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Introduction to the Series
The Seven QC Tools —— check sheets, stratification, Pareto charts, cause-and-effect diagrams (fishbone diagrams), scatter diagrams, histograms, and control charts —— are the most fundamental and powerful "seven weapons" in quality management.
Many QC personnel use them, but not all truly understand them; many quality engineers know what they are, but do not fully utilize them. The purpose of this series is to dissect each tool: what it is for, when to use it, how to use it correctly, common pitfalls in practical application, and how to progress from "using it" to "mastering it."
This issue starts with the fishbone diagram. It is the most widely used tool among the Seven QC Tools, but also the one most easily misused.
Chapter 1: The Essence of Fishbone Diagrams
1.1 What is a Fishbone Diagram?
The fishbone diagram (Fishbone Diagram), also known as the cause-and-effect diagram (Cause-and-Effect Diagram), was first introduced by Japanese quality management master Kaoru Ishikawa in 1943, hence it is often referred to as the Ishikawa Diagram.
Standard Definition: The fishbone diagram is a visual tool that uses systematic causal chain analysis to unfold potential causes of a problem by category. Its core logic is: any result (problem/effect) has multiple causes, and these causes have hierarchical and categorical relationships.
1.2 The Essence of Fishbone Diagrams is Not "Drawing," but "Thinking Framework"
Many beginners view the fishbone diagram as "drawing a fish on the wall in a meeting room" — this misses its value entirely.
The essence of the fishbone diagram:
A structured, systematic, visual framework for cause analysis.
→ Structured: Not random, but categorized according to 5M1E
→ Systematic: Covers all possible dimensions of causes, avoiding omissions
→ Visual: A single diagram to see all potential causes and their relationships
1.3 Three Major Functions of Fishbone Diagrams
| Function | Description | Applicable Scenario |
|---|---|---|
| Identify Root Causes | Systematically list all possible causes to find the true root cause | 8D-D4, CAPA analysis, quality incident investigation |
| Prevent Problems | Identify potential issues in advance for risk prediction | FMEA brainstorming, new production line/product introduction |
| Promote Collaboration | Facilitate cross-departmental team communication, breaking down information barriers | Quality meetings, improvement project kick-off meetings |
Chapter 2: Structure and Elements of Fishbone Diagrams
2.1 Standard Structure Diagram
Cause Category 1 Cause Category 2
│ │
┌───────────────┼───────────────────────┤
│ │ │
▼ ▼ ▼
┌────────┐ ┌───────────┐ ┌───────────┐
│ Sub-Cause│ │ Sub-Cause │ │ Sub-Cause │
│ ├Main Cause│ │ ├Main Cause │ │ ├Main Cause │
│ │ ├Major Category│ │ │ ├Major Category │ │ │ ├Major Category │
└────────┘ └───────────┘ └───────────┘
│ │ │
└───────────────┼───────────────────────┘
│
▼
┌──────────────────┐
│ Problem/Effect │
│ (Fish Head - Right) │
└──────────────────┘
┌───────────────┼───────────────────────┐
│ │ │
▼ ▼ ▼
┌────────┐ ┌───────────┐ ┌───────────┐
│ Cause │ │ Cause │ │ Cause │
│ Category 3 │ Category 4 │ │ Category 5 │
└────────┘ └───────────┘ └───────────┘
2.2 Core Elements of Fishbone Diagrams
| Element | Name | Description | Position |
|---|---|---|---|
| Fish Head | Problem/Effect (Effect) | The core issue to be analyzed, the more specific, the better | Rightmost |
| Fish Spine (Main Line) | Main Line | A horizontal thick line pointing to the fish head | Center |
| Major Bones | Cause Categories (Major Category) | Categorized according to 5M1E or other frameworks | Diagonally from the main line |
| Medium Bones | Main Causes (Main Cause) | The main causes under each major category | Extending from major bones |
| Minor Bones | Sub-Causes (Sub-Cause) | Specific causes under the main causes | Extending from medium bones |
| Fine Bones | More Detailed Causes | The deepest level of analysis | At the end of minor bones |
2.3 Types of Fishbone Diagrams (by Direction)
| Type | Structure | Applicable Scenario |
|---|---|---|
| Cause-Type Fishbone Diagram | Fish head to the right (cause → problem) | Most commonly used — for root cause analysis |
| Countermeasure-Type Fishbone Diagram | Fish head to the left (measure → goal) | For planning improvement actions |
| Classification-Type Fishbone Diagram | Fish head to the right, checklist style | Process梳理, risk identification |
Chapter 3: 5M1E —— The "Skeleton" of Fishbone Diagrams
3.1 Complete Meaning of 5M1E
5M1E = Man (人) + Machine (机) + Material (料) + Method (法) + Measurement (测) + Environment (环)
This is the "standard classification framework" for fishbone diagram analysis in manufacturing.
Below are typical cause paths for each dimension:
M1 —— Man (人 / Personnel)
| Secondary Cause | Tertiary Cause (Examples) |
|---|---|
| Insufficient Skills | Inadequate training, many new employees, lack of certification for critical processes |
| Non-Standard Operations | Unfamiliar with SOPs, taking shortcuts, failing to self-inspect at the required frequency |
| Lack of Focus | Fatigue, monotonous work, reduced efficiency during night shifts |
| Weak Quality Awareness | Unclear about quality standards, lack of understanding of nonconformity consequences |
| Poor Communication | Information missing during shift changes, anomalies not promptly escalated |
| High Turnover | Loss of skilled workers, temporary replacements, hurried onboarding of new employees |
In-depth Comment: "Human" issues are often attributed to "bad attitude" or "lack of responsibility" — this is a major pitfall in analysis. Excellent quality professionals will continue to ask: Why is the attitude bad? Is it due to inadequate training? Insufficient incentives? Or is the process design itself prone to errors (the necessity of poka-yoke)?
M2 —— Machine (机 / Equipment)
| Secondary Cause | Tertiary Cause (Examples) |
|---|---|
| Insufficient Equipment Precision | Aging, wear, lack of timely calibration |
| Parameter Abnormalities | Incorrect parameter settings, drift, temperature/pressure/speed deviations |
| Tooling/Mold Issues | Mold wear, inaccurate positioning, unstable clamping force |
| Improper Maintenance | Lack of preventive maintenance, delayed fault repairs |
| Low Automation | Reliance on manual judgment, lack of error-proofing devices |
| Vibration/Noise | Worn bearings, failed dynamic balance, loose installation |
M3 —— Material (料 / Materials)
| Secondary Cause | Tertiary Cause (Examples) |
|---|---|
| Poor Incoming Quality | Supplier quality issues, significant batch-to-batch variation |
| Material Changes | Unannounced specification changes, unverified substitute materials |
| Improper Storage | Moisture, oxidation, expiration, temperature and humidity deviations |
| Confused Labeling | Different batches/specifications mixed, labels falling off |
| Poor Packaging | Damage during transportation, unverified changes in packaging methods |
M4 —— Method (法 / Methods)
| Secondary Cause | Tertiary Cause (Examples) |
|---|---|
| Unreasonable Process Parameters | Narrow parameter window, unverified parameters |
| Incomplete SOPs | Key parameters not specified, missing operation steps, unclear diagrams |
| Unclear Inspection Standards | Lack of boundary samples, subjective judgment criteria, unreasonable sampling plans |
| Process Design Flaws | Lack of error-proofing design, missing critical control points, process breakpoints |
| Unapproved Method Changes | Unauthorized process changes, hidden changes |
| Ineffective Training Methods | Disconnection between training and actual operations, lack of certification exams |
M5 —— Measurement (测 / Measurement)
| Secondary Cause | Tertiary Cause (Examples) |
|---|---|
| Insufficient Gauge Precision | Insufficient resolution, lack of timely calibration, mismatched measurement range |
| Improper Measurement Methods | Inconsistent measurement locations, non-uniform measurement techniques, incorrect reference surfaces |
| Standard Part Failure | Worn standard blocks, discolored samples, lost boundary samples |
| Insufficient Inspection Frequency | Too small sample size, too long inspection intervals |
| Reading/Recording Errors | Human reading errors, non-standard recording, incorrect data units |
| Poor MSA | High GR&R, significant bias, non-conforming linearity |
In-depth Comment: Issues with the measurement system itself are often overlooked — many people assume the measurement results are correct. Excellent quality engineers always ask: Is this data reliable? Is there a problem with the measurement system?
M6 —— Environment (环 / Environment)
| Secondary Cause | Tertiary Cause (Examples) |
|---|---|
| Temperature and Humidity | Loss of control over constant temperature and humidity, diurnal temperature differences, seasonal changes |
| Cleanliness | Dust particles, oil contamination, static electricity |
| Lighting | Insufficient illumination affecting visual inspection, color temperature deviation affecting color judgment |
| Noise/Vibration | Ground vibrations from external equipment affecting precision machining |
| Space Layout | Unreasonable material flow routes, cramped workspaces |
3.2 5M1E Extensions in Different Industries
| Industry | Additional 5M1E Dimensions | Description |
|---|---|---|
| Service Industry | 4M+1C (Customer) | One of the core influencing factors in the service industry is customer participation behavior |
| Software Industry | Add 2M (Information Management + Metrics) | Categories for software quality reasons should be expanded to: requirements, design, coding, testing, deployment, operations |
| Medical Industry | Add 1P (Patient) | Patient compliance and physical differences are important dimensions |
| Food Industry | Add 1C (Cold Chain) | Cold chain logistics are critical control points for food quality |
Chapter 4: Operating Procedures for Fishbone Diagrams (Standard 7-Step Method)
Step 1 —— Define the Problem (Fish Head)
Key: The more specific the problem definition, the more effective the analysis.
× Incorrect Example: "Poor product quality"
→ Too vague, difficult to focus the analysis direction
✓ Correct Example: "The welding strength of product B on line A has decreased by 30% over the past two weeks compared to industry standards"
→ Specific to: what product, what process, what metric, what time, what deviation amount
Problem Definition Checklist:
- Is the problem measurable? (Specific data/metrics)
- Is the problem time and space-limited? (What product, what time, what line)
- Are known factors excluded? (Are certain conditions known to be unchanged?)
- Is the problem a single focus? (Analyze one problem at a time)
Step 2 —— Build the Framework (Draw the Main Line and Major Bones)
Draw the basic structure of the fishbone diagram on paper or a whiteboard:
- Draw a horizontal thick line (main line)
- Draw a box on the right (fish head) and write the problem description
- Draw 5-8 diagonal arrows (major bones) and label them with cause categories (5M1E)
Step 3 —— Brainstorm (Team Collaboration)
Invite a cross-functional team to participate — the greatest value of the fishbone diagram lies in the collision of multiple perspectives.
Suggested Participants:
└── QC (Most familiar with on-site details)
└── QE (Most familiar with quality data and system issues)
└── Production Operators/Team Leaders (Most familiar with actual operations)
└── Process Engineers (Most familiar with process parameters)
└── Equipment Maintenance Personnel (Most familiar with equipment status)
Brainstorming Rules:
- Do not criticize or judge any opinions (no matter how "absurd")
- Encourage quantity; more ideas can lead to better solutions
- Encourage "piggybacking" — building on others' ideas
- Describe each cause in neutral language (do not presuppose conclusions)
- Record every idea — do not filter
Step 4 —— Layered Expansion (Small Bones → Fine Bones)
Key Principle: Ask at least three levels deep.
Example (Increased defect rate → Welding defects):
First Level (Major Bone → Medium Bone):
M (Method): Unreasonable welding parameters
Second Level (Medium Bone → Small Bone):
Unreasonable welding parameters → Deviation in welding current settings
Third Level (Small Bone → Fine Bone):
Deviation in welding current settings → Parameters not adjusted to standard after shift change
Deviation in welding current settings → Failure of the equipment's parameter memory function
Fourth Level (Fine Bone → More Detailed):
Failure of the equipment's parameter memory function → Preventive maintenance not covering this function module
Failure of the equipment's parameter memory function → Parameters not verified after repairs
In this example, the initial symptom is "welding defects,"
the surface cause is "parameter deviation,"
and the deep cause is "incomplete maintenance system."
Excellent fishbone diagrams find the true root cause at the 3rd to 4th level. Stopping at the 1st to 2nd level results in superficial analysis of surface causes.
Step 5 —— Identify Key Influencing Factors
There are many causes on a fishbone diagram (usually 30-50), and not all need to be addressed.
Screening Methods:
Method 1: Voting (Team Consensus)
Each person selects the top 5 most important causes from all causes
Rank by the number of votes, select the top 5-8 causes
Applicable: When the team is experienced
Method 2: Data Verification
Use existing inspection data to verify the "relevance" of each cause
For example: If it is "cause of equipment A," compare defect rates when equipment A is running and not running
Applicable: When data is available
Method 3: Pareto Chart Screening
Convert the causes identified by the fishbone diagram into data collection
Use a Pareto chart to identify the "vital few" causes
Applicable: When strict quantification is needed
Method 4: Control Experiment
Conduct a small-scale intervention experiment on suspected root causes
If the problem disappears after the intervention, the root cause is found
Applicable: In controllable scenarios
Step 6 —— Verify Root Causes
Important Understanding: The causes identified by the fishbone diagram are just "hypotheses," not "conclusions."
Fishbone Diagram → Generate Hypotheses (Hypothesis Generation)
Data Verification → Verify Hypotheses (Hypothesis Verification)
A fishbone diagram without data verification is just a "pretty picture."
Three Levels of Root Cause Verification:
| Level | Method | Reliability |
|---|---|---|
| Basic | Team Consensus (Everyone thinks it is) | ★★ |
| Intermediate | Historical Data Review (Data supports the hypothesis) | ★★★★ |
| Advanced | Control Experiment/DOE Verification (Problem disappears after intervention) | ★★★★★ |
Step 7 —— Develop Improvement Actions
For verified root causes, develop specific improvement actions:
Root Cause: Failure of the equipment's parameter memory function (not covered by preventive maintenance)
Actions:
Short-term: Immediately repair the parameter memory module, verify parameters after line stop for maintenance
Medium-term: Include the parameter memory function in the preventive maintenance checklist
Long-term: Increase reliability requirements for the parameter memory function in equipment procurement
Chapter 5: Common Pitfalls and Avoidance in Fishbone Diagrams
Pitfall 1: Listing Causes Without Categorization
× Incorrect Practice:
List all causes directly on the fishbone diagram without categorization
→ Result: A mess of arrows pointing to the fishbone, no clear structure
✓ Correct Practice:
Categorize using 5M1E before filling in
→ "Categorization itself is analysis" — ask "Are there any causes in this category?" for each category
Pitfall 2: Only Writing Major Bones, No Further Subdivision
× Incorrect Practice:
Write "Man" on the major bone and do not expand further
→ Result: Too little information, no analytical value
✓ Correct Practice:
Expand each major bone to at least the 2nd-3rd level
"Man" → "Insufficient Skills" → "Inadequate Training" → "Insufficient New Employee Training Period"
Pitfall 3: Stopping at "Surface Causes" on One Fishbone
× Incorrect Fishbone Analysis:
"Increased defect rate"
→ Man: Unfamiliar operations
→ Machine: Equipment aging
→ Material: Poor quality
Then stop.
→ Result: Unable to develop effective countermeasures
✓ Correct Fishbone Analysis:
Continue asking until you reach a level where "something can be done to change it"
Pitfall 4: One Person Completes the Entire Diagram
× Incorrect Practice:
A quality engineer completes the fishbone diagram alone in the office
→ Result: A "expert perspective" diagram that misses real production line information
✓ Correct Practice:
Cross-functional team (QC + Production + Process + Equipment + ...) works together
→ Different perspectives complement each other, uncovering hidden causes
Pitfall 5: Treating the Fishbone Diagram as a "Closing Report"
× Incorrect Practice:
A beautiful fishbone diagram in an 8D report, then... no one looks at it again
→ Result: A pretty PPT, but the problem will reoccur
✓ Correct Practice:
The fishbone diagram is an analysis tool, not a presentation tool
The key is whether the conclusions from the analysis have been converted into improvement actions
Pitfall 6: Confusing "Causes" and "Phenomena"
× Incorrect: "High defect rate" is caused by "dimensional tolerance exceeded"
→ Dimensional tolerance exceeded is itself a nonconformity, not a cause
✓ Correct:
Nonconformity: Dimensional tolerance exceeded
Cause: Tool wear → Unreasonable tool life setting → Lack of tool management system
Pitfall 7: Attempting to Analyze Multiple Problems on One Fishbone Diagram
× Incorrect Practice:
One fishbone diagram lists "increased scrap rate, increased customer complaints, decreased efficiency"
→ Result: Multiple problems mixed, causes intersect, no clear starting point
✓ Correct Practice:
Analyze one problem at a time
If there are multiple problems, draw separate fishbone diagrams
Chapter 6: Combining Fishbone Diagrams with Other Tools
6.1 Fishbone Diagram + 5 Whys
Best Partner. The fishbone diagram provides "breadth," while 5 Whys provides "depth."
Combined Use Process:
Step 1: Fishbone Diagram Brainstorming
→ List all possible causes (broad coverage)
Step 2: Use voting/data to select key causes
→ Identify the top 3-5 most likely causes
Step 3: Apply 5 Whys to each key cause
→ Drill down to the system-level root cause (deep analysis)
6.2 Fishbone Diagram + Pareto Chart
Combined Use:
Step 1: Fishbone Diagram Analysis → List all cause hypotheses
Step 2: Design data collection for the cause hypotheses
Step 3: Analyze the collected data using a Pareto chart
→ Identify the "vital few" causes
Step 4: Develop improvement actions for the key few causes
This method addresses the inherent weakness of the fishbone diagram: The fishbone diagram generates many hypotheses but does not prioritize them, while the Pareto chart adds priority judgment.
6.3 Fishbone Diagram + FMEA
Combined Use:
Step 1: Use the fishbone diagram to identify potential failure causes in the process
Step 2: Input the causes identified by the fishbone diagram into the "failure cause" column of the FMEA
Step 3: Evaluate the severity (S), occurrence (O), and detection (D) of the cause
Step 4: Calculate the RPN to determine improvement priorities
FMEA's O (occurrence) and D (detection) judgments require fishbone diagram information as input.
6.4 Fishbone Diagram + C&E Matrix (Cause & Effect Matrix)
The C&E matrix is a "quantitative upgrade" of the fishbone diagram:
Approach:
├── Rows: All causes identified by the fishbone diagram
├── Columns: Product quality characteristics (CTQs)
├── Cells: Impact scores of causes on CTQs (0, 1, 3, 9)
└── Summary: Total score for each cause → Rank the most critical causes
Chapter 7: Practical Cases of Fishbone Diagrams in Various Industries
Case 1: Manufacturing —— "Insufficient Welding Strength"
Problem: The welding strength nonconformity rate of product B on line A increased from 0.3% to 2.5%
Fishbone Diagram Analysis Path (Simplified):