The College of Administration and Economics at the University of Baghdad discussed , a master’s thesis in field of Industrial Management by the student (Nabaa Mohammed Sharif) and tagged with (Adoption of Agile Project Management to Achieve Sustainable Performance Using Artificial Intelligence: A Case Study in the Roads and Bridges Department) , Under supervision of (Assist.Prof Dr. Aws Hatem Mahmoud )
This study aimed to clarify the concepts of each of the axes of agile management of projects (organization of the work site، continuous improvement، six sicama، encouraging creativity) and the axes of sustainable performance (environmental، social، economic). Then analyze the impact of the axes of agile management of projects and sustainable performance used on the effectiveness of the performance of the Department of Roads and Bridges.
The researcher adopted the case study approach as an integrated scientific approach in terms of methods of collecting data and information and analyzing the actual reality through the use of more than one method at the same time to obtain the maximum benefit related to the case studied.as she began using the examination lists to poll the opinions of the sample to support the case study، prepared for this purpose a questionnaire consisting of (49) items، and was applied in the Cordoba Bridge project to extract the knowledge and skill gaps of the axes related to (agile project management، sustainable performance). The researcher also built a model based on machine learning algorithms in order to improve the use of the agile methodology for sustainable projects to predict the quality of bridges.
In order to improve the management of construction projects and help in their sustainability، artificial intelligence was used، as machine learning was used through algorithms (linear regression)، (random forest classifier)، (logistic regression) and (decision tree classifier) to build a model that enables it to predict the quality of bridges، which is the main pillar in sustainability. The models were implemented using the Python programming language in the work environment (Google collab)، and the study found that the six-sikma axis seems satisfactory by 50% of the application range، but With a gap of 50% that requires work on improving the six sekma to ensure its success and effectiveness، the study also provided a comprehensive assessment of the performance of models in predicting the classification and quality prediction of bridges. The results showed that the RandomForestClassifier model achieved the highest accuracy by 0.88، and on this basis the forest classifier model was chosen as it carries the highest accuracy in learning and prediction to apply the agile methodology.
The study recommended the need to enhance interest in the use of agile management tools (work site organization، continuous improvement، encouraging creativity، six sigma)، and to see all that is new in this field because of its clear impact on achieving sustainable performance in the organization. Encourage project managers to integrate agile methodology with artificial intelligence to make the most of modern technology. The study recommended the need to enhance interest in the use of agile management tools (work site organization، continuous improvement، encouraging creativity، six sigma)، and to see all that is new in this field because of its clear impact on achieving sustainable performance in the organization. Encourage project managers to integrate agile methodology with artificial intelligence to make the most of modern technology.