Python library for mechanical engineers to help with statistical tolerancing analysis and design.
https://pypi.org/project/dimstack/
import dimstack as ds
ds.display.mode("rich")
k = 0.25
target_process_sigma = 6
stdev = 0.036 / target_process_sigma
m1 = ds.dim.Statistical(
nom=208,
tol=ds.tol.SymmetricBilateral(0.036),
distribution=ds.dist.Normal(208 + k * target_process_sigma * stdev, stdev),
target_process_sigma=target_process_sigma,
name="a",
desc="Shaft",
)
m2 = ds.dim.Statistical(
nom=-1.75,
tol=ds.tol.UnequalBilateral(0, 0.06),
target_process_sigma=3,
name="b",
desc="Retainer ring",
)
m3 = ds.dim.Statistical(nom=-23, tol=ds.tol.UnequalBilateral(0, 0.12), target_process_sigma=3, name="c", desc="Bearing")
m4 = ds.dim.Statistical(
nom=20,
tol=ds.tol.SymmetricBilateral(0.026),
target_process_sigma=3,
name="d",
desc="Bearing Sleeve",
)
m5 = ds.dim.Statistical(nom=-200, tol=ds.tol.SymmetricBilateral(0.145), target_process_sigma=3, name="e", desc="Case")
m6 = ds.dim.Basic(
nom=20,
tol=ds.tol.SymmetricBilateral(0.026),
# target_process_sigma=3,
name="f",
desc="Bearing Sleeve",
)
m7 = ds.dim.Statistical(nom=-23, tol=ds.tol.UnequalBilateral(0, 0.12), target_process_sigma=3, name="g", desc="Bearing")
items = [m1, m2, m3, m4, m5, m6, m7]
stack = ds.Stack(name="stacks on stacks", dims=items)
stack.show()
stack.Closed.show()
stack.WC.show()
stack.RSS.show()
stack.MRSS.show()
designed_for = stack.SixSigma(at=4.5)
designed_for.show()
spec = ds.Spec("stack spec", "", dim=designed_for, LL=0.05, UL=0.8)
spec.show()
ds.plot.StackPlot().add(stack).add(stack.RSS).show()
Returns:
STACK: stacks on stacks
┏━━━━┳━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━┳━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━┓
┃ ID ┃ Name ┃ Desc. ┃ dir ┃ Nom. ┃ Tol. ┃ Sens. (a) ┃ Rel. Bounds ┃
┡━━━━╇━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━╇━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━┩
│ 0 │ a │ Shaft │ + │ 208.0 │ ± 0.036 │ 1 │ [207.964, 208.036] │
│ 1 │ b │ Retainer ring │ - │ 1.75 │ + 0.06 / + 0 │ 1 │ [1.75, 1.81] │
│ 2 │ c │ Bearing │ - │ 23.0 │ + 0.12 / + 0 │ 1 │ [23, 23.12] │
│ 3 │ d │ Bearing Sleeve │ + │ 20.0 │ ± 0.026 │ 1 │ [19.974, 20.026] │
│ 4 │ e │ Case │ - │ 200.0 │ ± 0.145 │ 1 │ [199.855, 200.145] │
│ 5 │ f │ Bearing Sleeve │ + │ 20.0 │ ± 0.026 │ 1 │ [19.974, 20.026] │
│ 6 │ g │ Bearing │ - │ 23.0 │ + 0.12 / + 0 │ 1 │ [23, 23.12] │
└────┴──────┴────────────────┴─────┴───────┴────────────────┴───────────┴────────────────────┘
Dimension: stacks on stacks - Closed Analysis -
┏━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━┳━━━━━━┳━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
┃ ID ┃ Name ┃ Description ┃ dir ┃ Nom. ┃ Tol. ┃ Sens. (a) ┃ Relative Bounds ┃
┡━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━╇━━━━━━╇━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
│ 7 │ stacks on stacks - Closed Analysis │ │ + │ 0.25 │ + 0.233 / - 0.533 │ 1 │ [-0.283, 0.483] │
└────┴────────────────────────────────────┴─────────────┴─────┴──────┴───────────────────┴───────────┴─────────────────┘
Dimension: stacks on stacks - WC Analysis -
┏━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━┳━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━┓
┃ ID ┃ Name ┃ Description ┃ dir ┃ Nom. ┃ Tol. ┃ Sens. (a) ┃ Relative Bounds ┃
┡━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━╇━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━┩
│ 8 │ stacks on stacks - WC Analysis │ │ + │ 0.1 │ ± 0.383 │ 1 │ [-0.283, 0.483] │
└────┴────────────────────────────────┴─────────────┴─────┴──────┴────────────────┴───────────┴─────────────────┘
WARNING:root:Converting Basic Dim. (5: f Bearing Sleeve +20 ± 0.026) to Statistical Dim.
DIMENSION: stacks on stacks - RSS Analysis - (assuming inputs with Normal Distribution & ± 3σ)
┏━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━┳━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓
┃ ID ┃ Desc. ┃ dir ┃ Nom. ┃ Tol. ┃ Sens. (a) ┃ Rel. Bounds ┃
┡━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━╇━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩
│ 10 │ (assuming inputs with Normal Distribution & ± 3σ) │ + │ 0.1 │ ± 0.17825 │ 1 │ [-0.07825, 0.27825] │
└────┴───────────────────────────────────────────────────┴─────┴──────┴────────────────┴───────────┴─────────────────────┘
WARNING:root:Converting Basic Dim. (5: f Bearing Sleeve +20 ± 0.026) to Statistical Dim.
DIMENSION: stacks on stacks - MRSS Analysis - (assuming inputs with Normal Distribution & ± 3σ)
┏━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━┳━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓
┃ ID ┃ Desc. ┃ dir ┃ Nom. ┃ Tol. ┃ Sens. (a) ┃ Rel. Bounds ┃
┡━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━╇━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩
│ 12 │ (assuming inputs with Normal Distribution & ± 3σ) │ + │ 0.1 │ ± 0.24046 │ 1 │ [-0.14046, 0.34046] │
└────┴───────────────────────────────────────────────────┴─────┴──────┴────────────────┴───────────┴─────────────────────┘
WARNING:root:Converting Basic Dim. (5: f Bearing Sleeve +20 ± 0.026) to Statistical Dim.
DIMENSION: stacks on stacks - '6 Sigma' Analysis - (assuming inputs with Normal Distribution)
┏━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━┳━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┓
┃ ID ┃ Desc. ┃ dir ┃ Nom. ┃ Tol. ┃ Sens. (a) ┃ Rel. Bounds ┃
┡━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━╇━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━━━━━╇━━━━━━━━━━━━━━━━┩
│ 14 │ (assuming inputs with Normal Distribution) │ + │ 0.1 │ ± 0.036 │ 1 │ [0.064, 0.136] │
└────┴────────────────────────────────────────────┴─────┴──────┴────────────────┴───────────┴────────────────┘
SPEC: stack spec
┏━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━┓
┃ Desc. ┃ Dimension ┃ Median ┃ Spec. Limits ┃ Yield Prob. ┃ Reject PPM ┃
┡━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━┩
│ │ 14: stacks on stacks - '6 Sigma' Analysis (assuming inputs │ 0.425 │ [0.05, 0.8] │ 99.99999998 │ 0.0 │
│ │ with Normal Distribution) +0.1 ± 0.036 @ ± 4.5σ & k=0.0 │ │ │ │ │
└───────┴──────────────────────────────────────────────────────────────┴────────┴──────────────┴─────────────┴────────────┘
dimstack works great as a library in a python script, in REPL, or in JupyterLab.
Demo usage in a JupyterLite Lab
Demo usage in a JupyterLite REPL:
Embed in your site:
<iframe
src="https://phcreery.github.io/dimstack-demo/repl/index.html?kernel=python&toolbar=1&code=%pip%20install%20-q%20dimstack%0Aimport%20dimstack%20as%20ds"
width="100%"
height="100%"
></iframe>
pdm run test
OR
python -m unittest discover .\tests\
pdm run docs
pdm run deploydocs
First bump version in pyproject.toml, then
pdm build
pdm publish --no-build
See https://github.com/phcreery/dimstack-demo
%pip install -q dimstack