7 QC Tools - Quality

Table of Contents

Introduction & Why use the 7 QC Tools?

The 7 QC tools help to analyze the data and are most helpful in problem-solving methods. It is the fundamental tool to improve our product and process quality by identifying and analyzing the problems.

As per the Deming chain to achieve the organizational goal, we must tackle the product & process-related problems, and analyze these problems we get help from 7 QC tools. These 7 QC tools give us the analytical and statistical competence to solve the problems.

What are 7 QC tools?

7 Basic Quality techniques

Pareto Chart

Purpose:

Prioritize problems.
Pareto Charts are used to apply the 80/20 rule of Joseph Juran which states that 80% of the problems are the result of 20% of the problems. A Pareto Chart can be used to identify 20% of route causes of problems.

How is it done?

Create a preliminary list of problem classifications.
Tally the occurrences in each problem classification.
Arrange each classification in order from highest to lowest
Construct the bar chart

Benefits:

Pareto analysis helps graphically display results so the significant few problems emerge from the general background
It tells you what to work on first

To know the detail of What Pareto Principle is?, How to Make Pareto in Excel?

Cause & Effect Analysis

Purpose:

Graphical representation of the trial leading to the root cause of a problem
It’s a diagram that demonstrates the relationship between Effects and the categories of their causes
The Arrangement of the Diagram lets it look like a fishbone it is therefore also called a fish-bone diagram

How is it done?

Decide which quality characteristic, outcome, or effect you want to examine (may use a Pareto chart)
Backbone –draw a straight line
Ribs – categories
Medium-size bones –secondary causes
Small bones – root causes

Benefits:

Breaks problems down into bite-size pieces to find the root cause
Fosters teamwork
A common understanding of the factors causing the problem
Road map to verify picture of the process
Follows brainstorming relationship

To learn in detail How to create a cause and effect diagram (Fishbone diagram)?

Histogram

Purpose:

A Histogram is a bar graph
To determine the spread or variation of a set of data points in a graphical form
usually used to present frequency

How is it done?

Collect data, 50-100 data point
Determine the range of the data
Calculate the size of the class interval
Divide data points into classes Determine the class boundary
Count # of data points in each class
Draw the histogram

Benefits:

Allows you to understand at a glance the variation that exists in a process
The shape of the histogram will show process behavior
Often, it will tell you to dig deeper for otherwise unseen causes of variation.
The shape and size of the dispersion will help identify otherwise hidden sources of variation
Used to determine the capability of a process
The starting point for the improvement process

Check Sheet

Purpose:

Tool for collecting and organizing measured or counted data
Data collected can be used as input data for other quality tools

Benefits:

Collect data in a systematic and organized manner
To determine the source of the problem
To facilitate the classification of data (stratification).

Scatter Diagram

Purpose:

To identify the correlations that might exist between a quality characteristic and a factor that might be driving it
A scatter diagram shows the correlation between two variables in a process.
These variables could be Critical to Quality (CTQ) characteristics and a factor affecting it two factors affecting a CTQ or two related quality characteristics.
Dots representing data points are scattered on the diagram.
The extent to which the dots cluster together in a line across the diagram shows the strength.

Benefits:

Decide which paired factors you want to examine. Both factors must be measurable on some incremental linear scale.
Collect 30 to 100 paired data points.
Find the highest and lowest value for both variables.
Draw the vertical (y) and horizontal (x) axes of a graph.
Plot the data
Title the diagram

The shape that the cluster of dots takes will tell you something about the relationship between the two variables that you tested.

You may occasionally get scatter diagrams that look boomerang- or banana-shaped.

To analyze the strength of the correlation, divide the scatter plot into two sections.
Treat each half separately in your analysis

Benefits:

Helps identify and test probable causes.
By knowing which elements of your process are related and how they are related, you will know what to control or what to vary to affect a quality characteristic.

Control Chart

Purpose:

The primary purpose of a control chart is to predict expected product outcomes.
Statistical tool, showing whether a process is in control or not.
Taking samples of a process and detecting the possibility of the process being out of control

How does it Work?

Define Upper limit, lower limit, and medium value
Draw Chart.
Gather values and draw them into the chart

Benefits:

Predict process out of control and out of specification limits
Distinguish between specific, identifiable causes of variation
Can be used for statistical process control

Strategy for eliminating assignable-cause variation:

Get timely data so that you see the effect of the assignable cause soon after it occurs.
As soon as you see something that indicates that an assignable cause of variation has happened, search for the cause.
Change tools to compensate for the assignable cause.

Strategy for reducing common-cause variation:

Do not attempt to explain the difference between any of the values or data points produced by a stable system in control.
Reducing common-cause variation usually requires making fundamental changes in your process