1. Introduced in 1926 by WALTER SHEWART, who concluded that a
distribution can be transformed into normal shape by estimating
mean and standard deviation. Control chart is a device which
specifies the state of statistical control. Control chart detects
the variation in processing and warns if there is any deviation
from the specified tolerance limits. The purpose of using control
chart is to stabilize process by keeping it under control and
carrying out necessary adjustments (on line). 8/1/2015 2
2. A control chart indicate whether the process is in control
or out of control. It determines the process variability and
detects unusual variations in a process. It ensures product quality
level. It warns in time and if process is rectified at that time
percentage of rejection can be reduced. It provides information
about selection of process and setting up of tolerance limits.
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3. CONTROL CHART VARIABLE CONTROL CHART X- BAR & R CHART
X-BAR & S CHART X & m R CHART ATTRIBUTE CONTROL CHART
PERCENTAGE OF DEFECTS 1.P-CHART 2.np- CHART NO OF DEFECTIVIES
1.C-CHART 2.U-CHART 8/1/2015 4
4. No two natural items in any category are the same. Variation
may be quite large or very small. If variation very small, it may
appear that items are identical, but precision instruments will
show differences. 8/1/2015 5
5. Within-piece variation One portion of surface is rougher
than another portion. A piece-to-piece variation Variation among
pieces produced at the same time. Time-to-time variation Service
given early would be different from that given later in the day.
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6. Equipment Tool wear, machine vibration, Material Raw
material quality Environment Temperature, pressure, humidity
Operator Operator performance- physical & emotional 8/1/2015
7
7. Variation due to Common or chance causes Assignable causes
8/1/2015 8 Control chart may be used to discover assignable
causes
8. Control charts are powerful aids to understanding the
performance of a process over time. 8/1/2015 9 PROCESS Input Output
Whats causing variability?
9. Chance causes - common cause inherent to the process or
random and not controllable if only common cause present, the
process is considered stable or in control Assignable causes -
special cause variation due to outside influences if present, the
process is out of control 8/1/2015 10
10. 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 8/1/2015
11
11. To monitor output, we use a control chart we check things
like the mean, range, standard deviation To monitor a process, we
typically use two control charts mean (or some other central
tendency measure) variation (typically using range or standard
deviation) 8/1/2015 12
12. Variable data Product characteristic that can be measured
Length, size, weight, height, time, velocity Attribute data Product
characteristic evaluated with a discrete choice Good/bad, yes/no
8/1/2015 13
13. 8/1/2015 14
14. A single measurable quality characteristic ,such as
dimension, weight, or volume, is called variable. Since statistical
control for continuous data depends on both the mean and the
variability, variables control charts are constructed to monitor
each. The most commonly used chart to monitor the mean is called
the X-BAR chart. There are two commonly used charts used to monitor
the variability: the R chart and the S chart. 8/1/2015 15
15. X-BAR Chart: This chart is called the X-BAR chart because
the statistic being plotted is the sample mean. The reason for
taking a sample is because we are not always sure of the process
distribution. By using the sample mean we can "invoke" the central
limit theorem to assume normality. 8/1/2015 16
16. R Chart The R chart is used to monitor process variability
when sample sizes are small (n20), compute the control limits for
the charts. The following additional calculations will be
necessary: 8/1/2015 21
21. V. If any points fall outside of the control limits,
conclude that the process is out of control, and begin a search for
an assignable or special cause. When the special cause is
identified, remove that point and return to step 4 to re-evaluate
the remaining points. VI. If all the points are within limits,
conclude that the process is in control, and use the calculated
limits for future monitoring of the process. 8/1/2015 22
22. EXAMPLE PROBLEM A large hotel in a resort area has a
housekeeping staff that cleans and prepares all of the hotel's
guestrooms daily. In an effort to improve service through reducing
variation in the time required to clean and prepare a room, a
series of measurements is taken of the times to service rooms in
one section of the hotel. Cleaning times for five rooms selected
each day for 25 consecutive days appear below: Day Room 1 Room 2
Room 3 Room 4 Room 5 1 15.6 14.3 17.7 14.3 15 2 15 14.8 16.8 16.9
17.4 3 16.4 15.1 15.7 17.3 16.6 4 14.2 14.8 17.3 15 16.4 5 16.4
16.3 17.6 17.9 14.9 6 14.9 17.2 17.2 15.3 14.1 7 17.9 17.9 14.7 17
14.5 8 14 17.7 16.9 14 14.9 9 17.6 16.5 15.3 14.5 15.1 10 14.6 14
14.7 16.9 14.2 8/1/2015 23
25. CALCULATE THE CONTROL LIMITS 15.94 2.7 1.14 X R s x Chart
Control Limits UCL = x + A R LCL = x - A R 2 2 R Chart Control
Limits UCL = D R LCL = D R 4 3 X-BAR , R CHART X- BAR ,S CHART
8/1/2015 26
26. TABLE FOR CONSTANTS SQC A MODERN INTRODUCTION 6th Edition,
D.C. Montgomery 8/1/2015 27