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lean-six-sigma-consultant

Execute DMAIC/DMADV projects with Lean waste methods and statistical quality tools.

5|4|Updated Nov 9, 2025
Search Tags:#statistical analysis#fmea#dmaic#process capability#control charts#lean waste elimination
One-click install
npx skills add https://github.com/takusaotome/claude-skills-library --skill lean-six-sigma-consultant
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: lean-six-sigma-consultant
Source: https://github.com/takusaotome/claude-skills-library/tree/main/skills/lean-six-sigma-consultant
Command: npx skills add https://github.com/takusaotome/claude-skills-library --skill lean-six-sigma-consultant

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires numpy, scipy, argparse, json, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

It helps teams execute Lean Six Sigma improvement projects end-to-end—turning vague process complaints into structured DMAIC/DMADV work with root-cause analysis, statistical validation, risk planning, and sustainable control plans.

Core Features & Use Cases

  • DMAIC project execution (Define→Measure→Analyze→Improve→Control) with phase-specific deliverables, tollgate checklists, and templates (charter, SIPOC, VOC/CTQ, A3-style problem solving).
  • Statistical analysis support for process capability and performance (Cp/Cpk, Pp/Ppk, sigma level, DPMO/yield estimates) plus control chart analysis with Western Electric rule detection for stability and special-cause signals.
  • Lean waste elimination workflows using Value Stream Mapping and the 8 Wastes (DOWNTIME) to design a future state and drive Kaizen-style improvements.

Quick Start

Tell the skill: "We need to reduce defects in our process; here are the baseline defect counts, units, and opportunities per unit—walk us through a DMAIC project and generate the project charter, baseline metrics, and the next-phase actions."

Frequently Asked Questions about lean-six-sigma-consultant

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I execute a DMAIC project to reduce process defects?▼

To execute a DMAIC project for defect reduction, you define the project scope using a charter and SIPOC, measure baseline performance metrics, analyze root causes, implement improvements, and establish control plans with stability checks to sustain quality gains.

How do I calculate process capability and check stability using control charts?▼

Process capability is calculated by assessing Cp, Cpk, Pp, Ppk, sigma level, and DPMO metrics. Control chart stability is verified by detecting special-cause signals using Western Electric rules to ensure your process remains in statistical control.

What is the best way to identify Lean waste using Value Stream Mapping?▼

The best way to identify Lean waste is mapping the current process flow using Value Stream Mapping and categorizing inefficiencies using the 8 Wastes (DOWNTIME) framework to design a future state and drive Kaizen-style improvements.

Can I perform FMEA risk planning using Python and numpy?▼

Yes, you can perform FMEA risk planning using Python with numpy and scipy. The statistical environment supports calculating risk priority numbers and structuring failure mode analysis for comprehensive DMAIC project risk mitigation.

Do I need baseline defect counts and opportunities per unit for statistical analysis?▼

Yes, baseline defect counts, total units, and opportunities per unit are required inputs for statistical analysis. These values drive accurate process capability assessment, sigma level calculation, and DPMO estimates for your DMAIC project.

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