fishbone-diagram

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React fishbone (Ishikawa) diagram component.

Fishbone Diagrams using D3JS in Angular

pddon diagram editor linux client，PDDON is a daily drawing tool that supports low code for learning or office use.

Interactive Fishbone (Ishikawa) Diagram tool for practicing Root Cause Analysis — built for Six Sigma learners

React.js dynamic, sortable fishbone diagram based on html canvas. Print friendly. JSON or manual creation

This repository contains case studies set in real-life Food production facility that are analyzed using Excel

Six Sigma Yellow Belt project applying the DMAIC methodology to optimize customer interaction handling time by eliminating process inefficiencies, standardizing workflows and improving operational efficiency.

Interactive Python application for automated Root Cause Analysis using dynamic Fishbone (Ishikawa) diagrams built with Tkinter and Matplotlib.

Quality management case study using inspection data, p-charts, control charts, root-cause analysis, and corrective-action planning to evaluate defect-rate improvement.

Root-cause analysis without drawing a fishbone. Same information as an Ishikawa diagram, held as a nested structure and saved as JSON. Single HTML file.

WSQ - Generative AI for Problem Solving (TGS-2023036653) — 2-day SkillsFuture-funded courseware: 160-slide deck, Lesson Plan, Learner Guide and 10 real-life case-study activities with GenAI prompts and problem-solving ed-tools.

Six Sigma Green Belt project using the DMAIC methodology to reduce unnecessary technician dispatches, improve remote resolution effectiveness and increase first-call resolution through data-driven process improvement.

An automatic generator of a fishbone diagram based on the excel import.

A fully dynamic Fishbone (Ishikawa) Analysis custom visual for Power BI built using TypeScript and D3.js, featuring responsive layout, zoom/pan, and enterprise-grade scalability for root cause analysis.

Clinical Root Cause Analysis MCP Server - AI-guided structured RCA with Fishbone (6M), 5-Why, and HFACS-MES integration for healthcare quality improvement