# Towards Semi-Automatic Generation of a Steady State Digital Twin of a Brownfield Process Plant
## 2 Literature Review
### Automatic Generation of Digital Twins  
The research on automatic generation of digital twins has been motivated by several use cases. The closest state-of-the-art works and their differences are analyzed as follows. A dynamic digital twin, as defined in Section 1, has been generated from 3D CAD information for the purpose of using process state values from the twin as soft sensors [11]; the approach is not applicable to brownfield plants for which 3D CAD models are generally not available. A qualitative digital twin of the plant has been generated for co-simulating control software against the plant in order to detect logic errors in the virtual commissioning phase [12; 48]. A digital twin has been generated for hardware- in- the- loop testing of control software [52], another activity that is not applicable in the context of steady state models that does not capture time-related behavior. A digital twin has been generated for the analysis of bottlenecks [53]; out of all the works reviewed in this section, this is the only one that is relevant to the specific purpose of the research presented in this paper, which is the design and validation of retrofits. However, the bottleneck analysis was performed specifically in the context of discrete manufacturing systems, so the approach is not applicable to the continuous processes addressed in this paper. Our main contribution over the state-of-the-art is to address the lack of research on automatic generation of digital twins, or even simulation models, that are applicable for the design and validation of retrofits to process plants. Nowadays, a limited number of the most modern plants have digital, machine-readable design information available. The information for other plants is mostly accessible in printed papers, static PDFs, and other human-readable formats [7]. To limit the engineering cost of digital twin development for brownfield plants, it is important to have a fully or at least partially automatic solution for simulation model creation from the available plant information. There are different available sources of information at process plants for the automatic generation of a digital display [11], such as datasheets, Process Flow Diagram (PFD) and Piping & Instrumentation Diagram (P&ID) diagrams, IO lists, 3D plant models and logic diagrams. The required information for simulation model creation can be extracted from these documents. The source information for the digital twin creation is not limited to design and engineering documents; for example, in [53] it was shown that a low fidelity digital twin has been generated automatically from high level requirements of the initial design phase of the project. Ref. [11] presents an automatic generation of simulation based digital twins for industrial process plants from 3D models. [PERSON] et al. [6] present an automatic solution to create the abstract graph model of the process system from a digital P&ID and a 3D CAD model of the system. This work was continued towards integrating the P&ID and CAD information by first converting the extracted information to the same level of abstraction [54]. Similarly, [55] introduces an automatic approach for matching 2D design documents and 3D scanned models of the process system by creating attribute graphs, calculating the level of similarity between graphs and merging the extracted results. [PERSON] et al. [56] use graph matching techniques to empower plant design engineers to reuse design information from existing process plants. The digital twin is not the only use case for automatic model generation. For example, [PERSON] et al. [57] present a general automatic solution reconstruction of an as-built 3D model of a brownfield process plant from 3D laser-scan data, a 3D CAD database, and P&ID documents. An automatic solution for extracting information from laser-scan data to detect straight pipes, elbows, and tee pipes is presented in [58] for generating an as-built 3D pipeline model.