Transcript chap7_2010

Chapter 7
Quality Tools
Which tool is best?
• Tools can serve as the backbone for virtually any
type of quality improvement effort (Six Sigma,
TQM, 8D)
• Graphical representations of data help us
understand the true importance of data.
• There is no single one-size fits all solution. Every
project and problem is different.
Diagnostic Tools
• Graphical Tools:
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–
–
–
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Histogram
Boxplots
Probability distribution plots
Main-effects plots
Pareto charts
Run charts
Multi-Vari charts
Time-series plots
Scatter plots
• Analytical Tools:
– Cause-Effect (CE) diagram
– Failure mode-effects Analysis
(FMEA)
– XY matrix
– Affinity diagram
– Fault tree analysis (FTA)
Diagnostic Tools
• Graphical Rep. of
Process:
–
–
–
–
–
Process flow charts
Process mapping
Cross-functional mapping
Deployment diagram
Supplier-input-processoutput-customer (SIPOC)
diagram
– Input-process-output (IPO)
diagram
– Force-field analysis
• Other Tools:
– Checksheets
– Scorecards
Problem Definition
• A good problem definition will include quantified information
about the problem, the magnitude of the problem, the
baseline, and the gap remaining to reach a benchmark or
desired state
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–
–
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Be Specific
Use declarative format
Quantify
Be factual
• Example of poor problem definition: “Reduce restorable time for severity 1
telephone banking problems, focusing on human errors as root cause”
• Example of good problem definition: “Reduce restorable time from 51% per
month for severity 1 telephone banking problems to 30% or less per month by
the third quarter of this year, resulting in annual savings of $4.5M”
Y = f (x)
•
•
•
x1
The transfer equation of Y=f(x) where X =x1, x2, x3,…,xn recognizes that a
causal relationship exits in any process of action performed.
Y is a function of one or many x’s where Y is the dependent variable and the
x’s are independent variables.
X can equal quality, delivery time, cost of the product. Therefore Critical to
Satisfaction refers to any variable that has significant influence on one of more
of the determinants of customer satisfaction.
x2
x3 . . . . xn
Inputs
» Pareto principal suggests that 80% of the of the total error or variance will be
caused by 20% of the variables. These are the “vital few”, while the remaining
are the “trivial many”. The key is to identify these vital few.
Process
...
Uncontrollable variables or factors (noise)
Critical-to (CT) Definitions
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•
•
•
Critical-to-Satisfaction (CTS) characteristics – expression of the customer’s vital needs.
Critical-to-Quality (CTQ) characteristics- the product, service and/or transactional
characteristics that significantly influence one or more CTS in terms of quality.
Critical-to-Delivery (CTD) characteristics- “
“
“
“ in terms of delivery.
Critical-to-Cost (CTC) characteristics“
“
“
“
in terms of cost.
Critical to Satisfaction
Delivery
CTD
Variables (X)
•
CTD
Quality
CTD
Price
CTQ
CTQ
CTQ
CTP
CTP
CTP
CTC
CTC
CTC
Critical-to-Process (CTP) characteristics- Process parameters that significantly influence a
CTQ, CTD, and/or CTC.
The Leverage Principle
• Not all X variable affect the outcome (Y) equally.
• In Six Sigma process:
• Identify the variables that exert strong influence (Vital Few).
• Then we must focus on controlling these variables. Design of
Experiments (DOE) is used to achieve this objective.
Y
X (x1, x2, x3,…,xn )
Dependent
Independent
Output
Input-process
Effect
Cause
Symptom
Problem
Monitor
Control
The Leverage Principle
(Variation Reduction Strategies)
Strategy
1 2 3 4 5 6
Total Red.
Efforts
Total
% Impr.
Baseline
4 11
3
2
1
1
--
12.33
Reduce each by 1
3 10
2
1
0
0
6
10.68
13.4%
Eliminate all but one
0 11
0
0
0
0
11
11.00
10.8%
Reduce the vital one
4
3
2
1
1
3
9.75
20.9%
 Total 
6
2

 j
j 1
8
What does measurement mean?
• Concept of measurement: seek to compare or
contrast a physical attribute of something to a rational
and invariant standard  performance gap
• Seek to quantify such gaps for purposes of
communications, verification, and analysis.
• Measure subjective matter (customer satisfaction)
through surveys, questionnaires
• Measure physical characteristics, time characteristics,
defect rates….
How do we know if customers are happy?
Goal is to understand how to better satisfy the customer
•
Survey design considerations:
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•
Types of question formats:
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•
Closed-ended (yes/no)
Rating scales
Open-ended questions / probes
Other considerations:
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•
Length (not too long)
Appearance (simple, not busy)
Types of questions (statements of fact or measures of performance or importance)
Focus on one theme
Usually best to include a midpoint in rating scales (i.e. odd number)
Try to solicit feelings toward your competitors.
Identify specific target control groups:
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– Follow up with a friendly collection strategy
At least 10% of customer base
– Develop action plans that are based on results
Stratify various customer segments
– Communicate results to customers
Give prior notice, before delivering survey
– Follow up with repeat surveys to monitor
Personalize the survey and cover letter
changes over time
Address confidentiality
Offer an incentive or token of appreciation for completion
Likert scale
• A subjective scoring system that allows a person being surveyed to
quantify likes and preferences on a 5-point scale, with 1 being the least
important, relevant, interesting, or other, and 5 being most excellent,
important, etc
• Strongly Agree / Agree / Undecided / Disagree / Strongly Disagree
• Very Frequently /Frequently /Occasionally /Rarely /Very Rarely /Never
• Very Important / Important / Moderately Important / Of Little Importance /
Unimportant
• Excellent / Above Average / Average / Below Average /Extremely Poor
• Almost Always True / Usually True / Often True / Occasionally True /
Sometimes But Infrequently True / Usually Not True / Almost Never True
Continuous Scales
• Linear Scale: A scale with equal
divisions for equal values
7000
6000
5000
4000
3000
2000
1000
0
0
10
20
30
40
50
Forecast Period (in Months)
60
•
If the data are nonlinear (i.e., with a
very wide range of values), then a
logarithmic scale (in this case base
10) may be more appropriate.
Analytical Tool:
Cause-Effect (CE) Analysis
• CE diagram (fishbone diagram) uses collective knowledge
to identify the main causes (x) of the effect (y) under study.
– Manufacturing diagrams (Six M’s: measurement, manpower,
machines, materials, methods, and mother nature).
– Transactional diagrams (4 P’s :Policies, procedures, personnel,
environment).
• Graphical way to show relationships between inputs and
outputs.
• Label each cause with a “C” (fixed variable), “N” (Noise) or
“X” (experimental independent variable.)
• CE Diagrams can be constructed using MINITAB (page
156-157)
Cause-Effect (CE) Analysis
www.syncfusion.com/.../img/Fishbone_larger.png
Analytical Tool: Failure Mode –
Effects Analysis (FMEA)
• Used to assess risks from potential product , service,
transaction or process failure modes.
• Widely used in the Analyze and Improve phase, can also be
used in Control phase.
• Helpful to assist in:
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–
–
–
Improving or designing more robust products, services & processes
Designing safer products and processes
Designing safer delivery systems
Receiving fewer complaints and reducing the organization’s
guarantee costs
– Creating fewer problems or minimizing them in everyday business
processes
– Provide improvement teams with prioritized causes and identifying
which causes need to be eliminated urgently.
How does FMEA work?
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•
Focus on Severity, Occurrence and Detectability of each process. Then
calculate the the Risk Priority number (RPN)
Each organization can define their own scale (1-10, 1-5… )as long as they
are consistent across the organization.
Example of FMEA analysis for Auto manufacturer
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Start with a grid to define the potential failures
Product or
Process
Failure Mode
Failure Effects
Engine
Overheat
Engine Damage
Battery
Doesn't retain
charge
Car doesn't start
Brakes
Brake failure
Can't STOP car
S
E
V
Causes
O
C
C
Controls
D R
E P
T N
P
S
Actions
Plans
P P
O D
P
RN
P
FMEA
Severity, Occurrence & Detectability
Rating
1
2
Criteria
Is not noticed by anybody, has no
effect
Is not noticed, has only an insignificant
effect
3
Causes only small irritations
4
Modest loss of performance
SEVERITY
Fall in performance level; consequence
is customer's complaints
Fall in performance level that disturbs
the capacity to function
Disturbed capacity function that leads
to an increase in customer
dissatisfaction
Product or
Process
Failure Mode
Failure Effects
Engine
Overheat
Engine Damage
Battery
Doesn't retain
charge
Car doesn't start
8
Product or service becomes useless
Brakes
Brake failure
Can't STOP car
9
Product or service is illegal
10
Customer or employee is injured or
killed.
5
6
7
S
E
V
Causes
O
C
C
C
FMEA
Severity, Occurrence & Detectability
Rating
Criteria
Probability
1
Once every 6-100 yrs
<2/1,000,000,000
2
Once every 3-6 yrs
<3/10,000,000
3
Once every 1-3 yrs
<6/1,000,000
4
Once a year
<6/100,000
Product or Failure
5
Once every 6 months
Process
Mode
<1/10,000
6
Once every 3 months
<0.33%
Engine
7
Once a month
<1%
8
Once a week
Battery
<5%
9
Every 3 to 4 days
Brakes
<30%
10
More than once a day
>30%
Overheat
Doesn't
retain
charge
OCCURANCE
Failure
Effects
Engine
Damage
Car doesn't
start
Can't STOP
Brake failure car
S
E
V Causes
Radiator
8 hose worn
Dry/dead
8 battery
worn
10 brakepads
O
D R
C
E P
C Controls
T N Actions
Check
5 frequently
Service
4 History
Replace
2 worn pads
FMEA
Severity, Occurrence & Detectability
Rating
1
Criteria
The cause of the failure is obvious and can be
hindered simply
2
All units are to be inspected automatically
3
Statistical process controls with a systematic
failure cause test and corresponding Actions
4
Statistical process controls are to be conducted
with a systematic failure cause test.
5
Statistical process controls are to be conducted
6
or Failure
All units are to be inspectedProduct
manually
and
Process
Mode
avoidance actions installed
7
All units are to be inspectedEngine
manuallyOverheat
Doesn't
8
9
10
retain
Manual inspections are to be conducted
Battery
charge
frequently
Manual inspections are to be conducted
Brakes
Brake failure
occasionally.
The defect caused by the failure is not
detectable
PROBABILITY OF DETECTION
• Risk Priority number (RPN) is
calculated by multiplying
Severity x Occurrence x Detectabillity
Failure
Effects
Engine
Damage
S
E
V Causes
Radiator
8 hose worn
Car doesn't
start
Can't STOP
car
Dry/dead
8 battery
worn
10 brakepads
O
D
C
E
C Controls
T
Check
5 frequently 1
Service
4 History
Replace
2 worn pads
1
8
R
P
N
Actions
Replace
40 Radiator Hose
32 Change Battery
Revise Brakes
160 frequently
Analytical Tool: XY Matrix
• XY matrix allows everyone involved with a process to agree on
output (y’s) critical to the survey, transaction and/or customer.
• Matrix allows the team to assign the level of importance of each
variable (x) to the output (y).
• EXAMPLE of XY matrix as relates to a coffee house.
INPUT VARIABLES (X)
OUTPUT VARIABLES (Y)
Flavor
Aroma
Price
Acidity RANK
Rankings
10
10
10
2
Coffee Type
Coffee Amount
Grind Time
Water Temp
Cup Type
Cup Size
Brew Time
10
9
9
9
2
2
9
10
7
6
3
4
4
6
10
10
2
2
4
5
2
10
10
3
2
2
1
2
320
280
176
144
104
112
174
1310
%RANK
24.4%
21.4%
13.4%
11.0%
7.9%
8.5%
13.3%
• If the results/ranking were generated during a brainstorm session
than they should be verified based on actual data.
Graphical Tool: Pareto Charts
•
•
•
Pareto charts help
identify the top factors
(“vital few”)
Order X in descending
order.
Add a line showing
cumulative % of total.
Based on this which
inputs would you focus
on to insure customer
satisfaction?
Coffee Pareto Chart
1400
100.0%
90.0%
1200
RANK
•
80.0%
1000
70.0%
800
60.0%
50.0%
600
40.0%
400
30.0%
20.0%
200
0
10.0%
Coffee
Type
Coffee
Amount
Grind
Time
Brew
Time
Water
Temp
Cup Size
Cup
Type
320
280
176
174
144
112
104
Percentage
24.4%
21.4%
13.4%
13.3%
11.0%
8.5%
7.9%
Cumulative %
24.4%
45.8%
59.2%
72.5%
83.5%
92.1%
100.0%
Count
0.0%
Graphical Tool:
Histogram with Normal Curve
university-software.com/NormalHist.jpg
Graphical Tool:
Histogram with Normal Curve
Minitab:
Calc
Random Data
Integer
Stat
Basic Statistics
Graphical Summary
Graphical Tool:
Boxplot
• Minimum
• Maximum
• Median
• First Quartile
• Third Quartile
Minitab:
Stat
Basic Statistics
Display Descriptive..
• Boxplot
Graphical Tool:
Probability Plot
Minitab:
Graph
Probability Plot
• Single
Graphical Tool:
Main-Effects Plot
• Main-effects plot graphically compares the level of a
process output variable at various states of process
factors
• Lines with steeper slopes have larger impact on the
output compared to those lines with little or no slope
• Used to present result from analysis of variance
(ANOVA)
• Use to examine the level means for each factor,
compare the level means for several factors and
compare the relative strength of the effects across
factors
Graphical Tool:
Main-Effects Plot
MINITAB
STAT
ANOVA
Main Effect Plot
Input
X1
0
1
X2
0
1
X3
0
1
Output
60
83
72
71
74
69
Graphical Tool:
Run Chart
• A line graph of data points plotted in chronological
order that helps detect special causes of variation
–
–
–
–
Understand process variation
Analyze data for patterns
Monitor process performance
Communicate process performance
Graphical Tool:
Run Chart
www.pqsystems.com/.../chart_BasicRunChart.png
Graphical Tool:
Time-Series Plot
• A time series plot is a graph showing a set of
observations taken at different points in time and
charted in a time series.
– Outliers: values that do not appear to be consistent with
the rest of the data
– Discontinuities: a break or gap in a process that would
normally be continuous
– Trends: a general tendency in movement or direction
– Periodicities: any recurrence at regular intervals
Graphical Tool:
Time-Series Plot
cookbooks.opengrads.org/images/3/3b/Precip_ti..
Graphical Tool:
Multi-Vari Charts
• Show patterns of variation from several possible
causes on a single chart, or set of charts
• Obtains a first look at the process stability over
time. Can be constructed in various ways to get
the “best view”.
– Positional: variation within a part or process
– Cyclical: variation between consecutive parts or process steps
– Temporal: Time variability
Graphical Tool:
Multi-Vari Charts
Cus. Size
Product
Cus. Type
Satis.
1
1
2
3.54
2
1
3
3.16
Cus. Size: 1 = small
2 = large
1
2
2
2.42
Product:
2
2
2
2.70
1
1
3
3.31
2
1
2
4.12
2
2
1
3.24
2
2
2
4.47
2
1
2
3.83
1
1
1
2.94
http://www.qimacros.com/qiwizard/multivari-chart.html
1 = Consumer
2 = Manuf.
Cus. Type: 1 = Gov’t
2 = Commercial
3 = Education
Graphical Tool:
Multi-Vari Charts
Minitab:
Stat
Quality Tool
Multi Vari C
Graphical Tool:
Scatter Plot
• Show patterns of variation from several possible
causes on a single chart, or set of charts
• Obtains a first look at the process stability over
time. Can be constructed in various ways to get
the “best view”.
– Positional: variation within a part or process
– Cyclical: variation between consecutive parts or process steps
– Temporal: Time variability
Graphical Tool:
Scatter Plot
http://mste.illinois.edu/courses/ci330ms/youtsey/scatterinfo.html
Graphical Tool:
Scatter Plot
http://mste.illinois.edu/courses/ci330ms/youtsey/scatterinfo.html
Graphical Tool:
Scatter Plot
http://mste.illinois.edu/courses/ci330ms/youtsey/scatterinfo.html
Graphical Tool:
Scatter Plot
http://mste.illinois.edu/courses/ci330ms/youtsey/scatterinfo.html
Graphical Tools for Process Rep.:
Process Flowcharts
• Visual representation of the major process steps.
• Useful to compare “as is” with “should be” process.
1.
2.
3.
4.
5.
Determine the limits of the process. Clearly define where it begins & ends.
Determine the steps in the process
Put the steps into sequence
Draw the flow using standard symbols. Add arrows to show flow direction.
Verify the flow is complete. Is every feedback loop complete?
Standard symbols:
Stop/ Start
Decision Point
Activity
Connector (to another page or diagram)
Graphical Tools for
Process Rep.:
Process Flowcharts
www.breezetree.com/.../8D
-process-flowchart.png
Graphical Tools for Process Rep.:
Process Mapping
• Process mapping is a workflow diagram to bring forth a
clearer understanding of a process or series of parallel
processes
• Cross-Functional Mapping
• “As-is” vs. “To-be”
Graphical Tools for Process Rep.:
Process Mapping
www.oregon.gov/.../images
/iGrafx_Process_Map.JPG
Graphical Tools for Process Rep.:
SIPOC Diagram
• Supplier-Input-Process-Output-Customer diagram.
• A high-level picture of the process that depicts how the
given process is servicing the customer.
• Useful to discover customer “pain points”
• Identify key Y’s an X’s with project team.
Suppliers
Inputs
Machine
manufacturer
Bean supplier
Filter supplier
Cup supplier
Coffee beans
Water
Filter
Cup
Brewing
machine
Process
Outputs
Customers
Insert simple flow-chart here
Coffee
Espresso
Repeat (daily)
New
Graphical Tools for Process Rep.:
SIPOC Diagram
http://www.ptm-consulting.it/immagini/sipoc.jpg
Graphical Tools for Process Rep.:
IPO Diagram
• Input-Process-Output diagram is another visual rep. of a
process activity. Based on the transfer equation y=f(x)
Fixed Variables (C)
Process X’s
x1=Forecast
x2=Buyer
X3 =AVL
x4=BOM
x5=LT
x6=Market Dollar Value
Process
Program Management
Noise Variables(N)
Y=Lack of materials supplies
Graphical Tools for Process Rep.:
SIPOC Diagram
http://www.variancereduction.com/newsletters/images/9.6.16.jpg
Other Tools:
Force-Field Analysis
• Force-Field Analysis was developed by Lewin (1951) and is
widely used to inform decision-making, particularly in
planning and implementing change management programs
in organizations.
• It is a powerful method for gaining a comprehensive
overview of the different forces acting on a potential policy
issue, and for assessing their source and strength.
Force
-Field
Analysis
Other Tools:
Matrix Analysis
• Technique for finding new combinations of products
or services.
– List the attributes of the product, service or strategy
– Draw up a table using these attributes as column
headings
– Write down as many variations of the attribute as possible
within these columns.
– Select one entry from each column. By mixing one item
from each column, you will create a new mixture of
components. This is a new product, service or strategy.
– Finally, evaluate and improve that mixture to see if you
can imagine a profitable market for it.
Other Tools:
Matrix Analysis
http://www.mindtools.com/pages/article/newCT_03.htm
Other Tools:
Checksheets
• A check sheet is a structured, prepared form for
collecting and analyzing data
– Decide what event or problem will be observed. Develop operational
definitions.
– Decide when data will be collected and for how long.
– Design the form. Set it up so that data can be recorded simply by
making check marks or Xs or similar symbols and so that data do not
have to be recopied for analysis.
– Label all spaces on the form.
– Test the check sheet for a short trial period to be sure it collects the
appropriate data and is easy to use.
– Each time the targeted event or problem occurs, record data on the
check sheet.
Other Tools:
Checksheets
http://www.asq.org/learn-about-quality/datacollection-analysis-tools/overview/check-sheet.html
Other Tools:
Scorecards
• A balanced scorecard is a central list of numbers,
which show each key part of an organization's
success, such as financials, people, operations,
suppliers, customers, and support systems.
• The numbers should measure not just important
outcomes, but also the factors which influence, or
drive, those outcomes.
Other Tools:
Scorecards
www.jiscinfonet.ac
.uk/.../scorecard
Other Tools:
Affinity Diagram
• The affinity diagram organizes a large number of
ideas into their natural relationships
– Record each idea with a marking pen on a separate sticky
note or card. Randomly spread notes on a large work
surface so all notes are visible to everyone.
– Look for ideas that seem to be related in some way. Place
them side by side. Repeat until all notes are grouped.
– Participants can discuss the shape of the chart, any
surprising patterns, and especially reasons for moving
controversial notes. When ideas are grouped, select a
heading for each group.
– Combine groups into “supergroups” if appropriate.
Other Tools:
Affinity Diagram
http://www.asq.org/learnabout-quality/ideacreationtools/overview/affinity.html
Affinity
Diagram
http://www.asq.org/learnabout-quality/ideacreationtools/overview/affinity.html