What Is a Tag List in Engineering?
A tag list — also called a tag register or equipment register — is a structured inventory of every tagged item in a design: instruments, valves, equipment, piping lines, and other engineered items. Each tag is a unique identifier that links the physical item to its P&ID location, datasheet, purchase order, and maintenance record.
On any EPC project, the tag list is foundational. Everything from procurement to commissioning traces back to it. A wrong tag, a missed tag, or a duplicate tag creates rework that propagates through the entire project.
Why Manual Tag List Extraction Is Slow and Error-Prone
The conventional way to build a tag list is to read each P&ID drawing, identify every tagged item, and key it into a spreadsheet.
The problem is not that this is hard — it is that it is slow, repetitive, and the kind of work where human error is almost inevitable:
- Tags are embedded in drawing callouts that require careful reading
- The same tag may appear on multiple drawings (a process P&ID and a utility P&ID, for example)
- Abbreviations, drawing conventions, and revision states vary across the package
- Someone still has to cross-check the final list against the drawing set
On a 100-drawing package, a thorough manual tag list takes a senior engineer several days. On a larger package, it is weeks. And any document revision restarts part of that process.
What AI Tag List Extraction Changes
AI tag list extraction automates the reading and extraction step so that the engineering team receives a structured, source-linked tag list without the manual reading cycle.
Novek's extraction pipeline:
- Reads each P&ID drawing visually — symbols, callouts, line designations, and equipment references
- Identifies tagged items by type: instruments (ISA-5.1), valves, equipment, piping lines
- Extracts the tag number, description, referenced line, connected equipment, and drawing location
- Deduplicates tags that appear across multiple drawings and merges their references
- Produces a structured tag list with every row linked to its source drawing page
The result is a tag list that would have taken days to build manually — completed in minutes, with every entry traceable.
What a Correct Tag List Requires
Speed alone is not enough. A usable tag list has to be:
Complete — no tags missed across the full package
Accurate — tag numbers, types, and references correctly read from the drawing
Deduplicated — the same tag appearing on multiple drawings appears once in the list, with all drawing references captured
Source-linked — every row should be verifiable against the source drawing without re-reading the entire document
Template-consistent — the output should map to the project's tag register format, not a generic export
Novek's AI tag list extraction is designed to meet all five. Engineers can open any row, click the source reference, and verify the tag against the exact P&ID location.
Tag List vs. Tag Register vs. Equipment List: What Is the Difference?
These terms are often used interchangeably on projects but have distinct meanings:
| Term | Typically contains |
|---|---|
| Tag list | All tagged items across all disciplines |
| Tag register | A curated, controlled version of the tag list, often maintained as a living document |
| Equipment list | A subset — only major equipment (vessels, pumps, compressors) |
| Instrument list | A subset — only instrumentation |
Novek can produce any of these as standalone outputs or as subsets of the full tag extraction run.
What Teams Actually Get Out of AI Tag List Extraction
Faster project starts — tag lists are typically needed early for procurement and datasheets. Getting them in hours instead of days accelerates everything that depends on them.
Fewer spreadsheet errors — the extraction is systematic. The same reading logic is applied to every drawing, every time.
Faster QA — source links mean engineers can sample-check the extracted output in minutes rather than re-reading drawings.
More packages per team — when tag extraction takes minutes instead of days, the same team can service more concurrent projects without adding headcount.
Frequently Asked Questions
Does AI tag list extraction work on scanned P&IDs?
Novek works with standard PDF-format engineering drawings. Heavily degraded or low-resolution scans may affect accuracy, but standard project PDFs work well.
What happens when a drawing revision comes in?
Revisions can be re-run through the extraction pipeline. Changed tags, added tags, and removed tags are flagged as differences against the previous extraction.
Can we customise the output columns?
Yes. The tag list output maps to the project's template — column names, field order, and attribute selection are configurable per project.
How long does the extraction actually take?
For a typical 80–100 drawing package, extraction runs in minutes. Review and spot-check by the engineering team typically takes an additional 1–2 hours for a first run.