DMADV Define · Measure · Analyze · Design · Verify
Design for Six Sigma cycle for greenfield development of new products or processes.
Data & Tools
Data preparation, visualisation and generation tools — usable across every phase.
Data Collection
Spreadsheet for data entry and management
XY Plot
Create scatter plots from worksheet columns
Pie Chart
Pie/donut chart from worksheet columns or manual data
Bar Chart
Bar chart from worksheet columns: frequency, mean, or sum per category
Pareto Chart
Bar chart sorted by descending value with a cumulative-percentage line — the classic "vital few" tool.
Mosaic Plot
Visualises the joint distribution of two categorical variables — column widths show the marginal frequency, segment heights show the conditional shares.
Heatmap
Cross-tabulation as a color-coded grid — cell color shows frequency, mean, or sum per (X, G) combination.
Contour Plot
Visualize response surfaces z = f(x, y) as contour diagrams
Histogram
Frequency distribution with boxplot and statistics
Boxplot
Horizontal boxplots for comparing distributions
Individual Value Plot
Plot every individual observation per group as a point
Run Chart
Median run chart with four runs tests
Probability Plot
Normal probability plot for checking normality, with optional grouping
Chart Suggestion
Proposes suitable chart types for the selected columns
Data Import
Read data from third-party formats (Minitab .mpx, CSV/TSV/TXT, Excel/ODS, JSON/NDJSON, Q-DAS AQDEF) into a worksheet
REST API
Centrally manage and test REST API endpoints
Random Generator
Generate reproducible samples from statistical distributions
Model Data Generator
Generate synthetic datasets from configurable regression models
Calculator
Scientific calculator with statistics and 6σ mode
Unit Converter
Precise unit conversion (18 categories + timezones)
Data Transformation
Transform data (Box-Cox, Johnson, Log, …) for normality
Define
Phase 1 of the DMAIC cycle — define problem, goals, scope and stakeholders.
Project Charter
Project mandate: problem statement and measurable goals
Calendar
Description
Todo
Task list with status, due date, and owner
Stakeholder Analysis
Identify, assess, and plan communication with project stakeholders
VoC → CTx Tree
Translate Voice of Customer into measurable CTx requirements
RACI Matrix
Responsibility Assignment Matrix: roles per activity and stakeholder
SIPOC
Supplier-Input-Process-Output-Customer diagram
5-Why Analysis
Root cause analysis with branching question paths
Measure
Phase 2 of the DMAIC cycle — map the process, collect data, validate measurement systems.
Process Map
Visual process flow with inputs and outputs per step
MSA Type 1
Measurement System Analysis Type 1 — Repeatability (Cg) and Bias (Cgk)
MSA Type 2
Measurement System Analysis Type 2 — Gage R&R (Repeatability & Reproducibility)
Process Capability
Process Capability Analysis — Cp, Cpk, Pp, Ppk, PPM, Sigma Level
Analyze
Phase 3 of the DMAIC cycle — surface root causes, test hypotheses, uncover patterns.
C&E Matrix
Cause and Effect Matrix
Ishikawa 6M
Root cause analysis with 6M categories and expert scoring
Makigami Matrix
Swim-lane process analysis with processing/waiting times and waste classification
Correlation Analysis
Pearson, Spearman, and Kendall correlation between variables
Distribution Fit
Fit data to multiple distributions and rank by Goodness-of-Fit test
FMEA
Failure Mode and Effects Analysis with RPN calculation
Hypothesis Test
Variance and mean tests with automatic normality assessment and power analysis
Sample Size
Calculate the required sample size for variance and mean tests
Pairwise Comparison
Prioritize criteria through systematic pairwise comparison. Every criterion is judged against every other.
Outlier Test
Run classical outlier tests (Grubbs, Dixon Q, Generalized ESD, Tukey IQR, Hampel, Z-Score) in parallel on a column
Design
Phase 4 of the DMADV cycle — design the solution, build prototypes, optimise the draft.
DoE Advisor
Overview of DoE designs and a guided wizard for design selection
DoE Planner
Design of Experiments: Full Factorial, Fractional, Plackett-Burman, CCD, Box-Behnken, Taguchi
Regression Analysis
Polynomial regression (degree 1–3, interactions), Exponential, Logarithmic, Power
Regression (Attributive)
Binary logistic, Poisson, and negative binomial regression for attributive/count data
Response Optimization
Combines several saved regression models and searches for the factor point with the highest joint desirability (Derringer-Suich, multi-start Nelder-Mead).
Verify
Phase 5 of the DMADV cycle — validate the design and hand it over to operations.
Control Chart
SPC control charts for process stability
Control Chart (Attribute)
SPC charts for count data: p, np, c, u
Control Chart (Time-Weighted)
EWMA and CUSUM for small persistent shifts
Control Chart (Rare Events)
g and t charts for rare events
Multivariate Control Chart (Hotelling T²)
Hotelling T² for correlated characteristics
Control Chart (Short-Run Z-MR)
Standardised I-MR across parts with different targets
Control Chart (Box-Cox transformed)
I-MR with Box-Cox transform for non-normal data
Lessons Learned
Structured documentation of project insights
More tools
These tools have no fixed phase assignment in this cycle. In the app they appear in the trailing "More" tile and can be dragged into a phase.
Contradiction Matrix (TRIZ)
Inventive principles for technical contradictions (Altschuller)
9 Windows (TRIZ System Operator)
Examine the system on time × hierarchy axes
Physical Contradiction (TRIZ)
One parameter must be A and ¬A — resolution via four separation principles
Ideal Final Result (TRIZ)
State the ideal and work backwards to a solution
Resources Checklist (TRIZ)
Systematic inventory of substances, fields, space, time, information and functions
Trends of Technical Evolution (TRIZ)
Eight classical evolution trajectories — locate the system and identify the next stage jump
Substance-Field Analysis (TRIZ)
Model the interaction as an S1-S2-field triangle and apply Altshuller's 76 standard solutions