--- name: dmaic description: >- DMAIC (Define-Measure-Analyze-Improve-Control) — Six Sigma structured problem-solving for chronic, data-driven quality improvement projects. Use when a problem recurs despite corrective actions, when a process needs systematic capability improvement, or when a customer requests a Six Sigma approach. Use 8D for reactive single-incident problems; use DMAIC for recurring systemic issues requiring statistical analysis. Covers IATF 16949 §10.1 and ISO 9001 §10.3. license: MIT metadata: author: RBraga01 version: "1.1" iso-9001: "10.3" iatf-16949: "10.1" domain: quality-engineering subdomain: problem-solving industries: automotive,electronics,aerospace,medical,general status: approved created: "2026-06-06" last_updated: "2026-06-06" updated_by: migmcc reviewed_by: RBraga01 standard_edition: "Six Sigma DMAIC / ISO 9001:2015 §10.3 / IATF 16949:2016 §10.1" --- # DMAIC (Six Sigma Problem Solving) ## When to use Use DMAIC when: - A problem has recurred multiple times despite previous corrective actions - The process needs measurable, data-driven capability improvement (Cpk improvement target) - The root cause is unknown and requires statistical analysis to identify - A customer requires a Six Sigma approach or asks for a DMAIC report - The improvement opportunity involves eliminating chronic waste (rework, scrap, test failures) **Use 8D instead when:** The problem is a single customer complaint, an escape to the field, or requires immediate containment. 8D is reactive and fast. DMAIC is proactive and thorough — it takes weeks to months. **Use PDCA instead when:** The improvement is incremental and the root cause is already known or assumed. ## Prerequisites - A defined problem with measurable impact (reject rate, Cpk, scrap cost, defect count) - Baseline data available or collectable - Process owner and cross-functional team assigned - Management support and a time budget (minimum 4–12 weeks depending on project scope) ## Workflow ### Phase 1 — DEFINE **Objective:** Define the problem, the scope, the team, and the goal in measurable terms. **Key tools and deliverables:** **Project Charter** — The DMAIC starts and ends here. Contains: - Problem statement: what is happening, where, since when, how much (measured impact) - Goal statement: specific, measurable target (e.g., "Reduce connector reject rate from 3.2% to 0.5% by Q3") - Scope: what is IN and OUT of scope (use Is/Is-Not to define boundaries) - Business case: financial or customer impact ($, PPM, warranty cost) - Team: Champion, Black Belt/Green Belt, process owner, operators, engineering **SIPOC diagram:** - Suppliers → Inputs → Process → Outputs → Customers - Defines the process at a high level before diving into detail - Identifies all inputs that could affect the output (Y) **Voice of the Customer (VOC) → CTQ:** - What does the customer care about? (VOC) - Translate to a measurable Critical to Quality (CTQ) characteristic - The CTQ becomes the Y (output) the project will improve **Gate criteria to exit Define:** - Problem is specific and measurable - Goal is agreed with the Champion - Scope is bounded - Team is assigned and available --- ### Phase 2 — MEASURE **Objective:** Establish the current baseline and validate the measurement system. **Key tools and deliverables:** **Process map (detailed):** - Map every step of the process as it IS (not as it should be) - Identify where defects are created or detected - Mark each step: Value-Added (VA), Non-Value-Added (NVA), or Required Non-Value-Added **Data collection plan:** - What will be measured? (the Y and key process inputs Xs) - How will it be measured? (gauge, method) - How many samples? (for capability: minimum 100 pieces) - Who will collect data? When? Where? **MSA (Gauge R&R):** - Validate the measurement system for the CTQ before collecting data - %GRR < 30% required; <10% preferred - If measurement system is inadequate: fix it before proceeding **Baseline capability:** - Calculate current Cpk/Ppk for the CTQ - Establish current defect rate (PPM or %) - This baseline is the MEASURE gate deliverable — do not proceed without it **Gate criteria to exit Measure:** - Baseline Cpk/PPM established with statistical confidence - MSA complete and measurement system adequate - Data collection plan executed with sufficient data --- ### Phase 3 — ANALYZE **Objective:** Identify and confirm the root cause(s) of the problem using data. **Key tools and deliverables:** **Fishbone / Cause & Effect diagram:** - Brainstorm potential causes using 6M (Man, Machine, Method, Material, Measurement, Mother Nature) - All potential causes are hypotheses at this stage — none are confirmed **Is/Is-Not analysis:** - Scope the problem precisely — what IS affected vs. what IS NOT - Narrows the hypothesis list before investing in analysis **Multi-Vari study:** - Understand whether variation is: positional (within-part), cyclical (part-to-part), or temporal (time-based) - Identifies the dominant family of variation — directs the investigation **Hypothesis testing:** Confirm or reject hypotheses statistically. Selection guide: | Situation | Tool | |-----------|------| | Compare means of 2 groups (continuous Y, e.g., Shift A vs. B) | t-test (paired if same parts measured twice) | | Compare means of 3+ groups (e.g., 3 machines, 4 operators) | One-way ANOVA | | Categorical Y (pass/fail) vs. categorical X (supplier, shift) | Chi-square test | | Continuous Y vs. continuous X (does temperature predict dimension?) | Pearson correlation; then regression to quantify | | Multiple Xs affecting one Y | Multiple regression; confirm no multicollinearity | Use p < 0.05 as the significance threshold unless a different risk level is warranted. Always check the test's assumptions (normality for t-test/ANOVA; independence for chi-square). **Root cause confirmation:** - A root cause is NOT confirmed until data proves it - Reject "human error" as a root cause — it is a symptom; ask why the error was possible - Confirmed root causes: demonstrate that when the Xs change, the Y changes predictably **Gate criteria to exit Analyze:** - Root cause(s) confirmed with data (not assumed) - Cause-and-effect quantified (Y = f(X) relationship established) - Team agrees on which Xs to improve --- ### Phase 4 — IMPROVE **Objective:** Develop, test, and implement solutions that address the confirmed root causes. **Key tools and deliverables:** **Solution generation:** - Brainstorm solutions for each confirmed root cause - Evaluate solutions: impact vs. effort vs. risk - Do NOT select solutions based on opinion — test them **Pilot / Design of Experiment (DOE):** - Test the proposed solution on a small scale before full implementation - DOE: systematically vary multiple factors to find the optimal process settings - Simple experiments: OFAT (One Factor At A Time) for straightforward improvements **Solution validation:** - Run a production pilot with the solution in place - Collect data: does the Y improve as predicted? - Calculate new Cpk/PPM — compare to baseline and goal **Implementation plan:** - Who does what, by when, to implement the solution at full scale - Change management: update Process Flow, PFMEA, Control Plan, Work Instructions, training **Gate criteria to exit Improve:** - Solution tested and statistically validated (not just "it seems better") - Cpk/PPM improvement demonstrated in pilot data - Implementation plan complete and approved --- ### Phase 5 — CONTROL **Objective:** Sustain the gains — prevent the process from reverting to the old state. **Key tools and deliverables:** **Updated Control Plan:** - Add new controls for the Xs identified in Analyze - Define monitoring frequency and reaction plan for out-of-control conditions **SPC / Statistical monitoring:** - Install control charts on the critical Xs and the Y - Set control limits from the improved process data - Define who monitors and how often **Updated PFMEA:** - New failure modes identified during the project must be added - Controls added in Improve must be reflected in the PFMEA current controls column **Updated Work Instructions:** - Document the new process steps, settings, or behaviours required - Train operators and verify understanding **Mistake-proofing (Poka-yoke):** - For any root cause that was behavioural or procedural: add error-proofing to prevent recurrence - Error-proofing is the highest-reliability control — prefer it over inspection or SPC alone **Project handover:** - Transfer ownership from the project team to the process owner - Establish a 3–6 month monitoring period with defined Cpk targets; specify the minimum Cpk that constitutes "sustained improvement" (e.g., Cpk ≥ 1.33 for a minimum of 3 consecutive months of production data — not 3 months of calendar time) - Close the project only when the monitoring criterion is met with actual production data — not lab data or pilot data **Final project report:** - Before and after: Cpk, PPM, financial savings - Lessons learned for future projects **Gate criteria to close the project:** - Cpk/PPM goal achieved and sustained for minimum 3 months post-implementation - All documents updated (PFMEA, CP, WIs) - Process ownership transferred to process owner - Financial benefits validated by Finance (if business case required it) --- ### DMAIC vs. 8D — quick reference | Dimension | 8D | DMAIC | |-----------|-----|-------| | Trigger | Customer complaint, single escape | Recurring problem, capability gap | | Timeline | Days to weeks | Weeks to months | | Root cause method | 5-Why, Fishbone | Hypothesis testing, statistical analysis | | Output | Corrective action to prevent recurrence | Optimised process with sustained capability | | Standards | ISO 9001 §10.2, IATF 16949 §10.2.3 | ISO 9001 §10.3, IATF 16949 §10.1 | ## Validation criteria A DMAIC project is complete when: - Baseline and improved Cpk/PPM both quantified with data - Root causes confirmed statistically (not assumed) - Solution validated in a pilot before full implementation - PFMEA, Control Plan, and Work Instructions updated - Improved Cpk sustained for minimum 3 months post-implementation - Financial or quality benefit measured and reported ## Common mistakes - Jumping to Improve before confirming root cause (the most common DMAIC failure) - Not performing MSA before collecting baseline data — baseline may be measurement noise - Selecting the solution in Define before data analysis — biases the entire project - Closing the project at Implementation without monitoring for sustainability - Not updating PFMEA and Control Plan — process reverts within months - Using DMAIC for a single-event problem that needs 8D containment first ## Output Format At the start of each use, ask the user: > "How would you like to receive the output? > **A** — Structured Markdown (formatted tables and sections, ready to copy) > **B** — Plain tables (simplified structure for Excel or Word) > **C** — Narrative report (flowing text for a formal document or email) > > Default: A." Adapt all output sections to the chosen format. If the platform or session context already defines a format preference, skip this question. ## Changelog | Version | Date | Author | Change | |---------|------|--------|--------| | 1.0 | 2026-06-06 | @RBraga01 | Initial release | | 1.1 | 2026-06-06 | @migmcc | Added hypothesis test selection guide in Phase 3; added monitoring period closure criteria in Phase 5 (Cpk sustained on production data, not pilot) |