P&ID to Excel: Can ChatGPT Handle Equipment Registers?

Can a language model do more than describe workflows—can it actually deliver a functional equipment register in Excel? We tested ChatGPT by feeding it a simple P&ID with four tagged items and asking for a ready-to-download spreadsheet.

Key Strengths or Features ChatGPT’s performance in this narrowly defined task showed several tangible benefits:

• Structured extraction: It identified one vessel, one pump, one heat exchanger, and one compressor directly from the drawing and legend.

• Automated file generation: Returned an Excel workbook with clear headers, tag references, and consistent formatting—no intermediary copy-pasting required.

• Formula-ready layout: Left the sheet in a state where filters, lookups, or cost macros could be added immediately, saving setup time for downstream teams.

  
  

Limitations, Risks, and Workflow Fit The model’s accuracy still depends on legible tagging; blurred or partially hidden text is flagged as “no tag,” so a quick visual review remains essential. Even with this safeguard, the register was produced in under five minutes, reducing routine documentation time and fitting neatly into Singularity’s rapid-turnaround philosophy of “one-day engineering.”

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