Graph-Co digitizes and migrates technical flow diagrams into graph-based, intelligent models for use in Asset Lifecycle Management (ALM) and Computer-Aided Engineering (CAE) systems, such as Siemens COMOS. This process enhances corporate engineering standards and collaboration across disciplines while significantly reducing costs and time associated with manual data transfer.
Funding
Funding not disclosed
Founders
Product
Problem
Managing and utilizing technical flow diagrams, such as Piping and Instrumentation Diagrams (P&IDs), across the asset lifecycle is challenging due to their static nature and lack of integration with modern Asset Lifecycle Management (ALM) and Computer-Aided Engineering (CAE) systems. Manual data transfer from these diagrams is time-consuming, error-prone, and hinders collaboration across engineering disciplines, leading to inconsistencies and inefficiencies.
Solution
Graph-Co, under the Graph-ID brand, offers a solution for digitizing and migrating technical flow diagrams into graph-based, intelligent models that seamlessly integrate with ALM/CAE systems like Siemens COMOS. By converting non-intelligent R&I schematics (DWG, DGN, PID, PDF) into digital objects and graph-based models, Graph-ID facilitates the creation of enterprise-wide engineering standards, detailed plant information, and enhanced collaboration. The Graph-ID process extracts content from existing flow diagrams and transforms it into XML files, enabling comprehensive analyses, modular engineering, and the enrichment of digital twins. This approach eliminates heterogeneous CAE/CAD conventions, plant-specific documentation, and complex manual data transfers, ensuring data consistency and integrity across the organization.
Target Audience
The primary target audience includes companies in the process industry seeking to improve their asset lifecycle management, ensure regulatory compliance, and enhance collaboration across engineering disciplines.
Features
- Extraction of data from brownfield R&Is and delivery as XML files for data analysis and digital twin enrichment
- Conversion of R&I schematics into graph-based models for ALM/CAE systems, such as Siemens COMOS
- Automated extraction of quantities for all objects from large volumes of R&Is, useful for turnaround planning and RfQ processes
- Symbol recognition on R&Is to generate a table of all variants with counts for calculation purposes
- Secure data transfer to a Microsoft Azure silo with customer-exclusive data storage
- Automated data extraction and XML creation within a closed Azure environment
- Secure API for migrating XML files to target ALM systems