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| Track |
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Six Sigma |
| Course Id |
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520 |
| Duration |
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8 days |
| LP |
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6 |
| Pre-requisites |
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none |
| Introduction |
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Six Sigma is the latest methodology sweeping across the business landscape and being adopted by major corporations and consulting firms. It is a comprehensive, flexible system for achieving, sustaining and maximizing business success.
Green Belt program gives you an opportunity to master problem-solving technology using Six Sigma tools. You will be able to apply a sophisticated data-driven methodology toward any process within your organization.
Requirement: Laptop Computers (windows 98, 200, Me, XP, NT 4; 32MB RAM; Pentium Processor 133 MHz or higher; CD-ROM Drive; 32MB HD space) and Minitab Statistical Software will be required for use in the workshops. Participants must furnish their own laptop computers. |
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| Objectives |
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Upon completion of this course, participants will understand the Six Sigma methodology, Six Sigma metrics, and analytical skills for solving many Six Sigma projects. Participants will be awarded Green Belt Certification and should be capable of executing a complete Six Sigma project or a high impact project sub-task.
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| Audience |
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Anyone interested in making a significant and lasting positive contribution toward the effectiveness, efficiency, and profitability of their workplace.
Also for those individuals who wish to upgrade their skills to become more marketable for employment. |
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| Contents |
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Overview:
What is Six Sigma?
Defects Per Million Opportunities Metric (DPMO)
Success Stories
SIPOC Model
DMAIC Process
Process Mapping
Six Sigma Organizational Structure
Role of the Black Belt
Define:
Customer Satisfaction & Kano Model
Critical to Quality Characteristics (CTQC's)
Operational Definition
Process Mapping
Process Flow Chart
Project Selection and Planning
Project Charter
Measure:
Variable and Attribute Data
Data Collection
Measurement System Analysis
Baseline DPMO & Sigma Conversion
Rolled Throughput Yield
Analyse:
Distributions: Mean, Standard Deviation, Histograms
Statistical Process Control Charts (SPC)
Capability Analysis
Confidence Intervals and Hypothesis Testing (Supplemental )
Comparison of Two Treatments, F-Test, t-test (Supplemental)
Comparison of Multiple Treatments – ANOVA (Supplemental)
Comparison of Variances - Chi-Square Test (Supplemental)
Cause and Effect Diagrams
FMEA
Regression and Correlation Analysis
Introduction to Design of Experiments
Improve:
Error-proofing
Corrective Action Matrix
Introduction to DOE
Control: |
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