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1. 1. 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 1 QE Tools Menu Items 2 Copyright, University of Michigan Online Green Belt Transactional Course
2. 2. 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. 3 I. Getting Started 4 Copyright, University of Michigan Online Green Belt Transactional Course
3. 3. Module 24 – QE Software Tutorial 1a Getting Started – Excel Menu QE Tools appears as a menu option in the main Excel toolbar. 5 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. 6 Copyright, University of Michigan Online Green Belt Transactional Course
4. 4. 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. 7 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. 8 Copyright, University of Michigan Online Green Belt Transactional Course
5. 5. 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. 9 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), <space> 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. 10 Copyright, University of Michigan Online Green Belt Transactional Course
6. 6. 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. 11 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 12 Copyright, University of Michigan Online Green Belt Transactional Course
7. 7. Module 24 – QE Software Tutorial 1a II. Six Sigma Methods – Tool Roadmap 13 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. 14 Copyright, University of Michigan Online Green Belt Transactional Course
8. 8. Module 24 – QE Software Tutorial 1a Example: Measure Phase Blue Text Represent Hyperlinks To Various Analysis and Templates in QE Tools 15 III. Process Analysis – Qualitative Analysis Tools Working with ideas / text 16 Copyright, University of Michigan Online Green Belt Transactional Course
9. 9. 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* 17 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 18 Copyright, University of Michigan Online Green Belt Transactional Course
10. 10. 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 19 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. 20 Copyright, University of Michigan Online Green Belt Transactional Course
11. 11. 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 21 Process Analysis Tools > Control Plan Select Control Plan Template 22 Copyright, University of Michigan Online Green Belt Transactional Course
12. 12. Module 24 – QE Software Tutorial 1a QE Tools Control Plan Template Note: worksheets may be modified per user preference. 23 IV. Process Capability 24 Copyright, University of Michigan Online Green Belt Transactional Course
13. 13. 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 25 Process Capability Summary > Sigma Level Calculator 26 Copyright, University of Michigan Online Green Belt Transactional Course
14. 14. 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. 27 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. 28 Copyright, University of Michigan Online Green Belt Transactional Course
15. 15. 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 29 Process Capability Summary - Normal 30 Copyright, University of Michigan Online Green Belt Transactional Course
16. 16. 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”. 31 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). 32 Copyright, University of Michigan Online Green Belt Transactional Course
17. 17. 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 33 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
18. 18. 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). 35 Process Capability Summary – Non-normal (Weibull) 36 Copyright, University of Michigan Online Green Belt Transactional Course
19. 19. 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 37 Process Capability Summary – Binary (Binomial) 38 Copyright, University of Michigan Online Green Belt Transactional Course
20. 20. 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). 39 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” 40 Copyright, University of Michigan Online Green Belt Transactional Course