62 citations · 103 across the 6 of their papers we have counts for
6 papers
Talking like Piping and Instrumentation Diagrams (P&IDs)
Achmad Anggawirya Alimin, Dominik P. Goldstein, Lukas Schulze Balhorn +1
We propose a methodology that allows communication with Piping and Instrumentation Diagrams (P&IDs) using natural language. In particular, we represent P&IDs through the DEXPI data…
Rule-based autocorrection of Piping and Instrumentation Diagrams (P&IDs) on graphs
Lukas Schulze Balhorn, Niels Seijsener, Kevin Dao +4
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 insp…
Graph-to-SFILES: Control structure prediction from process topologies using generative artificial intelligence
Lukas Schulze Balhorn, Kevin Degens, Artur M. Schweidtmann
Control structure design is an important but tedious step in P&ID development. Generative artificial intelligence (AI) promises to reduce P&ID development time by supporting engine…
Toward autocorrection of chemical process flowsheets using large language models
Lukas Schulze Balhorn, Marc Caballero, Artur M. Schweidtmann
The process engineering domain widely uses Process Flow Diagrams (PFDs) and Process and Instrumentation Diagrams (P&IDs) to represent process flows and equipment configurations. Ho…
Data augmentation for machine learning of chemical process flowsheets
Lukas Schulze Balhorn, Edwin Hirtreiter, Lynn Luderer +1
Artificial intelligence has great potential for accelerating the design and engineering of chemical processes. Recently, we have shown that transformer-based language models can le…
Learning from flowsheets: A generative transformer model for autocompletion of flowsheets
Gabriel Vogel, Lukas Schulze Balhorn, Artur M. Schweidtmann
We propose a novel method enabling autocompletion of chemical flowsheets. This idea is inspired by the autocompletion of text. We represent flowsheets as strings using the text-bas…