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The complete statistical toolkit for reliability engineers, quality engineers, and data analysts. Powerful as Minitab — half the price.

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VinReliability™ — Process Capability Analysis
Reliability
SPC & Quality
DOE
Regression
ANOVA
Time Series
Process Capability — Shaft Diameter (mm)
05 1015 20 24.8524.90 24.9525.00 25.0525.10 25.15 Shaft Diameter (mm) LSL USL Target x̄ = 25.002
Capability Indices
Cp 1.67
Cpk 1.54
Pp 1.61
Ppk 1.48
Sigma 4.62σ
PPM 3.4
Interpretation
Cpk = 1.54 exceeds 1.33 threshold — process is capable Process centered near target (25.002 vs 25.000 mm) Est. 3.4 PPM defective (beyond ±4.6σ) ✓ Process meets Six Sigma quality requirements
VinReliability™ — Box-Cox Transformation
Reliability
SPC & Quality
DOE
Regression
ANOVA
Time Series
Before — Right-Skewed (Skew = 2.14)
✗ S-W p = 0.003
After — Normal (λ = 0.27)
✓ S-W p = 0.412
Box-Cox Results
λ 0.27
95% CI 0.12–0.41
Skew (before) 2.14
Skew (after) 0.08
S-W before p = 0.003
S-W after p = 0.412
Interpretation
λ = 0.27 (near cube root transform) Transformed data passes Shapiro-Wilk (p = 0.412) Skewness reduced from 2.14 to 0.08 ✓ Data now suitable for parametric analysis

What Sets VinReliability™ Apart

More than just numbers — actionable insights for better engineering decisions

Interactive Plots for Presentations

Create stunning interactive charts — zoom, pan, hover for details. Export as HTML to embed in presentations that impress stakeholders and drive decisions.

Publication-Ready Vector Graphics

Export every chart as SVG or PDF — crisp at any resolution. Perfect for journal submissions, technical reports, and regulatory documentation.

Built-in Interpretations & Decision Support

Every analysis includes plain-English interpretations. Understand p-values, confidence intervals, and what they mean for your engineering decisions — no statistics PhD required.

One-Click PDF & Excel Reports

Generate comprehensive PDF reports with all plots, tables, and interpretations in a single click. Export to Excel with formatted sheets — ready to share with your team or attach to quality audits.

Animated GIFs for Trend Visualization

Generate animated GIFs that bring your data to life — watch trends evolve, distributions shift, and patterns emerge. Far more insightful than staring at static plots.

Validation Documentation (IQ/OQ/PQ)

Ships with comprehensive validation documents — Validation Master Plan, Installation Qualification, Operational Qualification, and Requirements Traceability Matrix. Ready for regulated environments and quality audits.

Thorough Help with Worked Examples

Every analysis tool includes detailed help with numerical examples using built-in sample data. Learn how to perform the analysis, interpret results, and make confident decisions — step by step.

Design of Experiments

Full and fractional factorial designs, response surface methodology, and Taguchi arrays. Instantly see main effects, interactions, and the optimal operating conditions — with automated analysis and visualization.

2³ Factorial DOE — Injection Molding Optimization
Main Effects
LowHigh Temp Psi
Interaction Plot
LowHigh High Psi Low Psi
Pareto of Effects
p=0.05 A AB B C
Response Surface
Temperature (°C) Pressure (psi) Optimal
R² = 94.7% | R²(adj) = 92.1% • Factor A (Temp) is dominant (p < 0.001) • Optimal: 185°C, 42 psi → Yield 97.3%
  • Full & fractional factorial designs
  • Response surface methodology (CCD, Box-Behnken)
  • Taguchi & D-optimal designs
  • Main effects & interaction plots
  • Pareto of standardized effects
  • Contour & surface plots

Time Series & Forecasting

ARIMA, SARIMA, and exponential smoothing models with automated order selection. Watch historical trends extend into forecasts with confidence intervals — all with plain-English model diagnostics.

ARIMA(2,1,1) Forecast — Monthly Revenue
$0$50K $100K$150K JanFeb MarApr MayJun JulAug SepOct NovDec Jan 2025 — 2026 Today +12% next quarter
ARIMA(2,1,1) selected via AICc = 312.4 • Ljung-Box p = 0.42 — residuals are white noise • Forecast: $148K ± $12K (95% CI)
  • ARIMA / SARIMA forecasting
  • Exponential smoothing (Holt-Winters)
  • Trend decomposition & ACF/PACF
  • PCA & cluster analysis
  • Automated model order selection (AICc/BIC)
  • Forecast confidence intervals

Quality & SPC

Complete statistical process control toolkit including control charts, process capability analysis, measurement system analysis, and acceptance sampling — with automated rule-based interpretation.

X̄-R Control Chart — Bearing Diameter (mm)
12 34 56 78 910 1112 Subgroup UCL CL LCL Rule 1 X̄ = 25.003 R̄ = 0.042 Cp = 1.45 Cpk = 1.38
1 of 12 points beyond UCL (Rule 1 violation) • Cpk = 1.38 > 1.33 — process is capable • ⚠ Investigate subgroup 8 for assignable cause
  • Control charts: X̄-R, X̄-S, I-MR, P, NP, C, U
  • Process capability: Cp, Cpk, Pp, Ppk, Cpm
  • Pareto charts & tolerance intervals
  • Gage R&R / MSA (crossed & nested)
  • Acceptance sampling plans
  • Nelson & Western Electric rules

Statistics & Hypothesis Testing

Comprehensive statistical testing suite from basic descriptive statistics to advanced nonparametric methods — with automated assumption checking and plain-English interpretation of every result.

One-Way ANOVA — Treatment Comparison
025 5075 100 Group A Group B Group C ** n.s. F(2,27) = 14.3 p = 0.0001
F(2,27) = 14.3, p < 0.001 — significant difference • Post-hoc: A vs B (p = 0.0003), B vs C (p = 0.31) • ✓ Group B and C outperform Group A
  • Descriptive statistics & normality tests
  • One-sample, two-sample & paired t-tests
  • ANOVA (one-way, two-way, general linear model)
  • Chi-square & proportion tests
  • Nonparametric tests (Mann-Whitney, Kruskal-Wallis)
  • Equivalence & non-inferiority testing

ANOVA & General Linear Model

Complete analysis of variance suite — from one-way ANOVA to general linear models with covariates, mixed effects, and LS-Means. Automated assumption checks, post-hoc tests, and effect size reporting for balanced and unbalanced designs.

GLM ANOVA — Catalyst Yield by Temperature × Pressure
LS-Means Comparison
60 75 90 105 Low-Low Low-Hi Hi-Low Hi-Hi ***
ANOVA Table
SourceDFFp-value
Temperature142.8<0.001
Pressure118.3<0.001
Temp × Press17.60.008
Error36——
R²(adj) = 0.891 η²p = 0.54
Temperature × Pressure interaction significant (p = 0.008) • Tukey HSD: Hi-Hi > Low-Low (p < 0.001, d = 2.1) • ✓ Optimal: High Temp + High Pressure → Yield 102.3%
  • One-Way & Two-Way ANOVA
  • General Linear Model (GLM) with covariates
  • Kruskal-Wallis & Friedman (nonparametric)
  • Mixed Effects Models (random & nested)
  • LS-Means with pairwise comparisons
  • Post-hoc: Tukey, Bonferroni, Games-Howell
  • Effect sizes (η², ω², Cohen’s d/f)
  • Assumption checks (Levene, Shapiro-Wilk)

Multivariate Regression

Multiple regression, response surface, and nonlinear curve fitting — with automated variable selection, VIF diagnostics, partial regression plots, and model comparison tools built in.

Multiple Regression — Yield = f(Temp, Pressure, Catalyst, Time)
Partial Regression: Yield | others vs Temp | others −3−1 135 −3−1 13 Standardized Coefficients (β*) 0 −0.5 0.5 1.0 Temp 0.72*** Pressure 0.48** Catalyst 0.31* Time −0.35** T×P 0.22* R²(adj) = 0.927 F(5,24) = 82.4, p < 0.001 VIF max = 2.3 (no multicollinearity)
R²(adj) = 0.927 — 4 predictors explain 92.7% of yield • VIF all < 5, no multicollinearity detected • ✓ Temperature is dominant predictor (β* = 0.72)
  • Multiple & polynomial regression
  • Nonlinear curve fitting (50+ models)
  • Best subsets & stepwise selection
  • VIF & collinearity diagnostics
  • Partial regression & residual plots
  • Response surface regression

Reliability & Survival Analysis

Industry-standard reliability engineering toolkit with Weibull analysis, system reliability modeling (series, parallel, k-of-n), accelerated life testing, and warranty prediction — supporting censored data and 15+ distributions.

Kaplan-Meier Survival — Component Life (hours)
0.00.25 0.500.75 1.00 02K 4K6K 8K Time (hours) Median = 4,800 hr
Median survival = 4,800 hr (95% CI: 4,200 – 5,500) • 5 censored observations out of 30 total • 75% survival probability at 2,500 hours
  • Weibull analysis & Kaplan-Meier estimation
  • System reliability (Series, Parallel, k-of-n, Complex)
  • Accelerated life testing (ALT / HALT)
  • Competing risks & stress-strength analysis
  • Distribution fitting (15+ distributions)
  • Warranty prediction & spare parts planning
  • Right, left & interval censored data

Weibull Analysis

Industry-standard Weibull analysis with maximum likelihood and rank regression estimation, bathtub curve visualization, and B-life calculations. Supports right, left, and interval censored data with confidence bounds on all parameters.

Weibull Analysis — Motor Winding Life (hours)
Probability Plot
1% 5% 10% 25% 50% 2K6K 10K15K Time (hours) η = 12.5K
Bathtub Curve (Hazard Rate)
Operating Time Infant Useful Life Wear-out Current
β = 2.8, η = 12,500 hr → Wear-out failure mode • B10 Life = 6,800 hr | R(8,000) = 92.4% • ⚠ Schedule preventive maintenance before 10,000 hrs
  • 2-parameter & 3-parameter Weibull
  • Maximum likelihood & rank regression
  • Probability plots with confidence bounds
  • Bathtub curve & hazard rate visualization
  • B-life calculations (B1, B10, B50)
  • Mixed Weibull for multi-mode failures
  • Right, left & interval censored data

System Reliability Modeling

Build complex system reliability block diagrams with series, parallel, k-of-n, and standby configurations. Calculate system reliability, availability, and identify critical components — with real-time visual feedback as you adjust parameters.

System Reliability — Industrial Pump Station (3-of-5)
Pump 1 R = 0.96 ACTIVE Pump 2 R = 0.94 ACTIVE Pump 3 R = 0.95 ACTIVE Pump 4 R = 0.93 STANDBY Pump 5 R = 0.91 STANDBY 3-of-5 Required k-of-n Redundancy Rsys = 0.9987 Active + Standby
3-of-5 k-of-n with 2 standby pumps → Rsys = 0.9987 • Pump 5 is most critical (lowest individual R = 0.91) • ✓ System exceeds 99.8% reliability target
  • Series, parallel & k-of-n configurations
  • Active & standby redundancy
  • Complex block diagram builder
  • Component importance measures
  • System availability & MTBF
  • Monte Carlo simulation

How VinReliability™ Compares

All the power. A fraction of the price.

Feature VinReliability™ Minitab
Annual Price $999/yr $1,610/yr
Monthly Option $99/mo Not available
Descriptive & Hypothesis Tests ✓ ✓
Regression & GLM ✓ ✓
ANOVA (One-Way, Two-Way, GLM) ✓ ✓
Control Charts (SPC) ✓ ✓
Process Capability (Cp/Cpk/Pp/Ppk) ✓ ✓
DOE (Factorial, RSM, Taguchi) ✓ ✓
Gage R&R / MSA ✓ ✓
Weibull & Reliability ✓ ✓
ARIMA Forecasting ✓ ✓
Machine Learning (Random Forest) ✓ ✓
Interactive HTML Plots ✓ ✗
Built-in Interpretations ✓ ✗
Competing Risks Analysis ✓ ✗
Stress-Strength Interference ✓ ✗
Recurrent Events (Repairable Systems) ✓ ✗
Multi-Distribution Fitter (15+) ✓ Limited
One-Click PDF & Excel Reports ✓ Limited
Animated GIF Trend Visualization ✓ ✗
Help with Worked Numerical Examples ✓ Limited
System Reliability (Series, Parallel, k-of-n) ✓ ✗
Validation Documentation (VMP, IQ, OQ, RTM) ✓ ✗
Save $611 per year compared to Minitab

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  • Free updates
  • Email support
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Best Value

Annual

$999/yr

Save $189 vs monthly — just $2.74/day

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  • Built-in interpretations
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Volume Discounts

Team (5 seats) $4,499/yr — 10% off
Department (11 seats) $9,999/yr — 10% off
Enterprise Contact us for pricing

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