SIX SIGMA QUALITY TECHNIQUES... WHERE YOU NEED TO BE TO COMPETE IN THE NEW MILLENNIUM Michael W. Piczak Dipl.T., B.Comm., ...
 
THE MAIN ELEMENTS
DE FACTO, 6 SIGMA IS:  <ul><li>The search for and control of X’ s </li></ul>
GOALS OF 6 SIGMA   <ul><li>Defect reduction </li></ul><ul><li>Yield improvement </li></ul><ul><li>Improved customer satisf...
WHERE TO FOCUS? <ul><li>For each product or process critical to quality (CTQ): </li></ul><ul><li>Measure </li></ul><ul><li...
PRIMARY SOURCES OF VARIATION <ul><li>Inadequate design margin </li></ul><ul><li>Unstable parts and material </li></ul><ul>...
WHO IS THE ENEMY? <ul><li>VARIATION </li></ul>
SELECTION OF RESPONSE VARIABLE (Y) CHOICE OF FACTORS (X i ’s), LEVELS, RANGES RECOGNITION OF & STATEMENT OF PROBLEM CHOICE...
 
OUR BASIC RESEARCH PARADIGM <ul><li>Enter data and editing same </li></ul><ul><li>Verify data integrity via Counts/Describ...
PEDAGOGICAL APPROACH <ul><li>Lecture </li></ul><ul><li>Discussion, debate and argument </li></ul><ul><li>Videos </li></ul>...
TERMINAL PERFORMANCE OBJECTIVES <ul><li>As a result of taking this program, the participant will be able to: </li></ul><ul...
T.P.O.s CONTINUED... <ul><li>Participate as a contributing member of a continuous improvement or problem solving team </li...
GENESIS OF 6 SIGMA
WHAT ARE WE REACHING FOR?
ELEMENT 1
PORTER’S 5 FORCES MODEL
PEST MODEL
‘BONUS’ MODEL A key element
VOICE OF THE CUSTOMER <ul><li>2 Brands of customers </li></ul><ul><ul><ul><li>internal </li></ul></ul></ul><ul><ul><ul><li...
ALL ON THE SAME PAGE Voice of the customer
DESCRIBE THE PROCESS
IMPROVING THE PROCESS <ul><li>Elimination </li></ul><ul><li>Simplification </li></ul><ul><li>Combination </li></ul><ul><li...
CRITICAL EXAMINATION
NO NEW PROBLEMS PLEASE <ul><li>Poka Yoke techniques </li></ul><ul><ul><ul><li>guide pins </li></ul></ul></ul><ul><ul><ul><...
GETTING BETTER? <ul><li>The need to measure in quantitative terms important </li></ul><ul><li>QS9000 demands it in terms o...
ELEMENT 2: MEASUREMENT
OLD METRICS <ul><li>Measures of central tendency or typicality (mean, median, mode) </li></ul><ul><li>Measures of dispersi...
THE NORMAL DISTRIBUTION
NORMAL CURVE CHARACTERISTICS <ul><li>Continuous </li></ul><ul><li>Symmetrical </li></ul><ul><li>Tails asymptotic to zero <...
A KEY FORMULA
VARIATION IN PERSPECTIVE <ul><li>± 1 Sigma </li></ul><ul><li>± 2 Sigma </li></ul><ul><li>± 3 Sigma </li></ul><ul><li>± 4 S...
VISUALIZING VARIATION
THE HUNT FOR X
FIXING BELIEF <ul><li>Method of tenacity </li></ul><ul><li>Method of authority </li></ul><ul><li>Method of reasoning </li>...
THE SCIENTIFIC METHOD
VISUALIZING VARIATION
 
PROCESS CAPABILITY
PROCESS CAPABILITY II
THE JOURNEY <ul><li>Most companies presently at 3-4 sigma </li></ul><ul><li>The move is toward 6 sigma (Cp = 2) </li></ul>...
Cpk
HYDRAULIC LIFT COMPANY <ul><li>See case on Page 37 </li></ul>
CAPABILITY ST & LT
Cp LONG TERM (LT)
ST to LT
NEW METRICS <ul><li>dpu </li></ul><ul><li>dmpo </li></ul><ul><li>THE CAVEAT </li></ul>
Dpmo, Cp and Sigma <ul><li>using page 608 Lindsay and Evans, derive figures shown </li></ul><ul><li>using page 48 Piczak, ...
2 ROADS TO PROFITABILITY
COSTS OF QUALITY
ELEMENT 3: QUALITY INITIATIVES
SDWT’s <ul><li>See Appendix G </li></ul>
LITERATURE IDENTIFIED BENEFITS <ul><ul><li>Productivity    15% -250% </li></ul></ul><ul><ul><li>All employees can perform...
BENEFITS CONT’D <ul><ul><li>Late jobs    1000% </li></ul></ul><ul><ul><li>Quality     </li></ul></ul><ul><ul><li>Recurri...
BENEFITS CONT’D <ul><ul><li>Sales    830% </li></ul></ul><ul><ul><li>Operating statistics improved by 25-40% </li></ul></...
SHORT CYCLE MFG. <ul><li>SMED </li></ul><ul><li>automated & computerized inspection </li></ul><ul><li>X and moving range c...
DFM <ul><li>Group technology </li></ul><ul><li>accessibility of different parts & areas </li></ul><ul><li>ease of workpiec...
BENCHMARKING <ul><li>more than just organized tourism </li></ul><ul><li>more than just a nice walk over at a friend’s plan...
THE ALCOA SEQUENCE
SPC <ul><li>using numbers to describe absence or presence of a phenomenon </li></ul><ul><li>systematic gathering of data <...
STATISTICS <ul><li>Collecting </li></ul><ul><li>Organizing </li></ul><ul><li>Summarizing </li></ul><ul><li>Analyzing </li>...
THE ANALYST’S DUTY <ul><li>Start with a regularity, uniformity or curiosity </li></ul><ul><li>identify all previously sign...
<ul><li>construct conceptual model of hypothesized relationships </li></ul><ul><li>set out research question(s) clearly </...
 
3 KINDS OF STATISTICS <ul><li>Descriptive (p. 71) </li></ul><ul><li>Inferential </li></ul><ul><li>Predictive </li></ul>
NASA DATA & REGRESSION LINE
 
DATA TYPES <ul><li>Discrete </li></ul><ul><li>Continuous </li></ul>
CHART TYPES
CHART TYPES <ul><ul><ul><li>X Bar and R charts </li></ul></ul></ul><ul><ul><ul><li>X and Moving Range charts </li></ul></u...
CONTROL LIMITS FOR X BAR & R CHARTS <ul><ul><li>Upper control limit (UCL    )= x double bar + Z     </li></ul></ul><ul>...
OR
FOR  R
X &  MOVING RANGE CHARTS
PLOTTING R
PLOTTING X
P CHARTS
AN EXAMPLE P. 102
A SUMMARY TABLE OF FORMULAS
INTERPRETING CHARTS <ul><li>Examining patterns to make rational decisions </li></ul><ul><li>Using patterns puts the odds o...
U CAN BE RIGHT, U CAN BE WRONG
PATTERN ANALYSIS FIG. 41
CHANGE OR JUMP IN LEVEL
RECURRING CYCLES F. 43
TREND OR STEADY CHANGE IN LEVEL
NO BRAINERS
50% ABOVE/BELOW MEAN
6 POINT RUN
CYCLICAL PATTERN
CYCLICAL PATTERN
SHORT TERM TREND WITH ADJUSTMENT
68% WITHIN 1 SIGMA
SYSTEMATIC CAUSES OF VARIATION <ul><li>Lack of preventative maintenance </li></ul><ul><li>Worn tools </li></ul><ul><li>Ope...
 
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Six Sigma Statistical Methods Using Minitab 13 Manual ...

  1. 1. SIX SIGMA QUALITY TECHNIQUES... WHERE YOU NEED TO BE TO COMPETE IN THE NEW MILLENNIUM Michael W. Piczak Dipl.T., B.Comm., MBA
  2. 3. THE MAIN ELEMENTS
  3. 4. DE FACTO, 6 SIGMA IS: <ul><li>The search for and control of X’ s </li></ul>
  4. 5. GOALS OF 6 SIGMA <ul><li>Defect reduction </li></ul><ul><li>Yield improvement </li></ul><ul><li>Improved customer satisfaction </li></ul><ul><li>Higher net income </li></ul>
  5. 6. WHERE TO FOCUS? <ul><li>For each product or process critical to quality (CTQ): </li></ul><ul><li>Measure </li></ul><ul><li>Analyze </li></ul><ul><li>Improve </li></ul><ul><li>Control </li></ul>
  6. 7. PRIMARY SOURCES OF VARIATION <ul><li>Inadequate design margin </li></ul><ul><li>Unstable parts and material </li></ul><ul><li>Insufficient process capability </li></ul>
  7. 8. WHO IS THE ENEMY? <ul><li>VARIATION </li></ul>
  8. 9. SELECTION OF RESPONSE VARIABLE (Y) CHOICE OF FACTORS (X i ’s), LEVELS, RANGES RECOGNITION OF & STATEMENT OF PROBLEM CHOICE OF EXPERIMENTAL DESIGN PERFORMING EXPERIMENT STATISTICAL ANALYSIS OF DATA CONCLUSIONS, RECOMMENDATIONS, NEXT STEPS
  9. 11. OUR BASIC RESEARCH PARADIGM <ul><li>Enter data and editing same </li></ul><ul><li>Verify data integrity via Counts/Describe </li></ul><ul><li>Run Descriptives </li></ul><ul><li>Generate graphs & charts of data </li></ul><ul><li>Analyze ANOVAs </li></ul><ul><li>Run regressions, DOEs, GR&Rs </li></ul>
  10. 12. PEDAGOGICAL APPROACH <ul><li>Lecture </li></ul><ul><li>Discussion, debate and argument </li></ul><ul><li>Videos </li></ul><ul><li>Hands-on exercises using general and company specific examples </li></ul>
  11. 13. TERMINAL PERFORMANCE OBJECTIVES <ul><li>As a result of taking this program, the participant will be able to: </li></ul><ul><li>Appreciate the scope of 6 Sigma practices in context of other company initiatives </li></ul><ul><li>Apply a variety of tools to solve problems </li></ul>
  12. 14. T.P.O.s CONTINUED... <ul><li>Participate as a contributing member of a continuous improvement or problem solving team </li></ul><ul><li>Use Minitab as a data analysis tool </li></ul>
  13. 15. GENESIS OF 6 SIGMA
  14. 16. WHAT ARE WE REACHING FOR?
  15. 17. ELEMENT 1
  16. 18. PORTER’S 5 FORCES MODEL
  17. 19. PEST MODEL
  18. 20. ‘BONUS’ MODEL A key element
  19. 21. VOICE OF THE CUSTOMER <ul><li>2 Brands of customers </li></ul><ul><ul><ul><li>internal </li></ul></ul></ul><ul><ul><ul><li>external </li></ul></ul></ul>
  20. 22. ALL ON THE SAME PAGE Voice of the customer
  21. 23. DESCRIBE THE PROCESS
  22. 24. IMPROVING THE PROCESS <ul><li>Elimination </li></ul><ul><li>Simplification </li></ul><ul><li>Combination </li></ul><ul><li>Reuse </li></ul><ul><li>Parallel processing </li></ul><ul><li>Subcontracting </li></ul>
  23. 25. CRITICAL EXAMINATION
  24. 26. NO NEW PROBLEMS PLEASE <ul><li>Poka Yoke techniques </li></ul><ul><ul><ul><li>guide pins </li></ul></ul></ul><ul><ul><ul><li>templates </li></ul></ul></ul><ul><ul><ul><li>limit switches </li></ul></ul></ul><ul><ul><ul><li>limited computer screen fields </li></ul></ul></ul><ul><ul><ul><li>checklists </li></ul></ul></ul><ul><ul><ul><li>interconnects </li></ul></ul></ul>
  25. 27. GETTING BETTER? <ul><li>The need to measure in quantitative terms important </li></ul><ul><li>QS9000 demands it in terms of quality and effectiveness </li></ul><ul><ul><ul><li>customer satisfaction </li></ul></ul></ul><ul><ul><ul><li>quality levels (# non-conformances, dpu, dpmo) </li></ul></ul></ul><ul><ul><ul><li>cycle times </li></ul></ul></ul><ul><ul><ul><li>die change times </li></ul></ul></ul>
  26. 28. ELEMENT 2: MEASUREMENT
  27. 29. OLD METRICS <ul><li>Measures of central tendency or typicality (mean, median, mode) </li></ul><ul><li>Measures of dispersion (range, variance, standard deviation) </li></ul>
  28. 30. THE NORMAL DISTRIBUTION
  29. 31. NORMAL CURVE CHARACTERISTICS <ul><li>Continuous </li></ul><ul><li>Symmetrical </li></ul><ul><li>Tails asymptotic to zero </li></ul><ul><li>Bell shaped </li></ul><ul><li>Mean = median = mode </li></ul><ul><li>Total area under curve = 1 </li></ul>
  30. 32. A KEY FORMULA
  31. 33. VARIATION IN PERSPECTIVE <ul><li>± 1 Sigma </li></ul><ul><li>± 2 Sigma </li></ul><ul><li>± 3 Sigma </li></ul><ul><li>± 4 Sigma </li></ul><ul><li>± 5 Sigma </li></ul><ul><li>± 6 Sigma </li></ul><ul><li>± ? Sigma </li></ul>
  32. 34. VISUALIZING VARIATION
  33. 35. THE HUNT FOR X
  34. 36. FIXING BELIEF <ul><li>Method of tenacity </li></ul><ul><li>Method of authority </li></ul><ul><li>Method of reasoning </li></ul><ul><li>Method of science </li></ul>
  35. 37. THE SCIENTIFIC METHOD
  36. 38. VISUALIZING VARIATION
  37. 40. PROCESS CAPABILITY
  38. 41. PROCESS CAPABILITY II
  39. 42. THE JOURNEY <ul><li>Most companies presently at 3-4 sigma </li></ul><ul><li>The move is toward 6 sigma (Cp = 2) </li></ul><ul><li>Literature has references to 12 sigma (Cp = ?) </li></ul>
  40. 43. Cpk
  41. 44. HYDRAULIC LIFT COMPANY <ul><li>See case on Page 37 </li></ul>
  42. 45. CAPABILITY ST & LT
  43. 46. Cp LONG TERM (LT)
  44. 47. ST to LT
  45. 48. NEW METRICS <ul><li>dpu </li></ul><ul><li>dmpo </li></ul><ul><li>THE CAVEAT </li></ul>
  46. 49. Dpmo, Cp and Sigma <ul><li>using page 608 Lindsay and Evans, derive figures shown </li></ul><ul><li>using page 48 Piczak, derive figures shown </li></ul>
  47. 50. 2 ROADS TO PROFITABILITY
  48. 51. COSTS OF QUALITY
  49. 52. ELEMENT 3: QUALITY INITIATIVES
  50. 53. SDWT’s <ul><li>See Appendix G </li></ul>
  51. 54. LITERATURE IDENTIFIED BENEFITS <ul><ul><li>Productivity  15% -250% </li></ul></ul><ul><ul><li>All employees can perform all tasks </li></ul></ul><ul><ul><li>Costs  30% </li></ul></ul><ul><ul><li>Cycle time  50%-90% </li></ul></ul><ul><ul><li>Inventory  66% </li></ul></ul><ul><ul><li>Rework due to engineering flaws  50% </li></ul></ul>
  52. 55. BENEFITS CONT’D <ul><ul><li>Late jobs  1000% </li></ul></ul><ul><ul><li>Quality  </li></ul></ul><ul><ul><li>Recurring defective product problems  10% </li></ul></ul><ul><ul><li>Return on investment/sales  </li></ul></ul>
  53. 56. BENEFITS CONT’D <ul><ul><li>Sales  830% </li></ul></ul><ul><ul><li>Operating statistics improved by 25-40% </li></ul></ul><ul><ul><li>Accounts receivable  from 66 days to 51 days </li></ul></ul><ul><ul><li>Corporate overhead  from $100M to $24M </li></ul></ul><ul><ul><li>Accidents  72% </li></ul></ul>
  54. 57. SHORT CYCLE MFG. <ul><li>SMED </li></ul><ul><li>automated & computerized inspection </li></ul><ul><li>X and moving range control charts </li></ul><ul><li>automated systems (MAPs/CAD/CAM/flexible mfg., etc.) </li></ul><ul><li>flexible, self directed work force </li></ul>
  55. 58. DFM <ul><li>Group technology </li></ul><ul><li>accessibility of different parts & areas </li></ul><ul><li>ease of workpiece handling </li></ul><ul><li>ergonomic principles </li></ul><ul><li>safety requirements </li></ul><ul><li>appearance </li></ul><ul><li>QFD </li></ul>
  56. 59. BENCHMARKING <ul><li>more than just organized tourism </li></ul><ul><li>more than just a nice walk over at a friend’s plant </li></ul><ul><li>not industrial espionage </li></ul><ul><li>not a one way channel of communication </li></ul>
  57. 60. THE ALCOA SEQUENCE
  58. 61. SPC <ul><li>using numbers to describe absence or presence of a phenomenon </li></ul><ul><li>systematic gathering of data </li></ul><ul><li>using a collection of analytics that promote common understanding </li></ul><ul><li>emphasis is on measurement </li></ul>
  59. 62. STATISTICS <ul><li>Collecting </li></ul><ul><li>Organizing </li></ul><ul><li>Summarizing </li></ul><ul><li>Analyzing </li></ul><ul><li>Presenting </li></ul>
  60. 63. THE ANALYST’S DUTY <ul><li>Start with a regularity, uniformity or curiosity </li></ul><ul><li>identify all previously significant predictors of phemon in question </li></ul><ul><li>theorize as to why independent variables (X’s) should be predictive of dependent variables (Y) </li></ul>
  61. 64. <ul><li>construct conceptual model of hypothesized relationships </li></ul><ul><li>set out research question(s) clearly </li></ul><ul><li>gather data </li></ul><ul><li>organize same into spread/worksheet </li></ul><ul><li>run full model followed by reduced form </li></ul><ul><li>draw conclusions/rec’s and share same </li></ul>
  62. 66. 3 KINDS OF STATISTICS <ul><li>Descriptive (p. 71) </li></ul><ul><li>Inferential </li></ul><ul><li>Predictive </li></ul>
  63. 67. NASA DATA & REGRESSION LINE
  64. 69. DATA TYPES <ul><li>Discrete </li></ul><ul><li>Continuous </li></ul>
  65. 70. CHART TYPES
  66. 71. CHART TYPES <ul><ul><ul><li>X Bar and R charts </li></ul></ul></ul><ul><ul><ul><li>X and Moving Range charts </li></ul></ul></ul><ul><ul><ul><li>p charts </li></ul></ul></ul><ul><ul><ul><li>c charts and </li></ul></ul></ul><ul><ul><ul><li>u charts </li></ul></ul></ul>
  67. 72. CONTROL LIMITS FOR X BAR & R CHARTS <ul><ul><li>Upper control limit (UCL  )= x double bar + Z   </li></ul></ul><ul><ul><li>Lower control limit (LCL  ) = x double bar - Z   </li></ul></ul>
  68. 73. OR
  69. 74. FOR R
  70. 75. X & MOVING RANGE CHARTS
  71. 76. PLOTTING R
  72. 77. PLOTTING X
  73. 78. P CHARTS
  74. 79. AN EXAMPLE P. 102
  75. 80. A SUMMARY TABLE OF FORMULAS
  76. 81. INTERPRETING CHARTS <ul><li>Examining patterns to make rational decisions </li></ul><ul><li>Using patterns puts the odds of making a good decision on your side </li></ul><ul><li>Can make two good decisions and two bad decisions </li></ul>
  77. 82. U CAN BE RIGHT, U CAN BE WRONG
  78. 83. PATTERN ANALYSIS FIG. 41
  79. 84. CHANGE OR JUMP IN LEVEL
  80. 85. RECURRING CYCLES F. 43
  81. 86. TREND OR STEADY CHANGE IN LEVEL
  82. 87. NO BRAINERS
  83. 88. 50% ABOVE/BELOW MEAN
  84. 89. 6 POINT RUN
  85. 90. CYCLICAL PATTERN
  86. 91. CYCLICAL PATTERN
  87. 92. SHORT TERM TREND WITH ADJUSTMENT
  88. 93. 68% WITHIN 1 SIGMA
  89. 94. SYSTEMATIC CAUSES OF VARIATION <ul><li>Lack of preventative maintenance </li></ul><ul><li>Worn tools </li></ul><ul><li>Operator performance </li></ul><ul><li>Differentials </li></ul><ul><li>Environmental changes </li></ul><ul><li>Sorting practices </li></ul>
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