3D CAD models are tools used in the industry for planning and simulations before construction or completion of tasks. In many cases, such as in the oil and gas industry, these models can be massive, that is, they have large-scale detailed information in order to be sources of accurate information. Interactive navigation in these models requires a combination of appropriate hardware and software. Even nowadays with modern GPUs, the direct rendering of these models is not efficient, requiring classic approaches such as culling non-visible objects and LOD before sending the data to the GPU. Therefore, for real-time rendering of massive CAD models, we need scalable algorithms and data structures to efficiently process the scene. The work of this thesis proposes MCAD (Massive Computer-Aided Design) Shape grammar, an expansive grammar that procedurally generates objects to create 3D scenes of massive models. In recent years procedural modeling has drawn attention for quickly creating 3D scenes using a compact representation, which stores generation rules rather than explicit representation of the scene. MCAD Shape grammar explores repetitions and patterns present in massive models for rendering scenes, reducing memory footprint and procedurally processing the scene efficiently. We converted real refinery models into MCAD Shape grammar and implemented a renderer for them. Results showed that our solution is scalable with high performance, also it is the first time that procedural modeling is used in this domain.