Transcript what is a control chart?

In the name of Allah,the Most
Beneficient,
Presented by
Nudrat Rehman
Roll# 07-47
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• Chapter 3, Quality Improvement Tools
• Total Quality Management
• by Poornima M Charantimath
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WHAT IS A CONTROL CHART?
A statistical tool used to distinguish between process
variation resulting from common causes and variation
resulting from special causes.
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Common causes
SPECIAL CAUSES
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ELEMENTS OF CONTROL CHART
Each point is usually a
sample statistic (such as
subgroup average) of the
quality characteristic
Center Line represents
mean operating level
of process
LCL & UCL are vital guidelines for
deciding when action should be
taken in a process
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TWO KINDS OF VARIATIONS

Natural Variations:


Due to common causes, purely random, unidentified.
Assignable Variations:

Variability where causes can be identified.
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VARIATIONS
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Developing Control Charts
1. Prepare
– Choose measurement
– Determine how to collect data, sample size, and
frequency of sampling
– Set up an initial control chart
2. Collect Data
– Record data
– Calculate appropriate statistics
– Plot statistics on chart
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3. Determine trial control limits
– Center line (process average)
– Compute UCL, LCL
4. Analyze and interpret results
– Determine if in control
– Eliminate out-of-control points
– Recomputed control limits as necessary
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5. Use as a problem-solving tool
– Continue to collect and plot data
– Take corrective action when necessary
6. Compute process capability
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Out-Of-Control Process
when a sample point (e.g., mean in an X-bar chart)
falls outside the control lines, you have reason to
believe that the process may no longer be in
control.
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Types of Control Charts
Control Charts for Variables
• X-bar chart (mean chart)
• R chart (range chart)
• S chart (Sigma
chart/Standard Deviation)
Control Charts for Attributes
• p chart
• np chart
• c chart
• u chart
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Control Charts for Variables
• X-bar chart:
In this chart the sample means are plotted in order to
control the mean value of a variable (e.g., size of piston
rings, strength of materials, etc.).
• R chart:
In this chart, the sample ranges are plotted in order to
control the variability of a variable.
• S chart:
In this chart, the sample standard deviations(a measure
of the variation between individuals on a variable) are
plotted in order to control the variability of a variable.
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Control Charts for Attributes
• P chart:
In this chart, we plot the percent of defectives (per batch, per
day, per machine, etc.)
• Np chart:
In this chart, we plot the number of defectives (per batch, per
day, per machine) as in the C chart.
• C chart:
In this chart , we plot the number of defectives (per batch, per
day, per machine, per 100 feet of pipe, etc.),but assumes that
defects of the quality attribute
are rare.
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• U chart:
In this chart we plot the rate of defectives, that is, the
number of defectives divided by the number of units
inspected (e.g., feet of pipe, number of batches).
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Advantages of attribute control charts
•
allow quick summaries of various aspects of the quality of a
product
• the engineer may simply classify products as acceptable or
unacceptable, based on various quality criteria. Thus,
attribute charts sometimes bypass the need for expensive,
precise devices and time-consuming measurement
procedures.
• Also, this type of chart tends to be more easily understood by
managers
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Advantages of variable control charts
• Variable control charts are more sensitive than attribute
control charts . Therefore, variable control charts may alert us
to quality problems before any actual "unacceptables" (as
detected by the attribute chart) will occur.
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Control Chart Applications
• Establish state of statistical control
• Monitor a process and signal when it goes out of
control
• Determine process capability
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SELECTION OF CONTROL CHART
Data
Variable
Data
n = 2 to 9
n = 10
or more
X bar
Range Chart
X bar
Sigma Chart
Attribute
Data
n=1
Defectives/
Units
Defects
non-normal
data
normal
data
n fixed
n varies
n fixed
n varies
Run Chart
Individual X
Range Chart
np Chart
p Chart
c Chart
u Chart
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QUESTIONS
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