Naming conventions for documents and parts in Onshape

svenolov_nystrom

Bask_BBU_Part_Convention.docx

This is generated by CHATGPT it is a naming convention witch make perfect sense in Onshape

https://cad.onshape.com/documents/ab4bf61e0709d5e5244f335c/w/b3a52dc94c136ef78d95a6f0/e/b785ab1e1084692b3a643469

Check 404 008.02 000 CYL 100/xL and assy -500

As a new part is generated in a part studio assign the name (ex 404 008.02 001 Plate) to the feature i the feature list and change the part name

Make a folder containing the part and sketch named 404 008.02 001 Plate. Make sure that all features coupled to this part in the said folder

CHATGPT can keep track of catalog numbers and subset numbers. Its a pity that chatgpt don't have access to Onshape documents

S1mon

I use ChatGPT all the time, but I would not trust it to keep track of numbering over time. You need a PLM system to do that or at least use the basic PLM tools in Onshape to generate part numbers and assembly numbers. I would recommend using non-significant part numbering. In fact, here's what ChatGPT says about that:

Here are ten widely-cited advantages of adopting non-significant (a.k.a. “dumb,” “surrogate,” or “random”) part numbers in a PLM environment:

1. Future-proofing the schema
   Because the number carries no meaning, you never have to revise the schema when organizations, product lines, or technologies evolve. The code that was issued in 2025 is still valid in 2035 even if your product taxonomy has changed completely.
2. Eliminating embedded-meaning errors
   Engineers can’t accidentally choose the “wrong” code just because they misunderstood a prefix or digit that was supposed to convey material, voltage, revision level, etc. Fewer misclassified parts means fewer downstream BOM, sourcing, and regulatory mistakes.
3. Simpler governance and training
   Users only need to know how to request or generate the next number—not how to decipher or build a complex string. That slashes onboarding time, desk-side support, and the length of the corporate numbering policy.
4. Automation-friendly
   Because numbers are generated sequentially (or by an algorithm), PLM, ERP, and MES systems can auto-assign them with zero human intervention—ideal for API-driven or workflow-driven part creation.
5. Unlimited scalability
   Growth never forces you to overload digit positions or invent new prefixes. Whether you add one new division or ten, the next available number is always just “N + 1.”
6. Reduced cross-functional friction
   Manufacturing, quality, service, and finance teams don’t need to learn engineering shorthand to work with the parts list; they just treat the identifier as a key. That improves data sharing across the whole digital thread.
7. Minimizing renumbering events
   With significant codes, a change to form/fit/function or a new commodity classification often forces a new part number—creating zombie parts and traceability gaps. Non-significant schemes avoid that churn.
8. Globalization & Localization neutrality
   Numbers remain language-independent and culture-neutral, preventing translation issues and unintended meanings (e.g., leading zeros in Europe, unlucky digits in some Asian markets).
9. Cleaner analytics
   Because metadata lives in controlled attributes—not encoded in the number—your reports, dashboards, and parametric searches rely on explicit fields. That improves data quality and enables richer analytics and AI/ML initiatives.
10. Consistent treatment of hardware, software, and documents
    The same assignment logic can be applied across mechanical parts, electronics, firmware, CAD files, technical publications, and even marketing assets, giving you a single, coherent ID strategy throughout the PLM backbone.