Crane Operation Planning in Overlapping Areas Through Dynamic Supply Selection
Automation in Construction
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The planning of tower crane operations is a complex process that has significant impact on the time, cost, productivity, and safety of construction projects. This complexity pertains to the involvement of multiple tasks, cranes, and material supply locations, as well as their interactions with each other. Overlapping areas between cranes also lead to increased collision possibilities, resulting in additional crane operation complexity. To increase crane operation productivity while maintaining safety, proper linkage between tasks, cranes, and material supply locations is important. Past research has linked tasks to supply points based on minimized individual task operating time, such that a task is linked to a supply point that provides the minimum amount of time for task completion. This approach may not be as efficient as possible for construction sites with overlapping crane areas, as it may increase total project time although time for each individual task is at a minimum. To address this concern, this research develops a Java-based, agent-based modeling (ABM) simulation tool to investigate the effects of dynamic supply selection on crane efficiency. This ABM applies a dynamic supply selection system and tests numerous scenarios to ensure the most efficient linkage between tasks, cranes, and supply locations. To evaluate the capabilities of the developed method, it has been applied to a real-world construction project. The results of this case study indicate that effective crane operation planning, conducted through dynamic supply location selection, with respect to tasks and cranes, can have a significant impact on productivity and the total schedule time of crane tasks.
Crane operations; Overlapping areas; Agent-based modeling; Planning; Collision; Optimization; Supply location
Construction Engineering and Management
Park, J. W.,
Crane Operation Planning in Overlapping Areas Through Dynamic Supply Selection.
Automation in Construction, 117