• Module 24 – QE Software Tutorial 1a


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    • Abstract: Module 24 – QE Software Tutorial 1aQE Tools Software TutorialPart I – Getting Started, Tool RoadMap,Cause-and-Effect Diagrams, Measure PhaseQETOOLSAn excel-based Six Sigma statisticalsoftware add-in.

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Module 24 – QE Software Tutorial 1a
QE Tools Software Tutorial
Part I – Getting Started, Tool RoadMap,
Cause-and-Effect Diagrams, Measure Phase
QETOOLS
An excel-based Six Sigma statistical
software add-in.
qetools.com
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QE Tools Menu Items
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Topics
I. Getting Started
II. Six Sigma Methods - Tool Roadmap
III. Process Analysis - Qualitative Tools
IV. Process Capability Summary
Note: Not all tools are shown in this tutorial.
See help files for additional examples.
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I. Getting Started
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Getting Started – Excel Menu
QE Tools appears as a menu
option in the main Excel toolbar.
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Getting Started – New Data Sheet
QE Tools uses its own data sheet
when performing analyses.
You may begin by creating an
initial blank datasheet using the
New Data Sheet menu pick.
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Data Sheets
A new, pre-formatted worksheet is inserted with the
name DataSheet.
After you create a data sheet, you can add and
manipulate data in most of the ways familiar to you in
Excel (e.g., copy, paste, add formulas, etc.).
Note: You must define a variable name for each data
series in the Row: “Variable Name”.
Optional, you may include upper and lower
specification limits (USL and LSL) as well as a target
(nominal) value for each variable.
These will automatically be referenced for those
tools that require specification limits for analysis.
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Data Format in “DataSheet”
Data variables may either be values or
calculations of other variables.
Examples:
‘TotalVisit’ list values
‘TotalWait’ and ‘WattoVisit’ are formula.
Data for any variable may be constructed
using standard Excel formulas.
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Variable Type Identifier
The Variable Type is automatically determined
when data is added or pasted into the Datasheet.
Type is either “data” (numerical) or “text.” Various
tools require certain data types in order to run. For
example, basic descriptive statistics (sample N,
mean, standard deviation, etc) can only be
computed for “data” type variable.
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Variable Names
n When entering variable names, QE Tools may update
after you enter them or paste from another worksheet.
QE Tools uses an algorithm to standardize variable
names. The algorithm ensures that:
n Certain characters are not allowed in variable names.
The following characters are stripped from variable names:
n :, \, /, ?, *, [, ], ‘ (apostrophe),
n Variable names are no longer than 16 characters.
Names that are longer are shortened by using the first 8
and last 8 characters of whatever is entered.
n Duplicate names are not allowed to insure QE Tools knows
which variable you wish to analyze.
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Number of Worksheet Warnings
n QETools warns of having too many active
worksheets because performance may be
diminished with increasing file size.
n After 30 worksheets, QE tools issues a
warning message.
n Recommend creating a second analysis file or
removing unused worksheets.
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QE Tools Demo – Getting Started
n Create a new data sheet
n Enter raw data
n Numerical Data
n Text
n Enter Formula in DataSheet
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
II. Six Sigma Methods –
Tool Roadmap
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Six Sigma Tool Roadmap
n QE Tools provides a Six Sigma problem solving
roadmap with common analysis steps and
hyperlinks to analysis tools and templates.
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Example: Measure Phase
Blue Text
Represent
Hyperlinks
To Various
Analysis and
Templates
in QE Tools
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III. Process Analysis –
Qualitative Analysis Tools
Working with ideas / text
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Process Analysis – Qualitative Tools
n SIPOC Diagram
n Cause-Effect Diagram * Sample Templates Provided
n QFD - House of Quality
n FMEA Table*
n Process Control Plan Manufacturing or Transactional*
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Process Analysis Tools > SIPOC
Sample Excel Data File:
qetools-sampledata.xls
Select Variables Using
SIPOC Dialogue Box
OUTPUT: SIPOC Diagram - Loan Process
Suppliers Inputs Process Outputs Customers
• Appraisers • Lender • Loan Documents • Mortgage
Programs Customers
• Insurance • Interest Rates • Mortgage • External
Companies Underwriter
• Title Companies • Type of Loan • Lending
Institution
• Government • Loan Value
Step 1: Step 2: Step 3: Step 4: Final:
•Prepare •Process •Underwrite •Clear •Close Loan
Loan Loan Loan Conditions
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
QE Tools Demo – SIPOC Diagram
Sample Excel Data File:
qetools-sampledata.xls
SIPOC Variables
Process
Suppliers
Inputs
Outputs
Customer
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Process Analysis Tools >
Cause-Effect Diagram
May enter data
Directly in dialogue
Box.
However, we recommend
entering reasons for
each cause category
in data sheet column.
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
QE Tools Demo –
Cause and Effect Diagram
Sample Excel Data Cause and Effect Diagram
File: Man Method
qetools-sampledata.xls
Late Crew Boarding Process
computer failure
wrong terminal
short staff
Late Pilot Gate Blocked
wrong terminal
short staff
Variables Used Example Late Cleaning
Machine
Late Flights
Environment FAA Delay Late Baggage Mechanical
Man Weather Late Meals Gate Not Working
Material
Method Late Fuel
Twiglet: Boarding
Environment Material Machine
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Process Analysis Tools > Control
Plan
Select
Control
Plan Template
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
QE Tools Control Plan Template
Note: worksheets may be modified per user preference.
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IV. Process Capability
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Process Capability Summary
n Data Analysis Tools
n Sigma Level Calculator
n DPM Calculator - Normal
n Process Capability Graphical Summary*
n Variable is Normal
n Variable is Non-Normal – Best Fit with Weibull Distribution
n Variable is Binary – Assume Binomial Distribution
Note: Process Capability Graphical Summary includes:
summary statistics, observed DPM, expected DPM (distribution),
histogram, run charts, box plot, control charts where applicable
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Process Capability Summary >
Sigma Level Calculator
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Sigma Level Calculator - Example
Three different methods are available to calculate the “sigma level”
depending on the format of information available from your process. Enter
the appropriate information in white boxes and sigma level is calculated
automatically.
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Process Capability Summary >
DPM Calculator - Normal
If data may be assumed to
be normal, you may input
the average, standard
deviation and specification
limits in white boxes and QE
Tools automatically
estimates Defects per
million.
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Process Capability –
Graphical Summary*
n Different Process Capability Summaries are
available depending on data / distribution.
n Continuous Variable and Normal Distribution
n Continuous Variable and Non-Normal –
Best Fit with Weibull Distribution
n Binary Variable – Distribution assumed Binomial
Note: Process Capability Graphical Summary includes:
summary statistics, observed DPM, expected DPM (distribution),
histogram, run charts, box plot, control charts where applicable
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Process Capability Summary -
Normal
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Process Capability Summary –
Normal – Dialogue Box
Select one or more variables from the variable
list to analyze (note: each variable is output
to its own results worksheet).
Select type of control charts to
display on the results worksheet
(note: subgroup size is assumed 1
for “Ind / Moving Range”.
Options –
-- show out-of-control patterns.
-- manual scale run chart
-- enter specification limits if not
already entered on “data sheet”.
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Process Capability Summary –
Normal – Using Data Ranges
Optionally select a range of data to
analyze from a worksheet other than
the DataSheet (note: the first row is
assumed to be a label used as the
variable name).
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Process Capability Summary –
Normal à Results
The output contains several sections:
• Statistical summary
• Expected Defects per Million
(distribution)
• Observed Defects per Million
• Histogram
• Run chart
• Box plot
• Control charts
Sample Excel Data File:
qetools-sampledata.xls
Output: Time in Waiting Room
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Results – Summary Stats - Histogram
Notice that the Upper Specification
Limit (USL) from the datasheet is
displayed on the chart and
summarized in the data output. 34
Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Results – Run Chart – Box Plot
The Run Chart provides a time trend.
Box Plot summarizes basic
distribution. Example shown is skewed
right (more points > median).
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Process Capability Summary –
Non-normal (Weibull)
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Results- Non-normal (Weibull)
The output contains:
• Statistical summary
• Expected Defects per Million
(distribution)
• Observed Defects per Million
• Histogram
• Run chart
• Box plot
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Process Capability Summary –
Binary (Binomial)
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Copyright, University of Michigan Online Green Belt Transactional Course
Module 24 – QE Software Tutorial 1a
Process Capability Summary –
Binary (Binomial) à Dialogue Box
Select two variables for the
analysis (one variable represents
the number of units and the
second is for the number
defective).
Do not enter defective
percentages – QE tools
automatically calculates.
Alternatively, select one variable
for the number defective and
enter a constant sample size.
Specify a target for the process
(note: the target does not figure
into any calculations but does
appear on the results worksheet
for reference).
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QE Tools Demo – Process Capability
Sample Excel Data File:
qetools-sampledata.xls
Sigma Level Calculator
DPM Calculator - Normal
Process Capability Graphical Summary*
Datasheet Variable: “TimeinWaitRoom”
Datasheet Variable: “TimeinWaitRoom”
Datasheet Variable: Units: “P-Units” and Defective: “P-Defective”
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