Six Sigma Brilliant 4+

The Lean Six Sigma Coach provides Lean Six Sigma knowledge, the methodology as well as selected tools in English and German.


The App is aimed at process managers, project leaders and decision makers that focus on optimizing business processes. It enables the user to access important information quickly and conveniently and thereby organize his project work more efficiently.

Six Sigma is a business management strategy, which improve the quality of process outputs by identifying and removing the causes of defects (errors) and minimizing variability in manufacturing and business processes. In statistical terms, the purpose of Six Sigma is to reduce process variation so that virtually all the products or services provided meet or exceed customer expectations.

Some of topics Covered in this application are:
1. SIX SIGMA INTRODUCTION
2. SIX SIGMA DEFINITION
3. THE SIX SIGMA MOVEMENT
4. ROLE OF SIX-SIGMA
5. THE DESIGN FOR SIX-SIGMA
6. HISTOGRAMS IN SIX-SIGMA
7. HISTOGRAMS IN SIX-SIGMA
8. SOME OTHER HISTOGRAMS IN SIX-SIGMA
9. STATISTICAL INTERPRETATION OF SIX-SIGMA
10. PROJECT IMPLEMENTATION
11. SIX SIGMA-SIGMA VALUES
12. PURPOSE OF SIX-SIGMA
13. HISTORY OF SIX SIGMA
14. TOYOTA MANAGEMENT IN SIX-SIGMA
15. LEAN PRODUCTION
16. HISTORY OF DOCUMENTATION
17. HISTORY OF STATISCS AND QUALITY
18. THE CULTURE OF DISCIPLINE
19. QUALITY CONTROL AND SIX SIGMA
20. QUALITY FUNCTION DEVELOPMENT
21. ORGANIZATIONAL ROLES AND METHODS
22. STANDARD OPERATING PROCEDURE
23. ADVANCED STATISTICAL QUALITY CONTROL
24. SQC CASE STUDIES PRINTED CIRCUIT BOARD
25. STATISTICAL QUALITY CONTROL THEORY
26. PROBABILITY THEORY
27. DEFECTS PER MILLION OPPORTUNITIES
28. THE CENTRAL LIMIT THEOREM
29. DISCRETE RANDOM VARIABLES
30. XBAR CHARTS AND AVERAGE RUN LENGTH
31. OC CURVES AND AVERAGE SAMPLE NUMBER
32. DMAIC
33. LEAN SIX SIGMA METRICS
34. LEAN SIX-SIGMA APPROACH
35. LEAN SIX-SIGMA HISTORY
36. LEAN MANUFACTURING
37. LEAN MANUFACTURING WASTE
38. BENEFITS OF LSS
39. TYPES OF LAYOUT OF LSS
40. GROUP TECHNOLOGY
41. TOTAL PRODUCTIVE MAINTENANCE
42. KAIZEN
43. STAGES OF KAIZEN
44. MEASUREMENT SYSTEM ANALYSIS
45. REQUIREMENT OF MSA SYSTEM
46. REPEATEBILITY AND REPRODUCIBILITY
47. ANALYSIS OF VARIANCE METHOD
48. MEASURE PHASE AND STATISTICAL CHARTING
49. STATISTICAL CHARTING
50. GAUGE R AND R
51. STATISTICAL CHART SELECTION
52. P-CHARTING
53. P-CHARTING
54. DEMERIT CHARTING AND U-CHARTING
55. X-BAR AND R-CHARTING
56. ANALYZE PHASE
57. ANALYZE PHASE
58. THE TOYOTA PRODUCTION SYSTEM
59. CAUSES AND EFFECT MATRICES
60. DOE AND REGRESSION
61. PHAESES AND STRATEGY
62. PROJECT CHARTER
63. SNAB TAB PROJECT CHARTER
64. PHASES DIFINING METHODS
65. FORMAL MEETINGS
66. SIGNIFICANT FIGURES
67. THE LAW OF UNCOSCIOUS STATISTICIAN
68. PROCESS CAPABILITY INDICES
69. DESIGN PHASE
70. QUALITY FUNCTION DEVELOPMENT
71. CONTROL OR VERIFY PHASE
72. CONTROL PLANNING
73. ACCEPTANCE SAMPLING
74. DESIGN OF EXPERIMENTS (DOE) AND REGRESSION
75. DOE: SCREENING USING FRACTIONAL FACTORIALS
76. ORIGINS OF THE ARRAYS
77. TIME EXPERIMENTATION
78. DOE: RESPONSE SURFACE METHODS
79. SEQUENTIAL RESPONSE SURFACE METHODS
80. DOE: ROBUST DESIGN
81. REGRESSION
82. THE LEAST SQUARE FORMULA
83. DOE THEORY
84. VARIANCE INFLATION FACTORS AND CORRELATION MATRICES
85. REGRESSION NUMERICALS
86. STATISTICS IN SIX SIGMA
87. AOV BY MULTIPLE T-TESTS
88. NORMAL PROBABILITY PLOTS
89. REGRESSION MODELING FLOWCHART
90. ADVANCED REGRESSION AND ALTERNATIVES
91. KRIGING MODELS
92. NEURAL NETS FOR REGRESSION
93. FITTING LOGIT MODELS
94. LOGISTIC REGRESSION AND DISCRETE CHOICE MODELS
95. CASE STUDY: THE RUBBER MACHINE
96. SYSTEM BOUNDARIES
97. LOW COST RESPONSE SURFACE METHOD
98. PROBABILISTIC MODELS INTRODUCTION
99. DISCRETE PROBABILITY SPACES
100. And More Topics