificial intelligence-supported services that have the potential to play an active role in digitalized project planning in the construction industry were identified. These influence areas of AI are automated project scheduling, labor/productivity management, predictive modeling and risk determination, health and safety, accessible data and cost engineering. In the next step, a survey was conducted to various professionals from the construction industry to investigate the impact of using AI for digital construction project management during the planning phase. It was aimed to reach the effects of the concept of AI on project and construction management at the planning phase with the answers received to the questions asked on a 7-point Likert scale (1=not effective, 7=extremely effective) in the first part of the survey, which consists of two parts. In the second part, questions were asked to obtain demographic information about the survey participants. The aim of the survey study was to reach a 50% response rate, which was planned to be shared with 120 participants from the construction industry, determined by purposive sampling. The data obtained from the survey conducted using the SPSS 27 program was analyzed by subjecting it to various tests. First, Cronbach's alpha (α) reliability test was applied due to the need to test data reliability. Then, which of the various parametric tests would be used in the advanced statistical analyses planned to be carried out within the scope of the study is evaluated depending on the normality values of the Skewness-Kurtosis test. Later, the obtained data were subjected to the Pearson correlation test, which revealed the relationships between the evaluation criteria presented to the participants in the first part of the survey. Then, depending on the number of groups, independent samples t-test and ANOVA test were applied to evaluate the variables of the relevant groups, in order to search whether there is statistically significant difference in this evaluation. The t-test was applied to two paired groups. These groups are designed as (1) professions, (2) users and non-users of AI applications. During the one-way ANOVA test, the results divided into more than two groups were analyzed whether there is a significant difference in variable mean values. ANOVA groups are designed as (1) experience in the AECO industry, (2) associated organization, (3) organization scale and (4) years of experience with AI and concepts. Finally, Levene and post-hoc tests were applied to complete this phase of study. In scaling the effect of the specified AI applications on the variables, all influence areas have high mean scores. In the planning phase of construction projects, the highest effect was observed in accessible data, while the lowest was observed in health and safety. It was also understood that many influence areas were highly correlated. To sum up, within the scope of this thesis study, the concept of AI, its features, and current and future applications among digital technologies in the construction industry have been examined and analyzed. It aims to contribute to the limited literature, especially considering its position in the planning phase from the project and construction management perspective. In addition, many AI tools, applications and contributions that can be used during the construction project management and planning phase are mentioned. Also, the results and potentials that will arise from its practical use are mentioned. In this way, it can be claimed that the use of AI for digitalized project planning has the potential to solve low productivity and inefficiency problems, the biggest problems that the construction industry has had difficulty overcoming for decades. Finally, it is intended that this completed study will be a source of inspiration for industry-component companies, institutions, individuals and especially researchers who need motivation for the digitalization and progress of the construction industry.