In layered construction of offshore oil and gas modules, smooth docking and installation of steel structures on each layer are difficult due to manufacturing errors. This study proposes a method for detecting docking errors based on point clouds. This involves first registering the actual scanned point clouds of adjacent steel structures with their corresponding building information modeling models, and then calculating the alignment errors through feature extraction. This automated approach enables the docking feasibility to be evaluated prior to actual installation, thereby providing references for timely structural adjustments and reducing the possibility of rework. Compared with the traditional manual quality inspection method, our approach can effectively enhance detection efficiency and accuracy. We conducted experiments using two sets of simulated data to validate the accuracy of the proposed method. In addition, considering the characteristics of docking structures, we introduced a coarse registration algorithm based on five-plane sets. Experimental results demonstrate that the proposed coarse registration algorithm significantly enhances alignment accuracy as compared with four other methods.