Six Sigma Quality Engineering

1. Six Sigma Quality Engineering Week 4 Measure Phase

2. Chapter 5 Outline • Process Map/Spaghetti Diagram • Cause & Effect Fishbone Diagram • Cause & Effect Matrix • Reproducibility & Repeatability (Gage R&R) • Capability Analysis • Components of Variation Studies • FMEA

3. Process Map/Spaghetti Diagram

4. What is a Process Map? • A process map is a graphical representation of the flow of a process • A detailed process map includes information that can be used to improve the process, such as: • Process Times • Quality • Costs • Inputs • Outputs

5. Types of Process Map • Basic process map • Detailed process map • Work-flow (spaghetti diagrams) • Top-down flowchart • Deployment flowchart • Opportunity flowchart • Current State / Future state maps

6. Uses of a Process Map • Identify areas for focus of improvement efforts • Identify and eliminate non-value added steps • Combine operations • Assist root cause analysis • Baseline for failure mode and effect analysis (FMEA) • Identify potential controllable parameters for designed experiments • Determine needed data collection points • Eliminate unnecessary data collection steps

7. Detailed Process Map Example

8. Process Maps • Should include • Major activities and tasks • Sub-processes • Process boundaries • Inputs • Outputs • Documents reality, not how you think the process is supposed to be completed • Should identify opportunities for improvement

9. Steps for Process Mapping • Scope the process • Identify the start and end points of the process of interest • Document the top level process steps • Create a flow chart • Identify the inputs and outputs • What are the results of doing each process step? (Y’s) • What impacts the quality of each Y? (x’s) • Characterise the inputs

10. Characterising Inputs • Inputs can be classified as one of three types • Controllable (C) • Things you can adjust or control during the process • Speeds, feeds, temperatures, pressures…. • Standard Operating Procedures (S) • Things you always do (in procedures or common sense things) • Cleaning, safety…. • Noise (N) • Things you cannot control or don not want to control(too expensive or difficult) • Ambient temperature, humidity, operator...

11. Machining a shaft on a lathe Example Outputs (Y’s) Diameter Taper Surface finish C C C C C C C S C N N N S Inputs (x’s) Rotation speed Traverse speed Tool type Tool sharpness Shaft material Shaft length Material removal per cut Part cleanliness Coolant flow Operator Material variation Ambient temperature Coolant age

12. Order Entry Process MapAs-Is BEFORE 40 NVA STEPS NOTE: FROM THE CUSTOMER’S VIEWPOINT ALL OF ORDER ENTRY IS NON-VALUE ADDED

13. Order Entry Process MapNew REMEMBER: FROM THE CUSTOMER’S VIEWPOINT ALL OF ORDER ENTRY IS NON-VALUE ADDED We eliminated the steps that were NVA and UNNECESSARY (WASTE) BEFORE 40 NVA STEPS AFTER 11 NVA STEPS

14. Work-flow or Spaghetti Diagram • A work flow diagram is a picture of the movements of people, materials, documents, or information in a process. • Start by tracing these movements onto a floor plan or map of the work space. • The purpose of the work-flow diagram is to illustrate the inefficiency in a clear picture. • How can you make the map look simpler? What lines can you eliminate?

15. 56 Frame (Small Motor) Assy & Fabrication - Before x x x x BEFORE KAIZEN: Area: 4640 sq ft Operator Travel: 3696 ft Product Travel: 1115 ft x x x x x

16. Cause & Effect Fishbone Diagram

17. Cause & Effect Fishbone Diagram • Objectives • To understand the benefits of Cause & Effect Analysis • To understand how to construct a C & E Diagram • Analysis • A method a work group can use to identify the possible causes of a problem • A tool to identify the factors that contribute to a quality characteristic

18. Uses of C & E Fishbone Diagram • Visual means for tracing a problem to its causes • Identifies all the possible causes of a problem and how they relate before deciding which ones to investigate • C & E analysis is used as a starting point for investigating a problem

19. Fishbone Diagram • Effect • The problem or quality characteristic • The effect is the outcome of the factors that affect it Effect

20. Fishbone Diagram Causes • All the factors that could affect the problem or the quality characteristic • Five Major Categories • Materials • Methods • People • Machines • Environment

21. Machine Environment Effect Material Methods People

22. Cause & Effect matrix

23. The Eight Steps in Cause and Effect Analysis • Define the Effect • Identify the Major Categories • Generate Ideas • Evaluate Ideas • Vote for the Most Likely Causes • Rank the Causes • Verify the Results • Recommend Solutions

24. 2 1 5&6 3 4

25. Reproducibility & Repeatability (Gage R&R) “Data is only as good as the system that measures it. If you can’t measure it, you can’t manage it.”

26. The Science of Measurement “I often say that when you measure what you are speaking about and express it in numbers, you know something about it.” LORD KELVIN, 1891 He clearly stressed that little progress is possible in any field of investigation without the ability to measure. The progress of measurement is, in fact, the progress of science.

27. Objectives • Measurement Systems Analysis • Key Terminology • Variable Gauge R&R • A tool for estimating measurement system error • How to conduct a gauge R&R • Minitab Output • Gauge R & R Study Exercise

28. Definitions • Variable Data • Continuous measurements such as length, voltage, viscosity • Repeatability • Variation in measurements obtained with one gage when used several times by one appraiser. • Reproducibility • Variation in the average of the measurements made by different appraisers using the same measurement system.

29. What is GR&R? Measurement Systems Analysis How good is our measurement system? 2T = 2p + 2m 2T = Total Variance 2p = Process Variance 2m = Measurement Variance GRRRRRRR!!!

30. Gauge R&R Allows Control of the Measurement System

31. Variable Gauge R&R - What’s Involved? 3 Appraisers 1 Gauge 10 Parts

32. How to set up a Variable GRR Study • Preparation & Planning • 1 Gauge • 3 Operators (Appraisers) • 10 Parts • 3 Trials • Randomize the readings • Code the parts (blind study) if possible • 3 Ops x 10 parts x 3 trails = 90 Data Points • 4 Ops x 10 parts x 3 trails = 120 Data Points

33. Minitab Gage R&R Graphical Output The number of distinct categories of parts that the process is currently able to distinguish (Must distinguish at least 5 types of parts)

34. Acceptability Criteria • R&R Indices •  10% Acceptable Measurement System • 10% - 30% May be acceptable based upon application, cost of measurement device, cost of repair, etc. •  30%Not acceptable. Measurement system needs improvement. • Number of Distinct Categories Index • 1 Unacceptable. One part cannot be distinguished form another. • 2 -4 Generally unacceptable •  5 Recommended Module 0025

35. Minitab Gage R&R Graphical Output

36. Minitab Gage R&R Graphical Output

37. Minitab Gage R&R Graphical Output

38. Minitab Gage R&R Statistical Output

39. Minitab Gage R&R Statistical Output

40. Capability Analysis

41. Process Capability Study

42. Cpk & Cp • Cpk incorporates information about both the process spread and the process mean, so it is a measure of how the process is actually performing. • Cp relates how the process is performing to how it should be performing. Cp does not consider the location of the process mean, so it tells you what capability your process could achieve if centered.

43. Process Capability Study

44. Non-normal distributions • Use Capability Analysis (Nonnormal) to assess the capability of an in-control process when the data are from the nonnormal distribution. A capable process is able to produce products or services that meet specifications. • The process must be in control and follows a nonnormal distribution before you assess capability. If the process is not in control, then the capability estimates will be incorrect. • Nonnormal capability analysis consists of a capability histogram and a table of process capability statistics

45. Questions? Comments?