Open AccessBuilding a predictive model to improve the quality of government building construction projects in Iraq using Multi Linear Regression technique
Author(s) -
Ahmed F. H. ALFahham,
Hatem K. B. Alajeeli
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/888/1/012060
Subject(s) - quality (philosophy) , government (linguistics) , measure (data warehouse) , process (computing) , construction engineering , regression analysis , engineering , process management , risk analysis (engineering) , computer science , transport engineering , business , data mining , philosophy , linguistics , epistemology , operating system , machine learning
Quality measurement is an important tool for quality improvement. Due to the lack of tools and methods used to measure quality, quality improvement in construction projects is difficult. As a result of the high cost of construction projects for public buildings and the lack of improved tools for measuring quality, there is an urgent need to develop new models. This study aims to provide necessary information for owners, project managers, designers, and contractors to determine the main and secondary factors that have a major impact on improving the quality of construction projects for government buildings and reduce maintenance. This study also contributes to building a predictive model to measure the quality of these projects, and a literature review and interviews were conducted. A personal figure to collect a list of factors affecting the quality of government building projects, and the resulting factors were subject to a survey that was sent to owners, project managers, and engineers working on general construction projects in Iraq. Adoption of the technique of multiple linear regression in the modeling process and determining the most important factors that affect the quality of the project.