Scatter Diagram: A Key Tool Among the 7 QC Tools

 

In Previous blog we have learnt "What is a Histogram? Meaning, Example and Uses in Quality Control" If you have not learnt go with below link - 

Introduction to Scatter Diagram in Quality Control

In the EMS industry, maintaining product quality is not just important — it is essential. From PCB assembly and soldering to testing and final inspection, every process must meet strict quality standards. To control defects and improve process performance, industries use the 7 QC (Quality Control) Tools.

One of the most useful and easy-to-understand tools among them is the Scatter Diagram. A Scatter Diagram helps quality engineers and manufacturing teams understand the relationship between two variables. It is widely used in problem-solving, root cause analysis, and process improvement activities.

What is a Scatter Diagram?

A Scatter Diagram, also known as a Scatter Plot, is a graphical tool used to show the relationship between two sets of data using dots plotted on a graph.

Each dot represents one pair of values:

  • One value is plotted on the X-axis
  • The second value is plotted on the Y-axis

By observing the pattern of the dots, we can identify whether the two variables are related or not.

For example:

  • Temperature vs Failure Rate
  • Soldering Time vs Defects
  • Input Voltage vs Output Signal

The scatter diagram helps determine whether changes in one variable affect another variable.

Why is a Scatter Diagram Important in Quality Control?

In manufacturing and electronics industries, data is collected continuously during production and testing. However, raw data alone is difficult to understand. A scatter diagram converts complex data into a simple visual format, making analysis easier and faster.

Main Benefits of a Scatter Diagram

1. Identifies Relationship Between Variables

It helps determine whether two variables are connected.

2. Supports Root Cause Analysis

Quality teams can identify possible causes of defects or failures.

3. Improves Decision Making

Visual data representation helps engineers take data-driven decisions.

4. Simplifies Data Analysis

Large amounts of production data become easier to interpret.

5. Helps in Process Improvement

Manufacturing teams can optimize process parameters for better quality.

Types of Relationships in a Scatter Diagram

A scatter diagram mainly shows three types of relationships between variables.

1. Positive Correlation

A positive correlation occurs when both variables increase together.

Example:

  • Temperature increases
  • Failure rate also increases

This indicates that higher temperature may be causing more failures.

Example in Electronics:

High heat during PCB operation may damage electronic components and increase rejection rates.

2. Negative Correlation

A negative correlation occurs when one variable increases while the other decreases.

Example:

  • Voltage stability increases
  • Circuit errors decrease

This means improving one factor helps reduce problems.

Example in Manufacturing:

Better soldering quality may reduce short circuits and dry solder defects.

3. No Correlation

Sometimes there is no visible relationship between variables.

In this case, the dots appear randomly scattered on the graph.

Example:

Humidity level vs software loading error

This indicates the variables may not be related.

Examples of Scatter Diagram in Electronics Industry : 

Scatter diagrams are widely used in electronics manufacturing, testing, and quality assurance processes.

1. Temperature vs Failure Rate

Electronic components are highly sensitive to temperature changes.

Example Setup:

  • X-axis → Temperature
  • Y-axis → Failure Rate

Analysis:

  • If the graph shows an upward trend, higher temperature increases failure rate.
  • If the graph shows a downward trend, lower temperature increases failure rate.

Benefit:

Engineers can identify safe operating temperature limits for electronic products.



    Figure: Scatter Diagram showing relationship between Temperature and Failure rate. The upward trend indicates a positive correlation, where defects increase as temperature rises.

2. Input Voltage vs Output Signal

During circuit testing, engineers analyze how circuits respond to different input voltages.

Example Setup:

  • X-axis → Input Voltage
  • Y-axis → Output Signal

Scatter Diagram Helps To:

  • Verify linear circuit behavior
  • Detect signal distortion
  • Identify abnormal performance
  • Improve circuit stability

This is especially useful in power supply testing and analog circuit analysis.

3. Soldering Time vs Manufacturing Defects

Soldering quality directly affects PCB reliability.

Example Setup:

  • X-axis → Soldering Time
  • Y-axis → Number of Defects

Analysis:

  • Very short soldering time may create weak joints.
  • Excessive soldering time may damage components or create defects.

Benefit:

Scatter diagrams help identify the optimal soldering time for better product quality and fewer defects.

How to Create a Scatter Diagram : Creating a scatter diagram is simple and effective.

Step-by-Step Process

Step 1: Collect Data : Gather two related sets of data.

Step 2: Define Variables

  • Independent Variable → X-axis
  • Dependent Variable → Y-axis

Step 3: Plot the Data : Place dots on the graph according to data values.

Step 4: Analyze the Pattern

Observe whether the points show:

  • Positive relationship
  • Negative relationship
  • No relationship

Step 5: Take Corrective Action : Use the analysis to improve quality and reduce defects.

Role of Scatter Diagram in the 7 QC Tools : Among the 7 QC Tools, the scatter diagram is mainly used as an analytical and problem-solving tool.

It helps quality engineers study:
  • Cause-and-effect relationships
  • Process variation
  • Defect patterns
  • Production behavior

Scatter Diagram Works Better with Other QC Tools : A scatter diagram becomes even more powerful when combined with other quality tools. 

Commonly Used Together: 
Check Sheet - Used for collecting production or defect data.
Histogram - Shows frequency distribution of data.
Pareto Chart - Identifies major problems based on the 80/20 principle.
Cause and Effect Diagram - Helps identify root causes of problems.
Together, these tools improve quality control and process analysis.

Advantages of Scatter Diagram
  • Easy to understand
  • Simple visual representation
  • Helps identify trends quickly
  • Supports process optimization
  • Useful for root cause analysis
  • Improves manufacturing quality

Limitations of Scatter Diagram

  • Does not prove exact cause and effect
  • Requires accurate data collection
  • Difficult to analyze when too much data is plotted

Conclusion : A Scatter Diagram is one of the most effective tools used in quality control and electronics manufacturing. It helps engineers and quality professionals understand the relationship between two variables and identify possible causes of defects or failures.

In next blog, we will explore about Flow Chart is one of the most effective tools used in quality control and manufacturing process management.

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