A Framework for Crane Selection in Large-Scale Industrial Construction Projects

Selecting the best possible cranes and identifying spatial conflict-free locations on sites can result in productivity and safety improvements for large-scale industrial construction projects. In the current practice, experienced lift engineers select cranes based on the heaviest lift and/or the largest lifting radius of the identified crane. This practice is relatively time-consuming, and optimization of the crane’s use and location is also difficult. There are many factors which need to be considered during the crane selection process, a reality which further complicates the process. This paper presents a framework which aims at developing a decision support system to enhance the crane selection process and collision-free path planning for large-scale construction projects. This paper utilizes an innovative crane selection matrix in order to establish a process for optimized crane selection for construction projects. The study considers more than 40 different factors in order to reduce time and improve safety for crane operations. Following finalization of crane type (mobile crane versus tower crane), a visualization model to simulate crane operation and identify collision-free crane operation paths is proposed. This process can assist project managers to plan the lifting process more effectively and efficiently. A case study-based approach was utilized to demonstrate the proposed methodology. The methodology was tested in the planning and construction process for boiler house structures in Mannheim, Germany. The project entailed numerous challenges: one of the major tasks was to lift a 102-ton load on the top of the boiler structure through crane collaboration; space limitations on site also presented several challenges related to crane selection, location, and operation processes. Based on the project constraints, the proposed crane selection framework, and the visualization models, two tower cranes were selected and successfully implemented in the case study.