Run thousands of virtual builds to see the true distribution of your assembly outcome. The engine respects bilateral tolerances, loop direction, and sigma capability to report mean, σ, mean ± 3σ, observed min/max, and predicted yield vs. your spec—fully reproducible via seed and adjustable sample size. Unlike RSS (which assumes linearity and symmetric, normal tolerances), Monte Carlo propagates your actual distributions and non-linear interactions, exposing tail risk and real pass/fail probability.
Create a polished, audit-ready PDF in one click. Each report captures project headers (title, analyst, date), objective, conclusions/recommendations, and full traceability (report ID, app version, seed, sample count, spec settings). It documents inputs (loop direction, nominal, bilateral/asymmetric tolerances, sigma level) and outputs (mean, σ, mean ± 3σ, observed min/max, predicted yield), with pass/fail summaries plus results and input tables. Share a clear, reproducible record stakeholders can trust.
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