Deterministic engine · same inputs, same result

Turn industrial inputs into defensible decisions.

Deterministic calculators for engineering, machining, quality and costing. See every input, assumption, formula and warning before you act. Client-side — your data never leaves your browser.

No login to try · No data uploaded · Reproducible by seed
Tolerance Stack-Up · live computing
Spec ± mm
Worst-case
RSS
Monte Carlo
Live preview — full Monte Carlo, Cpk & PDF in the calculator.
394
automated tests, all passing
Decimal
full-precision engine, no float drift
100%
client-side — nothing uploaded
Seeded
reproducible Monte Carlo
Start from your decision

What are you trying to decide?

Different roles run the numbers for different reasons. Pick the question — we route you to the right calculator and the right evidence.

Flagship

Statistical Tolerance Stack-Up

The hardest everyday question on the floor — will the assembled dimensions stay within spec? Three methods, one deterministic engine.

Engineering preview · not for production approval

Three methods, one answer you can trace

Worst-case for the safe bound, RSS for the statistical estimate, seeded Monte Carlo for the distribution — compared side by side, with the contributor that drives the most variation called out.

  • Per-part distribution: normal, uniform, truncated-normal, triangular
  • Real sample histogram — not a decorative bell curve
  • Predicted Cpk & PPM with a 95% confidence interval
  • Deterministic: same inputs + seed + engine version = same report
  • Save / load projects, CSV import, revision compare, PDF trace
Open the calculator
Worst-case±0.1150 mm
RSS±0.0687 mm
Monte Carlo (n=10 000)±0.0671 mm
Predicted Cpk2.18
Top contributorSpacer Width · 53%
VerdictPredicted in spec
The set

Cost, quality and risk — one deterministic engine

Every tool shares the same principles: structured inputs, full-precision math, visible assumptions, and a result you can defend.

$

Cost & Quoting

Know the real number before you commit a price or a hire.

  • SC-010 True labor cost
  • SC-012 Quote pricing & margin
σ

Quality & Capability

Predicted capability from tolerances — flagged as prediction.

  • SC-008 Tolerance stack-up
  • SC-001 Weld thickness
!

Risk & Review

See the contributor, the margin and the warning before it costs you.

  • Pareto variation contribution
  • What-if sensitivity, recomputed
Method

How a SectorCalc result is built

A result is only useful if you can defend it. Every report carries four layers — so a reviewer can follow the number from input to decision.

01 · DECISION
Recommended action

Primary result, pass / warning / fail, and the operational or commercial impact — stated up front.

02 · CALCULATION
Inputs & formula

Every input with units, derived values, the formula used and the assumptions made. Nothing hidden.

03 · VALIDATION
Checks & warnings

Input consistency checks, outlier warnings, the applicable standard and edition, and the engine version.

04 · REPORT
Audit trail

Executive result, detailed calculation, deviations, deterministic hashes and a PDF / shareable record.

Evidence

What a report actually looks like

Not a black-box number. A traceable record — the kind you can hand to a reviewer or attach to a design file.

SC-008 · Predicted Analysis

Calc ID SC008-7A3F1C9E (from inputs)
Engine SC008-2026.07-formula-v1.0.0+dist
Input hash 7a3f1c9e · Output hash 4d8b2e61
Method worst + RSS + seeded MC (n=10 000)
Generate your own →
Worst-case±0.1150 mm
RSS±0.0687 mm
Monte Carlo±0.0671 mm
Predicted Cpk2.18
Predicted PPM (95% CI)3 · 0–11
Top contributorSpacer Width · 53%
✓ Predicted in spec — verify with measured data before release
What you get

Built to be defended, not just displayed

We don't claim to replace measured data or a licensed engineer. We claim to make the calculation transparent, repeatable and reviewable.

Every input visible

Structured, unit-aware inputs with tooltips that state the assumption — no hidden defaults.

fx
The formula shown

The method and the math are stated in the report, so a reviewer can follow the derivation.

!
Warnings flagged

Out-of-range inputs, thin margins and out-of-spec predictions are called out, not buried.

Reproducible record

Deterministic seed + engine version + hashes mean the same inputs reproduce the same report.

Standards & honesty

What we reference — and what we are not

Trust comes from stating limits as clearly as capabilities.

Referenced methodology
ISO 286-1 — tolerance grades (reference for deviations)
ASME Y14.5 — statistical tolerancing context (RSS)
AIAG SPC — Cpk definition (model-derived here, not measured)
AWS D1.1 / EN ISO 2553 — weld sizing context
Engine — SC008-2026.07-formula-v1.0.0+dist · 394 tests
How to read our results
Validated against closed-form worst-case / RSS invariants
Calculated under stated distribution assumptions
Applicable within 1D linear stack-ups
Predicted capability — not observed process capability
Reproducible from inputs + seed + engine version
Known limitations (stated on purpose)

1D linear stacks only. Per-part sigma is derived from the tolerance (no measured-process input yet). No correlation model between dimensions yet. Results are predicted from drawing tolerances — an engineering preview to support a decision, not a substitute for measured SPC or a licensed engineer's sign-off, and not for production approval on their own.

Pricing

Pay with credits. Only for what you use.

No subscription. Try every tool free first; open a premium calculation with credits valid for 12 months. Heavy users save with big packs; light users pay little.

See credit pricing

Stop guessing. Start defending your numbers.

Run a tolerance stack-up in your browser — no login, no upload, reproducible by seed.

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