Rule-Based Autocorrection of Piping and Instrumentation Diagrams (P&IDs) on Graphs

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.

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Publication Details

Journal
Systems and Control Transactions
Published
2025-06-30
DOI
https://doi.org/10.69997/sct.150968
Primary Topic
Graph Theory and Algorithms
Type
article
Field-Weighted Citation Impact
0.00

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article

Rule-Based Autocorrection of Piping and Instrumentation Diagrams (P&IDs) on Graphs

Dominik P. Goldstein, Artur M. Schweidtmann, Lukas Schulze Balhorn, Minji Kim et al.
Systems and Control Transactions
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article

Rule-Based Autocorrection of Piping and Instrumentation Diagrams (P&IDs) on Graphs

Dominik P. Goldstein, Artur M. Schweidtmann, Lukas Schulze Balhorn, Minji Kim, Niels Seijsener, Kevin Dao, Ge H. M. Driessen
article en

Abstract

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.

Systems and Control TransactionsVol. 4
Delft University of Technology (NL)
Siemens
Openalex Percentile: Top 87%
Graph Theory and Algorithms
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