08 CM0471 Module 8
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Six Sigma Black Belt
Cert. Prep. Course:ControlControlControlControlModule VIII
©2009 ASQ 2
Agenda
This module consists of four lessons:
1. Statistical process control (SPC)
2. Other control tools3. Maintain controls4. Sustain improvements
©2009 ASQ 3
Lesson 1 – Statistical ProcessControl (SPC)
Define and describe the objectives of SPC, includingmonitoring and controlling process performance,
tracking trends, runs, etc., and reducing variation
in a process. (Understand)
VIII.A.1 Statistical Process Control
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©2009 ASQ 4
Statistical Process Control (SPC)
Definition• Using samples (rational subgroups), SPCestablishes the limits of natural variation for a
process.
Dr. Shewhart’s pioneering work in the area of
process analysis enabled generations of qualityengineers to adopt an effective approach to dataanalysis and process monitoring.
• SPC is used by organizations to measureprocesses (not just manufacturing).• It is a feedback system for the “operator” to identifythe need for process intervention.
©2009 ASQ 5
Benefits
• Assure customers that production is consistent over time
• Identify successful process improvement• Increase product consistency
• Maintain product quality
• Reduce the need for inspection
• Increase production yield
Objectives of SPC
• Produce data to inform and guide process improvement
• Reduce variation
• Increase knowledge about the process
• Detect, in real time, occurrences of special causes
Statistical Process Control (SPC)
©2009 ASQ 6
SPC tools achieve the objectives by collecting andanalyzing data
• Control limits are placed on the control chart to show
three standard deviations above and below averageor central line (these are NOT specification limits!)
• Subgroup data taken over time are plotted on the
control chart
• Subgroup statistics (mean/median and standard
deviation) are compared to the control limits to
determine process stability
• Therefore, the control chart is used to help youunderstand the variation in process
Statistical Process Control (SPC)
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©2009 ASQ 7
• Variation can be
– Common cause
– Special (assignable) cause
• Terminology
– “In statistical control” means the processis stable
– “Out of statistical control” means the processis unstable
• Predict the performance of a process using trendsand/or patterns
• Monitor the process as a part of the feedbacksystem directed at continuous improvement.
Statistical Process Control (SPC)
©2009 ASQ 8
• Common Cause
– Variation that is inherent to the system
– Management is responsible for reducing thisvariation
– Values that are located between the controllimits
– When a control chart contains points that arelocated between the control limits only, then
the process is said to be in statistical control(stable).
Common vs. Special Cause of Variation
Statistical Process Control (SPC)
©2009 ASQ 9
• Special Cause
– Variation that is not inherent to the system
– Employees are responsible for determining thesecauses
– Values are located outside the control limits
– Causes for which the reasons can be identified
– When a control chart contains some points thatfall outside of control limits, then the process issaid tonot be in statistical control (not stable).
Common vs. Special Cause of Variation
Basic rule of SPCVariation from common-cause systems should be left to chance,but special causes of variation should be identified and eliminated.
Statistical Process Control (SPC)
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©2009 ASQ 12
Progress Check
Which of the descriptions in the table below are
examples of Statistical Process Control? Check theappropriate box at the right.
Description/Name Example Non-Example
100% inspection (screening) of all production
Recording when assignable (special) causesare detected and taking corrective action
periodically (say, weekly)
Determining the natural variation of a process
Assigning design engineers to maintain SPC
Using samples to determine process stability
©2009 ASQ 14
Identify and select critical characteristics for controlchart monitoring. (Apply)
Lesson 1 – Statistical ProcessControl (SPC)
VIII.A.2 Selection of Variables
©2009 ASQ 15
Selection of Variables
Choosing the characteristic to be charted:• A variable for an SPC chart is selected for
monitoring purposes.
• It is usually the critical dimension / feature of aproduct / service being measured
• Give high priority to characteristics that are currently
running with a high defective rate
• Identify process variables
that contribute to end
product characteristics
SELECT
MEASUREMENT
MEASUREMENT
TYPE
VARIABLE ATTRIBUTE
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©2009 ASQ 16
Choosing the characteristic to be charted:
• Verify that the measurement process has sufficientaccuracy and precision to provide data (Gage R&R)
that does not obscure the variation in the process
• Determine the earliest point in the process at whichdata collection could be done, so that the SPC chart
serves as a warning device
Selection of Variables
SELECT
MEASUREMENT
MEASUREMENT
TYPE
VARIABLE ATTRIBUTE
©2009 ASQ 17
Progress Check
As a group, discuss some historical sourcesthat your organization uses for identifying keycharacteristics for monitoring purposes.
©2009 ASQ 18
Define and apply the principle of rational subgrouping.(Apply)
Lesson 1 – Statistical ProcessControl (SPC)
VIII.A.3 Rational Subgrouping
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©2009 ASQ 19
Rational Subgrouping
Donald J. Wheeler has six guiding principles for subgroupingi n a rational manner.
• Never knowingly subgroup unlike things together
• Minimize variation within each subgroup
• Maximize opportunity for variation between subgroups
• Average across noise, not across signals
• Treat charts in accordance with the use of the data
• Establish standard sampling procedures
Definition
•Rational subgroups are subgroups of data collected underrelatively homogeneous conditions.
•A rational subgroup is a subset of data defined by a specificfactor such as a stratifying factor or a time period.
•Rational subgrouping identifies and separates special causevariation (variation between subgroups) caused by specific,identifiable factors.
©2009 ASQ 21
Rational Subgrouping – Example
A quality engineer (QE) desires to monitor a process
that manufactures PET (plastic) bottles for thebeverage industry. The bottles are injection-moldedon a multi-cavity carousel. The particular carouselcontains four cavities, and the QE initially decides to
take three bottles from each cavity each hour and
measure a criticalcharacteristic. The
data might looklike the table here,where M1, M2,and M3 are thethree measures.
Therewouldbe aseparatecontrolchart for
eachcavity
©2009 ASQ 22
Progress Check
A candy-making process uses 40 pistons to deposit 40chocolate pieces in a 5 x 8 array on a moving sheet of waxpaper. Below are two options that illustrate how a rational
subgrouping of sample size n = 5 may be selected:Option 1: the first five chocolates in each row formed by five
different pistons.Option 2: the upper left-hand chocolate formed in five
consecutive arrays by the same piston.
Check off the optimal box.Use a multi-vari chart to determine
where the variation exists: piece-to-piece(Option 1) or within piece (Option 2)
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©2009 ASQ 23
Select and use the following control charts in varioussituations: X bar-R, X bar-s, individual and movingrange (ImR), p, np, c, u, short-run SPC and moving
average. (Apply)
VIII.A.4 Control Chart Selection
Lesson 1 – Statistical ProcessControl (SPC)
©2009 ASQ 24
Control Charts
• Originated by Walter Shewhart. Also known asShewhart Charts and Statistical Process ControlCharts.
• BenefitsDetection of special or assignable causes ofvariationIdentified by shifts in either location (mean) orspread (standard deviation)
Save money• Uses
Attain a state of Statistical ControlMonitor a processDetermine process capability
©2009 ASQ 25
Types of Control Charts• Attribute Charts• Variable Charts
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©2009 ASQ 26
X-bar and R (X-bar and Range)
X-bar estimates the process central tendency or location(mean) over time and the range (R) estimates the dispersionor process spread (standard deviation) over time.
Classification
Count
RK5
©2009 ASQ 27
Steps for Calculating X-bar and R
1. Collect data by subgroup
2. Calculate the mean for each group
3. Calculate the range for each subgroup
4. Estimate the mean of the population by calculatingthe grand mean.
The subgroup mean is the sum of the samples divided by
the number of samples:n = number of samples
An example has eight subgroups of sample size n = 5
The subgroup range is the maximum value minus the
minimum value:
R = X max – X min
The grand mean is the mean of the subgroup means:
j = number of subgroups
j
X
X
j
1 j j∑
=
=
Note: to establishstatistical process
control, 30 subgroupsof sample size n = 5 aretypically required (eight
subgroups are used
here for simplification)
©2009 ASQ 28
Steps for Calculating X-bar and R5. Calculate the mean of the ranges. R-bar divided by a constant d2 is an
unbiased estimate of the population standard deviation. The constant d2
is part of the constant A2.
6. Find the appropriate A2 value from the table of Control Chart Constants.
7. (See CSSBB Handbook Appendix 4 and 5; pages 463-464)
8. Calculate the UCL and LCL for the Mean
9. Find the appropriate D4 and D3 values from the table of Control Chart
Constants
10. Calculate the UCL and LCL for the Ranges
The mean range is the sum of the ranges divided by the
number of ranges:
j
R
R
j
1 j
j∑=
=
26.361.550.57725.47
RAXUCL 2Mean
=⋅+=
⋅+=
24.581.550.57725.47
RAXLCL 2Mean
=⋅−=
⋅−=
3.281.552.114
RDUCL 4Range
=⋅=
⋅=
0.01.550.0
RDLCL 3Range
=⋅=
⋅=
Note: if the number ofsubgroups is less than20, the table is incorrect
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Slide 26
RK5 what is count pointing to? It looks like it is pointing to a blank are b/t c chart and u chart. Is thatcorrect? Also, is there a way to move that bar to the right side of the slide, so it's not on the tan barrunning along the bottom of the sldie (I don't know how to rotate an arrow if it can be done).Robert Kraus, 12/21/2009
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©2009 ASQ 29
Steps for Calculating X-bar and R
11. Finished
©2009 ASQ 30
Graphing X-bar and R ControlCharts
1. For X-bar Chart, tick off equally spaced subgroups on the X-axis andtick off the UCL centerline (X-double-bar) and the LCL on the Y-axis
2. Use the Grand Mean to draw the Centerline
3. Draw lines for the UCL and LCL
4. Plot the Subgroup Means
5. Connect each point to form a scatter plot with connect lines
6. For R Chart, tick off equally spaced subgroups on the X-axis and tickoff the UCL, centerline (X-double-bar), and the LCL on the Y-axis
7. Use the Range Mean to draw the Centerline
8. Draw a line for the UCL and LCL
9. Plot the Subgroup Ranges
10. Connect each point to form a scatter plot with a connect line
11. Complete the X-bar and Range Chart (display them together)
©2009 ASQ 33
Mean and Standard Deviation(X-bar and S) ChartIn the average and standard deviation chart (X and S), thestatistic used to estimate the subgroup spread is the subgroupstandard deviation.
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©2009 ASQ 34
Steps for calculating X-bar and S(X-bar and Standard Deviation)1. Collect Data by Subgroup. The data shown are collected in
10 subgroups of sample size n = 5.
2. Estimate the population mean for each subgroup.
3. Estimate the population standard deviation for each subgroup.
4. Calculate the Grand Mean.
5. Calculate the mean of the subgroup standard deviations.
6. Find the appropriate A3 value from the table of ControlChart Constants.
7. Calculate the UCL and LCL for the mean.
8. Find the appropriate B4 and B3 values
from the table of Control Chart Constants.
9. Calculate the UCL and LCL forstandard deviation.
10. Finished.
See CSSBB HB,
pages 364 and365 for formulae
©2009 ASQ 35
Steps for Graphing X-bar and S
1. Follow the steps described for the X-bar and R chart.
2. Substitute standard deviation (S) for range (R) whereappropriate.
10987654321
220
210
200
190
180
Sample
S a m p l e M e a n
_ _ X=199.99
UCL=223.24
LCL=176.74
10987654321
40
30
20
10
Sample
S a m p l e S t D e v
_ S=23.85
UCL=40.93
LCL=6.77
Xbar-S Chart of Subgroup Data
©2009 ASQ 39
Individual and Moving Range(I and MR) Chart
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©2009 ASQ 40
Steps for Calculating I-MR(Individual and Moving Range)
1. Col lect data.2. Calculate the moving range between each pair of successive
values.
3. Calculate the mean for the data.
4. Find E2 in the table of Control Chart Constants.
5. Calculate the mean (MR-bar) of the moving range (MR).
6. Calculate the UCL and LCL for the individual observations.
7. Find D3 and D4 in the table of Control Chart Constants.
8. Calculate the UCL and LCL for the moving
range (MR).
9. Fin ished. See CSSBB HB, page 366for formulae
©2009 ASQ 41
Steps for Graphing I-MR Charts
1. For I Chart
• tick off equally spaced intervals for subgroups onthe X-axis.
• tick off equally spaced intervals that include the UCL,centerline (X-bar), and the LCL on the Y-axis.
2. Use X-bar to draw the centerline.
3. Draw lines for the UCL and LCL.
4. Plot the individual observation, X, for each subgroup.
5. Connect each point to form a scatter plot with connectlines.
©2009 ASQ 42
Steps for Graphing I-MR Charts
6. For the MR Chart
• tick off equally spaced intervals for subgroups on theX-axis
• tick off equally spaced intervals that include the UCL,the centerline (MR-bar), and the LCL on the Y-axis.
7. Use MR-bar to draw the centerline.
8. Draw lines for the UCL and LCL.
9. Plot the moving range, MR, for each subgroup.
10. Connect each point to form a scatter plot with connect lines.
11. Complete the I and MR Chart (display I Chart and the MRChart together).
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©2009 ASQ 46
p-Charts
©2009 ASQ 47
Steps for Calculating p-Charts
1. Record data by sample.
2. Calculate the sample totals.
3. Calculate fraction defective (proportion defective) p foreach sample.
4. Calculate the centerline, p-bar, the average fractiondefective (average proportion defective).
5. If one UCL and one LCL are desired (no moving limits),
calculate average sample size.
6. Calculate the UCL and LCL.
7. Finished.See CSSBB HB, page 368for formulae
©2009 ASQ 48
Steps for Graphing p-Charts
1. For the p Chart
• tick off equally spaced intervals for subgroups on theX-axis
• tick of equally spaced intervals that include the UCL,centerline (p-bar), and the LCL on the Y-axis
2. Use p-bar to draw the centerline.
3. Draw lines for the UCL and LCL.
4. Plot the fraction defective, p, for each subgroup.
5. Connect each point to form a scatter plot with connectlines.
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©2009 ASQ 52
np-Charts
©2009 ASQ 53
Steps for Calculating np-Charts
1. Collect the data.
(Example: There are 10 subgroups of 1000 pieces each. Total Defective = 376)1. Calculate the total defectives and total sample size.2. Calculate p-bar.
3. Calculate the centerline, np-bar.4. Calculate the UCL and LCL.
5. Fin ished.
0.037610,000/376Size)Sample(Total/)Defectives(Totalp ===
55.6 0.376)-1(0.03761,000337.6
)p - (1p[n3pnUCL
=⋅+=
+=
19.6 0.376)-1(0.03761,000337.6
)p - (1p[n3pnUCL
=⋅−=
+=
See CSSBB HB, page 370
for formulae
©2009 ASQ 54
Steps for Graphing np-Charts
1. For the np Chart
• Tick off equally spaced intervals for subgroups on theX-axis
• Tick off equally spaced intervals that include the UCL,centerline, and LCL on the Y-axis
2. Use np-bar to draw the centerline.
3. Draw lines for UCL and LCL.
4. Plot the number of defectives by subgroup.
5. Connect each point to form a scatter plot with connect lines.
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©2009 ASQ 57
c and u-Charts
With c- and u-Charts, it is very important to define
the defects and the unit.Examples:
Inspection Unit Type of Defects Counted
50 milesof pipeline
Weld defects
10 yards of cloth Blemishes, snags
50 circuit boardsSolder joint defects, damagedcomponents
100 forms Incorrect data entry, missing data
©2009 ASQ 61
c-Charts
©2009 ASQ 62
Steps to Calculate c-Charts
1. Collect data by subgroup
2. Calculate the total defects
3. Calculate the centerline, c-bar
4. Calculate the UCL and the LCL
5. Finish
See CSSBB HB, page 372for formulae
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©2009 ASQ 63
Steps for Graphing c-Charts
1. For the c Chart
• Tick off equally spaced subgroups on theX-axis
• Tick off equally spaced intervals that included
the UCL, the centerline (c-bar), and the LCLon the Y-axis
2. Use c-bar to draw the centerline.
3. Draw lines for the UCL and the LCL.
4. Plot the number of defects by subgroup.
5. Connect each point to form a scatter plot with
connect lines.
©2009 ASQ 66
u-Charts
©2009 ASQ 67
Steps for Calculating u-Charts
1. Collect data by subgroup: Shipping #, Rolls, and InspectedDefects. Calculate Defects per Roll.
2. Calculate the total rolls shipped.
3. Calculate the total defects.
4. Calculate the centerline, u-bar.
5. Calculate the UCL and LCL for an average sample size of n=1.
38.014
532 u ==
56.5 38.0338.0
1)(n
u3uUCL
=+=
=
+=
19.5 38.0338.0
1)(n
u3uUCL
=−=
=
−=
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©2009 ASQ 68
Steps for Calculating u-Charts
51.1 19.0338.0
2)(n
u3uUCL
=+=
=
+=
24.9 19.0338.0
2)(n
u3uUCL
=−=
=
−=
1. Calculate the UCL and LCL for an average sample size of n=2.
2. Finish.
©2009 ASQ 69
Steps for Graphing u-Charts
1. For the u Chart
• Tick off equally spaced intervals for the subgroups onthe X-axis
• Tick off equally spaced intervals that include the UCL,the centerline (u-bar), and the LCL on the Y-axis.
2. Use u-bar to draw the centerline
3. Draw the UCL and the LCL corresponding to the samplessize for the subgroup (n = 2 for subgroups 5 and 6; n = 1
for all other subgroups).
4. Plot the defects per unit by subgroup.
5. Connect each point to form a scatter plot with connectlines.
©2009 ASQ 72
Short Run SPC• Short-run or low-volume production is common in
manufacturing processes that produce built-to-order productsor quick turnaround production.
• The short-run control chart can also be used in other industriessuch as general services and healthcare when data arecollected infrequently.
• These processes often are so short that not enough data canbe collected to construct standard control charts.
• Statistical process control techniques have been developedto accommodate short-run production for both variables dataand attributes data.
• If possible, collect at
least 20 samples beforeyou construct the controlcharts for shortproduction runs.
See CSSBB HB, pages 376-382 for some examples.
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©2009 ASQ 79
Moving Average and Moving RangeCharts (MAMR)
•See CSSBB HB, pages 383-388for some examples.
•See page 383 for formulae
The moving average and moving range (MAMR)charts provide a graph of the moving average ofa process characteristic and the moving range.Moving averages are common in the financialindustry to analyze stock prices. The 200-day
moving average is the average closing price forthe past 200 trading days. With each new closingprice, a past price is excluded from the data.
©2009 ASQ 80
MAMR Charts
Key Points about MAMR Charts• Use with variable data
• Alternative to Shewhart X and R control charts• May be suitable when it is necessary to detect smaller process
shifts
• Appropriate to use when periodically collecting data• Relevant when it may be desirable to dampen the effects of
over control• Tends to smooth data, easier to spot trends
• Use with stable process mean
• Use time-ordered data• The selection of the moving average length affects the overall
sensitivity of the MAMR chart to detect process shifts.Generally, the longer the length, the less sensitive the chart isto detecting shifts – and, it follows, that a MAMR Chart with alength of two is less sensitive than and I and MR Chart.
©2009 ASQ 89
Progress Check
Check all statements that are true for MA charts:
• You can use MA charts when there are long timeintervals between consecutive results
• You can use MA charts when results are difficult ortime-consuming to obtain
• You can use MA charts when plotted points arecalculated from artificial subgroups created fromconsecutive observations
• The moving averages are independent
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©2009 ASQ 90
Interpret control charts and distinguish betweencommon and special causes using rules fordetermining statistical control. (Analyze)
Lesson 1 – Statistical ProcessControl (SPC)
VIII.A.5 Control Chart Analysis
©2009 ASQ 91
Control Chart Analysis
©2009 ASQ 92
Control Chart Analysis
Rule 1:Any point beyond the control limits is evidence thatthe process is not operating in a state of statistical
control.
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©2009 ASQ 93
Control Chart Analysis
Rule 2:
The second rule is known as a run. Seven or eightpoints in a row above or below the centerline isevidence of a special cause (and therefore theprocess is not stable).
©2009 ASQ 94
Control Chart Analysis
Rule 3:The third rule is called a trend. Six successive
points in an upward or downward direction isevidence that the process is not stable.
©2009 ASQ 95
Control Chart Analysis
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©2009 ASQ 96
Control Chart Analysis
©2009 ASQ 97
Control Chart Analysis
Example 1 – Process out of control
©2009 ASQ 98
Control Chart Analysis
Example 2 – Process in control
37332925211713951
8
7
6
5
4
3
2
1
0
Sample
S a m p l e C o u n t
_ C=2.775
UCL=7.772
LCL=0
C Chart of Blemish
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©2009 ASQ 99
Control Chart Analysis
Example 3 – Process cycling
37332925211713951
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0.00
Sample
P r o p o r t i o n
_ P=0.02575
UCL=0.07327
LCL=0
P Chart of Ding
©2009 ASQ 100
Control Chart Analysis
Example 4 – Process drifting
37332925211713951
20
15
10
5
0
Sample
S a m p l e C o u n t
__ NP=12.05
UCL=21.82
LCL=2.28
NP Chart of Index
©2009 ASQ 101
Control Chart Analysis
Example 5 – Process shifting
37332925211713951
0.30
0.25
0.20
0.15
0.10
0.05
Sample
P r o p o r t i o n
_ P=0.1772
UCL=0.2918
LCL=0.0627
P Chart of M1
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©2009 ASQ 102
Progress Check
©2009 ASQ 103
Progress Check
©2009 ASQ 104
Lesson 2 – Other Control Tools
Define the elements of TPM and describe how it canbe used to control the improved process. (Understand)
VIII.B.1 Total productive maintenance (TPM)
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©2009 ASQ 105
Total Productive Maintenance (TPM)
Total Productive Maintenance
• TPM is a systematic approach for continuousimprovement of maintenance activities having
an impact on the control of a process.
• This strategy’s main goal is to maximize equipmentusefulness across its lifespan.
• TPM increases the Overall Equipment Effectiveness(O.E.E.), a combination of the uptime, cycle timeefficiency, and quality output of the equipment:
– O.E.E. % = Uptime% x Speed% x Quality%
• Note: Speed is also called Efficiency
©2009 ASQ 106
OEE Example: Which shift is better?
–O.E.E. % = Uptime% x Speed% x Quality%
See CSSBB HB, page 401for example.
Total Productive Maintenance (TPM)
©2009 ASQ 107
Progress Check
Calculate OEE, given the following data:
• Downtime = 15%
• Speed = 89%
• Quality = 93%
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©2009 ASQ 108
Define the elements of a visual factory and describehow they can help control the improved process.(Understand)
Lesson 1 – Statistical ProcessControl (SPC)
VIII.B.2 Visual Factory
©2009 ASQ 109
Visual Factory
• Setting up the workplace with signs, labels, color-coded markings, etc. to increase the awarenessof personnel working in different work areas andmultiple shifts to ensure consistency in a process.
• Visual aids help reduce variation in the processwhich can ultimately lead to defects.
©2009 ASQ 110
• Example: The branch network and mail operationsof a bank implemented a color-coded paymentsystem where each type of payment would beassigned a colored bag to ensure proper processing.
Visual Factory
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©2009 ASQ 111
Progress Check – Optional
Discuss the benefits of the following Visual Controls
in a workplace:
• Process metrics are typically displayed at the
machine or cell.
• Andon lights on a machine
• Work instructions posted in the production areas
• Proper placement of parts and tools
©2009 ASQ 112
Lesson 3 – Maintain Controls
Review and evaluate measurement system capabilityas process capability improves, and ensure that
measurement capability is sufficient for its intended
use. (Evaluate)
VIII.C.1 Measurement System Re-analysis
©2009 ASQ 113
Measurement System Re-analysis
• After implementing solutions, we must measure theprocess and determine if it has been improved to astatistically significant degree.
• Various tools such as measurement systemanalysis, process capability analysis, graphicaldata analysis, and statistical testing are used to
answer the question, “Did the improvements have
a statistically significant impact?”
• Statistically validated outcomes will help
demonstrate our process improvements.
• Measurement system capability is re-assessed toensure it remains adequate for the ever-improving
process capability.
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©2009 ASQ 114
Measurement System Re-analysis
Generally unacceptable; every effort should bemade to identify and correct the problem.Customers should be involved in determininghow the problem will be resolved.
Total measurement error of more than 30% oftotal tolerance
Possibly acceptable based on the importanceof the application, cost of the measuringequipment, cost of repairs, etc.
Total measurement error of 10% to 30% oftotal tolerance
Acceptable measuring equipmentTotal measurement error of less than 10% oftotal tolerance
Acceptability% of Measurement Error to Total Tolerance
Guidance for Acceptable ranges of Gauge R&R
©2009 ASQ 118
Develop a control plan for ensuring the ongoing
success of the improved process, including thetransfer of responsibility from the project team tothe process owner. (Apply)
Lesson 3 – Maintain ControlsVIII.C.2 Control Plan
©2009 ASQ 119
Control Plan
• “A control plan is a document describing the systemelements to be applied to control variation ofprocesses, products and services in order to
minimize deviation from their preferred values.”This living document summarizes the necessaryinformation used to explain, monitor and controla product or process and should be updated as
control methods are evaluated and improved.
– Glossary and Tables for Statistical Quality Control ,ASQ Statistics Division
•See CSSBB HB, page 406 for examples.
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©2009 ASQ 120
Control Plan Elements
•Control plans formats vary within industries,organizations, and even departments.•The format or template used for the control plan
is not the key factor; the elements included are.•The following are typical elements and examplesincluded in a control plan.
©2009 ASQ 121
Control Plan Elements - AIAG
“Header information” for the
part/processes being controlled
“Process information” for eachassociated process step
• P lan number
• Prototype/pre-launch/production
• Part/process number
• Suppl ier/plant
• Key contact person, phone
• Team
• Plant approvals, date
• Date developed, last revised
• Customer approvals, e.g.,
• Engineering, date
• Quali ty, date
• O ther , dat e
• Part process step number
• Process name/description
• Machine/device/tools for mfg.
• Characteristics – For eachproduct/process feature,
reference drawing/FMEA/ spec source
• Special “critical/safety/key” issues
• Specification tolerance
• Eval/measurement technique
• Sample size, frequency
• Control method
• Reaction plan
©2009 ASQ 122
Control Plan
Multi-disciplined team
Customer-to-Customer Circle
Product Planning
Product Development Manufacturing
Field Operations
Customer SatisfactionCustomer Satisfaction
Quality, Cost, and DeliveryQuality, Cost, and Delivery
• Gain an understanding of theprocess:
• Cause-Effect matrix
• QFD diagram
• FMEA
• Process maps
• Customer/technical requirements
• Others….
• Develop entries for Control Planform:
• Sources listed above, and…
• Fault tree analysis
• DOE results
• Results of BB studies
• Update Control Plans as needed:
• Process/spec changes
• BB improvements
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©2009 ASQ 123
Progress Check
A company delivers products to the customer for daily “Just inTime” requirements. Each day, the clerk takes several large
containers of products from inventory, loads them on the truck,hauls them to the customer, fills the customer’s smaller containersfrom the large ones, completes the paperwork, and then returnsunneeded quantities to the original inventory. Normally, customerdemand is stable and predictable, but the customer may call for adifferent product mix or large volumes for peak demands.
Assignment: As a group, work together and develop a control planfor the five-step process of :
1. loading the truck with the product2. unloading products into the customer’s JIT bins3. completing the paperwork for delivery/invoicing/inventory4. returning to stock products not left with the customer
5. revising the inventory balance
©2009 ASQ 124
Lesson 4 – Sustain Improvements
Document the lessons learned from all phases ofa project, and identify how improvements can be
replicated and applied to other processes in theorganization. (Apply)
VIII.D.1 Lessons learned
©2009 ASQ 125
Lessons Learned
• A Six Sigma project generates a wealth of information.
• Establishing a process to capture, document, and sharelessons learned infuses change in the organization.
• Document the knowledge and experience gained bycarrying out various projects in an organization.
• Ask and document the answers to the followingquestions:
– What went well?
– What could have been done differently?
– What could be improved?
– What did we do that we should not have?
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©2009 ASQ 126
Lessons Learned
– Did all our various stakeholders interact
efficiently and effectively?
– Where were the gaps?
– Where were the overlaps?
– What can be done differently next time to make
the situation easier for all parties involved?
• Once captured, project information can be searchedand compared against future project opportunities
• Decisions can then be made to charter a project,replicate a past success, or kick-start innovativethinking on a new or an existing project
©2009 ASQ 127
Progress Check
• As a team, discuss the benefits of conducting a“Lessons Learned” from all the phases of a SixSigma project
©2009 ASQ 128
Develop and implement training plans to ensurecontinued support of the improved process. (Apply)
Lesson 4 – Sustain Improvements
VIII.D.2 Training Plan Deployment
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©2009 ASQ 129
Training Plan Deployment
Initial Training:
• This type is used for existing employees who havebeen responsible for executing the old process and
employees who are new to the process.
• It may be conducted either off-the-job, on-the-job,or both.
• Criteria is based on skill levels required, processcomplexity, and experience levels, among otherfactors.
• Initial training serves to calibrate employees and to
minimize variation in how the process is performed.
©2009 ASQ 130
Recurring Training
• This type is used to minimize deterioration in the
process performance over time.
• Specific facts, details, and nuances are frequentlyleft out as knowledge is passed on from worker
to worker.
• Restores the process execution to its original design.
• The frequency of recurring training should bedetermined based on process metrics and employeeperformance.
• Such training may be offered at specified intervalsor conducted as required to serve the needs of
underperforming employees.
Training Plan Deployment
©2009 ASQ 131
Considerations when developing training plans:
• Providing employees with the minimum skillsand information needed to perform the functions
required by the position.
• Providing employees with additional skills and
information that will assure a broader view of
what the position accomplishes for the enterprise.
• Providing employees with cross-training for
additional functions.
Training Plan Deployment
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©2009 ASQ 132
Other Considerations:
• Providing employees with opportunities for furthereducation outside the enterprise on topics not
directly related to the current organization needs.
• Providing incentives and requirements that motivateemployees to continue to seek education and
training opportunities.
• Providing employees with experiences thatdemonstrate the need the organization has for
their continuous improvement ideas.
• Providing employees with the opportunity to helpformulate a customized annual training plan.
Training Plan Deployment
©2009 ASQ 133
Progress Check
• As a team, discuss the method used by yourorganization for deploying training.
• What are some of the things that the organization
could consider when developing and deployingtraining?
©2009 ASQ 134
Progress Check
• Write down and discuss the “three most importantthings you learned at work” that is related to your job performance:
• How did you learn them? Next to each thing youlearned, note what you did to learn it. Do you know?Did it occur in a classroom? What was the reasonthat triggered the training?
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©2009 ASQ 135
Develop or modify documents, including standard
operating procedures (SOPs), work instructions, etc.,
to ensure that the improvements are sustained overtime. (Apply)
Lesson 4 – Sustain Improvements
VIII.D.3 Documentation
©2009 ASQ 136
Documentation
Considerations for developing and updatingdocuments:
• Documented standard operating procedures (SOPs)
and work instructions help reduce process variation.
• The purpose of these documents is to make certainthat the activity is performed the same way over
time.
• This is especially important when multi-skilled,cross-trained personnel move into a variety of
positions.
©2009 ASQ 137
DocumentationConsiderations for developing and updating documents:• The development and updating of these documents must
involve the people who perform the work.
• Documents must be kept current.• Employees need to have access to the appropriate
documentation based on effectivity of the change.• Multiple formats for documentation exist (SOPs/WI/
templates, etc.).• Choose the right format for documentation.
– The right choice depends on how the documentation is tobe used, by whom, and at what skill level.
– Develop documents that utilize pictures, graphics, and arelight on words – or no words when there is more than onelanguage in the work force.
– Level of detail provided in any set of documentation shouldbe reflective of the skills and education levels of thepersonnel doing the actual work and the degree to whichvariation must be controlled.
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©2009 ASQ 138
Progress Check
• As a team, discuss the various types of documents
that are controlled by your organization.
• What is the method used to ensure that personnelare using the most effective version required for thework being performed?
©2009 ASQ 139
Identify and apply tools for ongoing evaluation ofthe improved process, including monitoring for new
constraints, additional opportunities for improvement,etc. (Apply)
Lesson 4 – Sustain Improvements
VIII.D.4 Ongoing Evaluation
©2009 ASQ 140
Ongoing Evaluation
Tools such as control charts, process capabilitystudies, and process metrics:
• Control charts – These are used to monitor thestability of the process, determine when specialcause is present, and when to take appropriateaction.
• Process capability studies – These studies provideus with the opportunity to understand how the voiceof the process (i.e., control limits) compares with the
voice of the customer (i.e., specifications).
• Process metrics – This includes a wide variety of in-process and end-of-process metrics that measure
its overall efficiency and effectiveness.
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©2009 ASQ 141
Progress Check
As a group, discuss how your organization selects
and uses a tool for ongoing evaluation, once theprocess has been improved.
©2009 ASQ 142
Module Status
1. Statistical process control (SPC)
2. Other control tools3. Maintain controls4. Sustain improvements
©2009 ASQ 143
Module 8
Exercise Solutions
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©2009 ASQ 144
Answer
Which of the descriptions in the table below are
examples of Statistical Process Control? Check theappropriate box at the right.
Description/Name Example Non-Example
100% inspection (screening) of allproduction
X
Recording when assignable (special) causesare detected and taking corrective action
periodically (say, weekly)
X
Determining the natural variation of a
process
X
Assigning design engineers to maintain SPC X
Using samples to determine process stabil ity X
©2009 ASQ 145
Answer A candy-making process uses 40 pistons to deposit 40
chocolate pieces in a 5 x 8 array on a moving sheet of waxpaper. Below are two options that illustrate how a rational
subgrouping of sample size n = 5 may be selected:Option 1: the first five chocolates in each row formed by five
different pistons.Option 2: the upper left-hand chocolate formed in five
consecutive arrays by the same piston.
Check off the optimal box.Use a multi-vari chart to determine
where the variation exists: piece-to-piece(Option 1) or within piece (Option 2)
Answer: Option 2:
©2009 ASQ 146
Answer
Check all statements that are true for MA charts:
• You can use MA charts when there are long timeintervals between consecutive results. True
• You can use MA charts when results are difficult ortime-consuming to obtain. True
• You can use MA charts when plotted points arecalculated from artificial subgroups created fromconsecutive observations. True
• The moving averages are independent. False
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©2009 ASQ 147
Answers
Answers:1. D
2. C3. C
©2009 ASQ 148
Answers
Answers:
4. B5. B
©2009 ASQ 149
Answer
Calculate OEE, given the following data:
• Downtime = 15%
• Speed = 89%
• Quality = 93%
Answer:
O.E.E. % = Uptime% x Speed% x Quality%
If Downtime = 15%; then Uptime = 100-15 = 85%
OEE = .85* .89 * .93 = .7053 = 70.35%