Rule-based autocorrection of Piping and Instrumentation Diagrams (P&IDs) on graphs
This addresses the significant revision workload for chemical engineers in large-scale projects, though it is incremental as it builds on existing graph-based approaches.
The study tackled the problem of manually reviewing Piping and Instrumentation Diagrams (P&IDs) for errors by proposing a rule-based method for automated error detection and correction on graph representations, validated through a case study.
A piping and instrumentation diagram (P&ID) is a central reference document in chemical process engineering. Currently, chemical engineers manually review P&IDs through visual inspection to find and rectify errors. However, engineering projects can involve hundreds to thousands of P&ID pages, creating a significant revision workload. This study proposes a rule-based method to support engineers with error detection and correction in P&IDs. The method is based on a graph representation of P&IDs, enabling automated error detection and correction, i.e., autocorrection, through rule graphs. We use our pyDEXPI Python package to generate P&ID graphs from DEXPI-standard P&IDs. In this study, we developed 33 rules based on chemical engineering knowledge and heuristics, with five selected rules demonstrated as examples. A case study on an illustrative P&ID validates the reliability and effectiveness of the rule-based autocorrection method in revising P&IDs.