Statistical Quality Control & SQC Tools

Anjuman-I-Islam’s, Kalsekar Technical Campus Copyright 2016 © Afaqahmed
Prof Afaqahmed M J

Introduction to SQC
•Statistical Process Control (SPC) is a collection
of tools that when used together can result in
process stability and variability reduction
•Statistical Quality Control (SQC) is the term
used to describe the set of statistical tools used
by quality professionals.

 W. Edwards Deming invited Shewhart to speak at the Graduate School of
the U.S. Department of Agriculture, and served as the editor of Shewhart's
book Statistical Method from the Viewpoint of Quality Control (1939) which
was the result of that lecture.
 Deming was an important architect of the quality control short courses that
trained American industry in the new techniques during WWII.
 Deming traveled to Japan during the Allied Occupation and met with the
Union of Japanese Scientists and Engineers(JUSE)in an effort to introduce SQC
methods to Japanese industry
HISTORY

Benefits of Statistical Quality Control
1) It provides a means of detecting error at inspection.
2) It leads to more uniform quality of production.
3) It improves the relationship with the customer.
4) It reduces inspection costs.
5) It reduces the number of rejects and saves the cost of material.
6) It provides a basis for attainable specifications.
7) It points out the bottlenecks and trouble spots.
8) It provides a means of determining the capability of the
manufacturing process.
9) It promotes the understanding and appreciation of quality
control

THE SEVEN MAJOR TOOLS ARE
1) Histogram or Stem and Leaf plot
2) Check Sheet
3) Pareto Chart
4) Cause and Effect Diagram
5) Defect Concentration Diagram
6) Scatter Diagram
7) Control ChartAnjuman-I-Islam’s, Kalsekar Technical Campus Copyright 2016 © Afaqahmed

1. CHECK SHEET
•Manual Graphical Method of data collection
•It collects data in organized manner
•No of defects / sample is generally shown
•It gives acceptable range
•Tick mark is made against defect

HOW TO CONSTRUCT CS
 Define problem / process
 Define suitable period
 Design Check Sheet based on data
 Develop a CS which is easy to understand
 Perform data collection
 Analyze
 Training
 Plotting

2. FLOW CHART
• It shows sequence of operation in a process
• It can be drawn in no. of ways like pictures, symbols, line diagram
etc.
• May be drawn to represent entire process / part of process

Statistical Quality Control & SQC Tools

3. HISTOGRAM
• It shows variation of set of data in pictorial form
• It Displays frequency distribution
• On X- axis  No. of Defects
Y – axis  Frequency of occurrence
• Width of all rectangles is same but height varies
• It shows the pts. where max variation is occurring.

4. PARETO CHARTS
• Based on 20-80 rule based on Vilfredo Pareto 1897
• A small % of any given group (20%) accounts high amount (80%)
• It used to decide order of problems generated in industry to be
tackled.
• 80% of trouble caused by 20% problems
• Shows which defect causes max. rejection

Need
 When analysing data about the frequency of problems or causes in
a process.
 When there are many problems or causes and you want to focus
on the most significant.
 When analysing broad causes by looking at their specific
components.
 When communicating with others about your data.

5. Cause Effect / Fish Bone Diagram/
Ishikawa• How an unaccepted part is produced?
• Analyze the production process against defective part produced.
• Defects may occur due to machine, method, materials, measurement,
men etc.
• Steps
I. Define a problem
II. Select method i.e. CE
III. Draw the problem base and Centre arrow
IV. Specify major sources
V. Identify possible causes
VI. Analysis and Solution

6. SCATTER DIAGRAM
A scatter diagram, also called a scatterplot or a scatter plot, is a
visualization of the relationship between two variables measured on the
same set of individuals.
 Steps involved
1. Select Two factors
2. Collect data in large nos.
3. Draw a graph with independent variable on horizontal axis and dependent
variable on vertical axis.
4. If the data clearly form a line or a curve, you may stop. The variables are
correlated.

7. Control Charts
The control chart is a graph used to study how a
process changes over time. Data are plotted in time
order.
A control chart always has a central line for the
average, an upper line for the upper control limit and a
lower line for the lower control limit.
Lines are determined from historical data. By
comparing current data to these lines, you can draw
conclusions about whether the process variation is
consistent (in control) or is unpredictable (out of
control, affected by special causes of variation).

Control charts help us learn more about processes
•Separate common and special causes of variation
•Determine whether a process is in a state of statistical control or
out-of-control
•Estimate the process parameters (mean, variation) and assess
the performance of a process or its capability

WHEN TO USE A CONTROL CHART?
1. Controlling ongoing processes by finding and correcting
problems as they occur.
2. Predicting the expected range of outcomes from a process.
3. Determining whether a process is stable (in statistical
control).
4. Analyzing patterns of process variation from special causes
(non-routine events) or common causes (built into the
process).
5. Determining whether the quality improvement project
should aim to prevent specific problems or to make
fundamental changes to the process.

X-bar and R charts
•The X-bar chart - used to detect changes in the
mean between subgroups
•tests central tendency or location effects
•The R chart - used to detect changes in variation
within subgroups
•tests dispersion effects

Statistical Quality Control & SQC Tools

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