Much engineering data is obsolete and stored in silos, these data are non-digitized and unstructured. This leads to safety risks, knowledge loss, prolonged engineering for capital projects, and a laborious digital transformation process
Needs for keeping Engineering Information current and consistent
Outdated and conflicting engineering information brings the risk of safe and efficient engineering and operation. Non-digitalized and unstructured historical engineering information make it difficult for identifying these information conflicts and updating requires tremendous manual work, costly and resource consuming.
The need for digital transformation towards Industry 4.0
Non-digitalized and unstructured historical engineering information using traditional file management systems make information difficult to find and consolidate, Therefore, significant manual work required to build digital twins or digital platforms for existing facilities, and this make digital transformation process extremely unproductive and expensive
Needs for “faster, cheaper and better” capital project delivery
Non-digitized and unstructured engineering data makes information difficult to find and consolidate into a standardized knowledge base, forcing engineers to reinvent data, recreate numerous drawings, datasheets, and specifications for each project. Current engineering process still has much manual data transfer and cross-checking between multiple disciplines, design tools, and platforms. All of these lead to an unnecessarily lengthy engineering process.
Engineering information is essentially presented in the form of drawings, documents and 3D models (either design-built or via point clouds). The application of AI technology in machine learning, deep learning, image/visual recognition, and natural language processing enables computers to “READ” and “UNDERSTAND” engineering documents and drawings the way a human would, effectively replacing manual processing, improving engineering productivity and further automating engineering deliverables.
By applying AI technology, computers can
Digitalize critical engineering drawings and documents;
Provide content searching capabilities;
Consolidate data and knowledge;
Automate engineering deliverables