Man-Hour Estimation Model Development in BIM-Based Projects with Machine Learning-Regression Algorithms

Abstract

Construction management is a service that uses project management techniques to planning, design and construction of a project. Another branch of construction management is the planning made during the bidding stages before the construction starts. At this stage, the scheduling of the work, mobilization and most importantly the project design and drawing time should be analyzed and accurate estimates should be made. For this estimation, the experience of the bidding organization is the biggest reference. Construction management techniques in a BIM-based project are challengeable. The biggest reason is that knowledge about BIM is much less than the others and still a developing system. Therefore, the margin of error in the estimated project duration to be predicted in the bids to be made for such projects increases. Considering that man-hour estimations are financially very important for the company. This study is aimed to make observations with advanced technologies which is applied ML algorithms and analysis methods for man-hour estimations in BIM projects at the bidding stage. The project information to perform a man-hour analysis of completed construction projects was requested from offices that have gained experience in BIM projects. The project information of 16 projects were tabulated. The collected information was converted into a data set and transferred into regression analysis algorithms using Python format. Data set, which was turned into a matrix, was analysed and the consistency of the parameters in data set was tested. Spent man-hour estimation was made, graphed over parameters with simple and multiple linear regression algorithms. 
 Keywords: Building Information Modelling (BIM), construction management, bidding, project management, Artificial Intelligence (AI), machine learning, regression analysis