Linear Tolerance Stack Evidence
Bound an authored add/subtract assembly dimension chain with asymmetric component limits, integer copy counts and exact extreme witnesses.
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How to use Linear Tolerance Stack Evidence
Enter each component's closed dimension limits, copy count and sign in one common unit. Select all contributing endpoints for the lower and upper chain totals, then compare that entire interval with your entered functional bounds while retaining both simultaneous witnesses.
- Use the example as the schema; replace its labels and entered model assumptions.
- Enter each component's closed dimension limits, copy count and sign in one common unit. Select all contributing endpoints for the lower and upper chain totals, then compare that entire interval with your entered functional bounds while retaining both simultaneous witnesses.
- Calculate, inspect the complete witnesses and limitations, then copy or download the JSON report.
Good to know
- Up to 100 terms; each nonnegative component endpoint up to 1,000,000, quantity 1–1,000 and signed target limits within 1 billion. Six-place decimal strings; component and target minima cannot exceed maxima.
- Only independent box-bounded linear one-dimensional variation. No statistical/RSS/probability result, geometric correlation, angular error, GD&T/CAD, standard-fit selection, compliance, manufactured-part certification or structural/safety guarantee.
- Local calculation with no upload, input persistence or outside lookup. Model JSON is limited to 30,000 characters and 10,000 values. Decimal quantities are strings with up to six places; count fields use plain JSON integers. Exact fractions are capped at 8,192 bits. The complete JSON output is limited to 1,000,000 characters; approximate numbers preserve their stored values. Unsupported states fail explicitly.
Common questions
Is fully-within a physical assembly approval?
It only means the exact interval from the entered one-dimensional model lies within the entered target interval. Missing geometric constraints, measurement errors, part orientation and other real effects are outside that model. The endpoint witnesses are arithmetic evidence, not certification or a probability of fit.
Are my model inputs saved or sent to a server?
No. This model runs in the current browser tab and creates a local JSON download. It does not save your input or call an external data service.
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