1 / 59

Chapter 7 Quality Tools

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.

ametz
Download Presentation

Chapter 7 Quality Tools

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Chapter 7Quality Tools

  2. 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.

  3. Diagnostic Tools • Analytical Tools: • Cause-Effect (CE) diagram • Failure mode-effects Analysis (FMEA) • XY matrix • Affinity diagram • Fault tree analysis (FTA) • Graphical Tools: • Histogram • Boxplots • Probability distribution plots • Main-effects plots • Pareto charts • Run charts • Multi-Vari charts • Time-series plots • Scatter plots

  4. Diagnostic Tools • Other Tools: • Checksheets • Scorecards • Graphical Rep. of Process: • Process flow charts • Process mapping • Cross-functional mapping • Deployment diagram • Supplier-input-process-output-customer (SIPOC) diagram • Input-process-output (IPO) diagram • Force-field analysis

  5. 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 • 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”

  6. Y = f (x) • 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. • 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. x1 x2 x3 . . . . xn Process Inputs . . . Uncontrollable variables or factors (noise)

  7. Critical-to (CT) Definitions • 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-Process (CTP) characteristics- Process parameters that significantly influence a CTQ, CTD, and/or CTC. Variables (X)

  8. 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.

  9. The Leverage Principle(Variation Reduction Strategies)

  10. 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….

  11. How do we know if customers are happy?Goal is to understand how to better satisfy the customer • Survey design considerations: • Length (not too long) • Appearance (simple, not busy) • Types of questions (statements of fact or measures of performance or importance) • Types of question formats: • Closed-ended (yes/no) • Rating scales • Open-ended questions / probes • Other considerations: • 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: • At least 10% of customer base • Stratify various customer segments • Give prior notice, before delivering survey • Personalize the survey and cover letter • Address confidentiality • Offer an incentive or token of appreciation for completion • Follow up with a friendly collection strategy • Develop action plans that are based on results • Communicate results to customers • Follow up with repeat surveys to monitor changes over time

  12. 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

  13. Continuous Scales 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. • Linear Scale: A scale with equal divisions for equal values

  14. 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)

  15. Cause-Effect (CE) Analysis www.syncfusion.com/.../img/Fishbone_larger.png

  16. 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: • 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.

  17. How does FMEA work? • 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 • Start with a grid to define the potential failures

  18. FMEASeverity, Occurrence & Detectability SEVERITY

  19. FMEASeverity, Occurrence & Detectability OCCURANCE

  20. FMEASeverity, Occurrence & Detectability PROBABILITY OF DETECTION • Risk Priority number (RPN) is calculated by multiplying • Severity x Occurrence x Detectabillity

  21. 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. • If the results/ranking were generated during a brainstorm session than they should be verified based on actual data.

  22. 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?

  23. Graphical Tool: Histogram with Normal Curve university-software.com/NormalHist.jpg

  24. Graphical Tool: Histogram with Normal Curve Minitab: Calc Random Data Integer Stat Basic Statistics Graphical Summary

  25. Graphical Tool: Boxplot • Minimum • Maximum • Median • First Quartile • Third Quartile • Minitab: • Stat • Basic Statistics • Display Descriptive.. • Boxplot

  26. Graphical Tool: Probability Plot • Minitab: • Graph • Probability Plot • Single

  27. 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

  28. Graphical Tool: Main-Effects Plot MINITAB STAT ANOVA Main Effect Plot

  29. 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

  30. Graphical Tool: Run Chart www.pqsystems.com/.../chart_BasicRunChart.png

  31. 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

  32. Graphical Tool: Time-Series Plot cookbooks.opengrads.org/images/3/3b/Precip_ti..

  33. 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

  34. Graphical Tool: Multi-Vari Charts Cus. Size: 1 = small 2 = large Product: 1 = Consumer 2 = Manuf. Cus. Type: 1 = Gov’t 2 = Commercial 3 = Education http://www.qimacros.com/qiwizard/multivari-chart.html

  35. Graphical Tool: Multi-Vari Charts Minitab: Stat Quality Tools Multi Vari Chart

  36. 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

  37. Graphical Tool: Scatter Plot http://mste.illinois.edu/courses/ci330ms/youtsey/scatterinfo.html

  38. Graphical Tool: Scatter Plot http://mste.illinois.edu/courses/ci330ms/youtsey/scatterinfo.html

  39. Graphical Tool: Scatter Plot http://mste.illinois.edu/courses/ci330ms/youtsey/scatterinfo.html

  40. Graphical Tool: Scatter Plot http://mste.illinois.edu/courses/ci330ms/youtsey/scatterinfo.html

  41. Graphical Tools for Process Rep.:Process Flowcharts • Visual representation of the major process steps. • Useful to compare “as is” with “should be” process. • 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:

  42. Graphical Tools for Process Rep.:Process Flowcharts www.breezetree.com/.../8D-process-flowchart.png

  43. 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”

  44. Graphical Tools for Process Rep.:Process Mapping www.oregon.gov/.../images/iGrafx_Process_Map.JPG

  45. 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.

  46. Graphical Tools for Process Rep.: SIPOC Diagram http://www.ptm-consulting.it/immagini/sipoc.jpg

  47. 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) SOPs Supply Chain Process X’s x1=Forecast x2=Buyer X3 =AVL x4=BOM x5=LT x6=Market Dollar Value Process Program Management Y=Lack of materials supplies Unforecast demand Environment AVL Accuracy Shipping from Supplier Noise Variables(N)

  48. Graphical Tools for Process Rep.: SIPOC Diagram http://www.variancereduction.com/newsletters/images/9.6.16.jpg

  49. 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.

  50. Force-Field Analysis

More Related