I — Datum
Capability Manifest
Complete instrument specification for the SVEND analysis platform. 164 statistical analyses, process control, measurement system analysis, lean operations, and strategy deployment. The statistics are calibrated against NIST Statistical Reference Datasets and cross-checked against R. Anything not yet shipped is marked on the row that claims it, with the month it is due.
Contents
II — Statistical Analysis Engine
164 statistical analyses spanning hypothesis testing, regression, ANOVA, reliability, survival analysis, time series, machine learning, and Bayesian methods. Hypothesis testing, regression and capability are calibrated against published reference datasets with defined tolerance bands; families outside that scope are computed but not externally calibrated. The Workbench is a stateless calculator: it holds no project state, so an analysis is reproducible from its dataset and its configuration alone.
| Capability | Specification | Status |
|---|---|---|
| Hypothesis testing | t-tests (1-sample, 2-sample, paired), z-tests, chi-square, Fisher exact, Mann-Whitney U, Wilcoxon, Kruskal-Wallis, Friedman, McNemar, Mood's median | ● |
| ANOVA | One-way, two-way, general linear model, Welch ANOVA, repeated measures, nested, Tukey/Bonferroni/Dunnett post-hoc comparisons | ● |
| Regression | Simple linear, multiple linear, polynomial, logistic, Poisson, stepwise, ridge, LASSO, partial least squares, residual diagnostics | ● |
| Reliability & survival | Weibull, lognormal, exponential fitting, Kaplan-Meier, Cox proportional hazards, accelerated life testing, MTBF/MTTF, B-life estimates | ● |
| Time series | Autocorrelation, partial autocorrelation, decomposition, trend analysis, changepoint detection (BOCPD), exponential smoothing | ● |
| Bayesian methods | Bayesian estimation, credible intervals, prior specification, posterior predictive checks, Bayesian ANOVA, Bayesian regression, model comparison (BIC, WAIC) | ● |
| Distribution analysis | Normality tests (Anderson-Darling, Shapiro-Wilk, D'Agostino), distribution fitting, probability plots, goodness-of-fit, Box-Cox transformation | ● |
| Correlation | Pearson, Spearman, Kendall, partial correlation, correlation matrix, multicollinearity diagnostics (VIF) | ● |
| Sample size & power | Power analysis for means, proportions, ANOVA, regression, equivalence/non-inferiority, acceptance sampling (AQL/LTPD) | ● |
| Multivariate | PCA, factor analysis, discriminant analysis, cluster analysis, Hotelling T², multivariate capability | ● |
| Machine learning | Gradient boosting (XGBoost, LightGBM), random forest, regularised regression, model comparison, feature importance, anomaly detection | ● |
Tolerance bands: p-values ±0.005, correlation coefficients ±0.02, test statistics ±0.01. Checked on every build.
III — Statistical Process Control
Classical and Bayesian control charts with automatic rule-based detection. Process capability indices with frequentist and Bayesian estimation. Measurement system analysis for validation before capability studies.
| Capability | Specification | Status |
|---|---|---|
| Variables control charts | I-MR (individuals & moving range), X-bar/R, X-bar/S, zone charts, with automatic subgroup sizing | ● |
| Attributes control charts | p (proportion defective), np (count defective), c (defects per unit), u (defects per unit variable size) | ● |
| Advanced control charts | CUSUM (cumulative sum), EWMA (exponentially weighted moving average), Bayesian control charts with posterior probability of shift | ● |
| Nelson rules | All 8 Nelson rules with automatic detection, configurable rule selection, out-of-control point annotation | ● |
| Process capability (frequentist) | Cp, Cpk, Pp, Ppk, Cpm, sigma level, DPMO, yield (FPY, RTY), confidence intervals | ● |
| Process capability (Bayesian) | Bayesian Cpk with posterior distribution, P(Cpk > 1.33), credible intervals, prior specification, small-sample robust | ● |
| Gage R&R | Crossed design by ANOVA: %GRR, %Contribution, ndc (number of distinct categories), operator-by-part interaction. Gage linearity and bias runs here too. Nested (destructive) Gage R&R is not available — the study bench is section IV | ● |
| Changepoint detection | Bayesian online changepoint detection (BOCPD), evidence accumulation, shift probability estimation | ● |
Capability indices validated within ±0.05 of reference values. Ref: AIAG SPC Manual, 2nd Ed.
IV — Measurement Systems
A gage study is planned before it is measured, so it does not fit the stateless workbench in section II and has a bench of its own. Ten parts, three appraisers, three trials, randomized — issued as a run sheet, filled in on the floor hours or weeks later, then judged whole. How the study bench works →
| Capability | Specification | Status |
|---|---|---|
| Study plan | Parts as labels rather than a count, named appraisers, trial count, characteristic and units, optional specification limits. Up to 40 parts, 10 appraisers, 6 trials and 600 readings | ● |
| Randomized run sheet | A fresh permutation for every appraiser and every trial, generated from a seed recorded with the study so a reprinted sheet matches a half-worked one. Re-planning over recorded readings is refused | ● |
| Keyboard-wedge capture | Any digital gage or receiver presenting as a keyboard: focus opens on the first unmeasured row, Enter or Tab advances by run rather than by DOM order, and text that is not a reading holds the row. Input contract → | ● |
| Tamper-evident readings | Each submission is recorded as an act — who submitted what, against which rows, when — and those acts are hash-chained. A correction is a later event; the study declaration is deliberately outside the chain | ● |
| Instrument register | A typed gage name resolves to a device record, so a study names an instrument rather than a string | ● |
| Judgment | The completed study is judged through the same engine door as every other analysis. A part-worked sheet is refused, naming what is missing — a crossed study is judged whole | ● |
| Nested Gage R&R | Destructive testing, where no part can be measured twice — each appraiser gets its own parts. Available on the study bench | ● |
| Gage stability | Repeated measurement of a reference part over time as a dedicated study. Available | ● |
| Type 1 gage study | Cg and Cgk against a reference part and a declared tolerance. Runs in the Analysis Workbench on readings you already have, rather than on this bench — a type 1 study measures one part repeatedly and needs no run sheet issued across appraisers | ● |
| Identified device capture | Readings carrying the instrument that produced them, rather than an operator-declared gage name. Specified against the MobileCollect EVO serial interface; requires hardware validation and is published as a specification, not shipped | ○ |
| SVEND Device Trust System | The instrument’s own record rather than the study’s: a device register, calibration records carrying as-found values per check point, and reverse traceability as a query rather than an investigation. Team tier. In build for November 2026 — not yet available | ○ |
The bench above is available from Pro; the Device Trust System is Team. The free Gage R&R calculator needs no account and runs the same crossed ANOVA on readings you bring. Ref: AIAG MSA Manual, 4th Ed.
V — Design of Experiments
Both halves work today. Declare your factors and their real settings, choose a design, and get back a coded matrix and a randomized run sheet to carry to the line. Type the results in when they come back and the fit runs through the same engine as everything else in section II.
| Capability | Specification | Status |
|---|---|---|
| Factorial analysis | Main effects and interactions via ANOVA and general linear model, two-way and nested designs, post-hoc comparison, residual diagnostics | ● |
| Response surface fitting | Polynomial regression, curvature and lack-of-fit testing, multiple regression with interaction terms, model comparison | ● |
| Power & sample size | Power analysis for factorial designs, runs required per group at a target effect size, computed power curve across sample sizes | ● |
| Design generation | Full factorial, fractional factorial, Plackett-Burman, definitive screening, central composite, Box-Behnken and Taguchi designs, with a coded matrix and a randomized run sheet in the operator's own units. Mixture and split-plot generation are not among them; split-plot analysis is | ● |
Available from Pro. The full design reference covers the seven families, the run-sheet contract and the boundaries. Ref: Montgomery, Design and Analysis of Experiments, 8th Ed.
VI — Lean Operations
Value stream mapping, line balancing, OEE, takt time, kanban sizing, and a set of free operations calculators. Map current state, identify waste (DOWNTIME), simulate the line as a discrete-event model, and carry kaizen bursts forward into strategy.
| Capability | Specification | Status |
|---|---|---|
| Value stream mapping | Current state / future state pairing, process box editor, inventory triangles, two-level lead time ladder, discrete-event simulation of the mapped line, overhead floor layout | ● |
| Line balance & simulation | Cycle time analysis, operator balance charts, line efficiency, bottleneck identification, what-if simulation | ● |
| OEE | Availability, performance, quality breakdown, six big losses classification, OEE trending, world-class benchmarking | ● |
| Takt time | Available time, customer demand, takt calculation, pitch, planned cycle time, efficiency ratio | ● |
| Kanban sizing | Kanban quantity calculation, safety factor, replenishment lead time, container sizing, signal kanban | ● |
| Free calculators | 14 calculators, no account required: Cpk, Bayesian Cpk, control chart, Gage R&R, sigma level, FPY/RTY, sample size, OEE, takt time, Pareto, kanban cards, FMEA RPN, ISO 9001 audit checklist, ISO document creator | ● |
| Kaizen bursts | Bursts placed on the map, waste classification, lot sizing and SMED analysis per step, savings estimated from the step's own data | ● |
| Kaizen charters into a vandrebok | An approved burst is promoted to a chartered entry in the practitioner's vandrebok, carrying its charter and the map and burst it came from. Promoting the same burst twice returns the same entry | ● |
Free tools available at svend.ai/tools — no account required.
VII — The Vandrebok
A practitioner's book of improvement work — a running, attested record of what you have actually done, rather than a plan for what you intend. An entry arrives by promotion from a value stream map, carries the map and burst that produced it, and is measured against the map rather than against an estimate. It is an output of value stream mapping, not a peer to it: current state, future state, waste register, review, then the book. What a vandrebok is, and how it differs from hoshin kanri →
| Capability | Specification | Status |
|---|---|---|
| Entries | Chartered improvement work: title, charter, class and type, year, and the value stream it belongs to | ● |
| Provenance | Which map and which kaizen burst produced the entry, recorded on the entry itself and used as its identity | ● |
| Action items | The work inside an entry, owned and dated | ● |
| Commitments | Who has committed to which entry, with over-commitment detection across a facilitator's whole load | ● |
| Templates | Start an entry from a standard improvement pattern rather than a blank charter | ● |
| Sites & people | Multi-site organization model, per-site access control, employee assignment to entries | ● |
| The book screen | One view of everything in your vandrebok, across value streams and years. In build for August 2026 — not yet available | ○ |
Available from Pro. There is deliberately no savings estimator and no X-matrix — value is claimed against a measure on the map, not estimated in the book.
VIII — Platform
Multi-tenant architecture with tenant isolation enforced at the database level by Postgres row-level security, statistical results calibrated against externally certified reference values, and a public record of the result.
| Capability | Specification | Status |
|---|---|---|
| Managed datasets | Upload once into a managed library, clean and transform on a dedicated screen, then pull the finished dataset into any analysis. In build for August 2026 — not yet available | ○ |
| Team collaboration | Shared work across a team — analysis sessions and improvement entries visible to the people who own them together, rather than to one account. Deliberately moved out to November 2026 rather than shipped thin: it is the feature most likely to be built as an activity feed nobody reads, and the record-and-provenance work this platform is built on gives it a better shape than that. In build for November 2026 — not yet available | ○ |
| Audit trail | Tamper-evident hash chaining ships for gage studies, where every reading submission is recorded as an act and chained (section IV). It does not yet cover workbench analyses. The claim stays narrow on purpose: a chain shows the covered acts have not been altered since they were chained, and attests nothing before its first entry. In build for August 2026 for analytical entries | ○ |
| Data export | CSV, Excel and JSON export for any analysis. Printable report per analysis. 90-day retention after cancellation | ● |
| Security | Encryption at rest and in transit. Postgres row-level security for tenant isolation. Argon2 password hashing, TOTP multi-factor authentication, session management, sign-in rate limiting | ● |
| Multi-tenant | Multi-plant / multi-site model, per-site access control, tenant isolation enforced by Postgres row-level security rather than by application code | ● |
| Calibration system | NIST Statistical Reference Datasets (14 certified sets, 15 significant digits) · R cross-check: control charts and capability against qcc 28/28, hypothesis tests and regression against base R 40/40 · 149 golden cases in the statistics library · defined tolerance bands | ● |
Team collaboration is the Team tier. Everything else on this page is Free or Pro. Deep customisation — your own domain namespace, your own branding, a bespoke deployment — is a conversation, not a tier: see pricing.