Overview
ISO/TR 29901:2007 - Selected illustrations of full factorial experiments with four factors is a Technical Report that explains how to specify, run and analyse full factorial experiments with four factors (2^4 designs) through five practical illustrations. The report bridges rigorous statistical practice and Six Sigma-style applied problem solving by presenting generic guidance and detailed examples from diverse fields. It focuses on two-level factor settings (with optional centre points and repetitions) and demonstrates analysis with contemporary statistical software.
Key topics and requirements
- Scope and purpose
- Guidance for designing and analysing full factorial designs with four factors (2^4), while noting that other numbers of factors can be considered depending on the application.
- Basic experiment workflow (Table 1)
- 1. State the objective
- 2. Define the response variable(s)
- 3. List candidate factors
- 4. Select a full factorial design
- 5. Analyse results (numerical summaries, graphical displays)
- 6. Present results
- 7. Perform confirmation runs
- Design elements
- Two-level factors (coded as +1 / −1), centre points where applicable, replication and randomization, and the full factorial structure (all combinations of factor levels - 16 runs for four factors).
- Analysis methods
- Emphasis on ANOVA, interaction assessment (two-, three- and four-way interactions), graphical display and numerical summaries to interpret main effects and interactions.
- Constraints and exclusions
- Does not cover follow-up response surface designs, Taguchi or blocking designs; focuses on illustrative practice rather than detailed mathematical derivations.
- Terminology and symbols
- Aligns with ISO 3534 series (vocabulary for statistics and design of experiments).
Practical applications and users
ISO/TR 29901:2007 is practical for:
- Six Sigma practitioners (black belts/green belts) who need applied factorial-design examples.
- Quality engineers and process scientists in manufacturing, chemical processing, telecommunications, and software.
- Marketing analysts (e.g., direct-mail campaign optimization).
- R&D teams performing controlled experiments (examples include solder bar testing, button tactility, PVC formulation, and DNA sequencing algorithm experiments).
Benefits:
- Provides step-by-step templates for planning experiments, detecting factor interactions, improving process settings, and validating changes through confirmation runs.
Related standards
ISO/TR 29901:2007 is a concise, application-focused resource for professionals seeking practical guidance on 2^4 full factorial experiments, and it supports improved experimental design, robust analysis and actionable process improvements.
