Rule-based autocorrection of Piping and Instrumentation Diagrams (P&IDs) on graphs
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866916054076227584 |
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| author | Balhorn, Lukas Schulze Seijsener, Niels Dao, Kevin Kim, Minji Goldstein, Dominik P. Driessen, Ge H. M. Schweidtmann, Artur M. |
| author_facet | Balhorn, Lukas Schulze Seijsener, Niels Dao, Kevin Kim, Minji Goldstein, Dominik P. Driessen, Ge H. M. Schweidtmann, Artur M. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_18493 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Rule-based autocorrection of Piping and Instrumentation Diagrams (P&IDs) on graphs Balhorn, Lukas Schulze Seijsener, Niels Dao, Kevin Kim, Minji Goldstein, Dominik P. Driessen, Ge H. M. Schweidtmann, Artur M. Computational Engineering, Finance, and Science Artificial Intelligence 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. |
| title | Rule-based autocorrection of Piping and Instrumentation Diagrams (P&IDs) on graphs |
| topic | Computational Engineering, Finance, and Science Artificial Intelligence |
| url | https://arxiv.org/abs/2502.18493 |