The cost of modelling existing industrial facilities is currently considered to counteract the benefits of the model in managing and retrofitting the facility. 90% of the modelling cost is typically spent on labour for converting point cloud data to the final model, hence reducing the cost is only possible by automating this step. Previous research has successfully validated methods for modelling specific object types such as pipes. Yet modelling is still prohibitively expensive. We tackle a part of this issue by identifying the most frequent object types that require modelling in industrial plants to guide future work aimed at automating the tedious current practice. We determine a priority list of the object types in these facilities based on their frequency of appearance (%) and intent of modelling. A parametric study based on Outer Diameter (OD) then finds the most frequent OD ranges for these objects. The results indicated that steel sections were the most frequent object type encountered in all case studies.