training Introduction

Six Sigma is one of the quality improvement processes which includes collecting and optimizing the information data from different business groups and then identifying the defects. Once the defects are found out, it focuses on reducing all those errors in a short span of time along with optimized variability in manufacturing the business processes. It supports in creating a special infrastructure of people who are expert in applying a set of quality management methods like empirical method and statistical method at the most. There is a sequence of steps which the Six Sigma professional follows with absolute assignment of specific value targets to each step.

This course was developed by Motorola in 1986 with more emphasis on time-cycle improvement and reducing manufacturing defects to a minimum level of 3.4 per million. With the change in time, Six Sigma has evolved into a more general philosophy which is related to customer requirements, improving retention of clients, and developing and sustaining business products and services.

  • Industry recognised Six Sigma Black Belt training by expert professionals

  • Accelerate your career with SIX SIGMA BLACK BELT certification

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trainingCourse Details

Six Sigma is related to an ideology which focuses on improving several statistics. Six Sigma advocates that qualitative extents should take a step ahead for getting success over qualitative indicators. In this way, the achievement of credibility will be there to enhance the work performances by different employees. Six Sigma practitioners include all those business people who use statistics, financial analysis and project management for achieving improved business functions. It applies to all industries and vendors who want to attain optimization in various belts of Six Sigma. First of all, it comprises of a statistical benchmark which means to consider any business process as efficient it has to produce less than 3.4 defects per 1 million chances. In this system, errors include the production of those things that are outside the consumer satisfaction. After that, there is a training program and certification that relates to the core principles of Six Sigma.

With a pre-defined path, practitioners can achieve Six Sigma belt levels which range from white to black belt. As a final point, it promotes the ideas by comprising as the philosophy through which all business processes can become measurable and optimized.

EXAM:

For measuring the comprehension of the course, each certification candidate is required to pass an examination that consists of multiple-choice questions. There will be 100 questions out of which 70 are recommended to be given to clear the exam. The exam will come only in English.

Six Sigma Black Belt training includes the following details as a part of the course content:

  1. DEFINING PHASE
    • Six Sigma Overview
      • What is Six Sigma?
      • History of Six Sigma
      • Y = f(x) Approach
      • Methodology of Six Sigma
      • Roles & Responsibilities
    • Fundamentals of Six Sigma
      • Defining Process
      • VOC & CTQ’s
      • QFD
      • Cost of Poor Quality
      • Pareto (80:20 rule)
    • Projects of Lean Six Sigma
      • Six Sigma Metrics
      • Business Case & Charter
      • Project Team Selection
      • Project Risk Management
      • Project Planning
    • Lean Fundamentals
  1. MEASURING PHASE
    • Process Definition
      • Cause & Effect Diagrams
      • Cause & Effects Matrix
      • Process Mapping
      • FMEA
      • Theory of Constraints
    • Six Sigma Statistics
      • Basic Statistics
      • Descriptive Statistics
      • Distributions & Normality
      • Graphical Analysis
    • MSA
      • Precision & Accuracy
      • Bias, Linearity & Stability
      • Gage R&R
      • Variable & Attribute MSA
    • Process Capability
      • Capability Analysis
      • Stability Concept
      • Attribute Capability
      • Discrete Capability
      • Monitoring Techniques
  1. ANALYZING PHASE
    • Variation Patterns
      • Multi-Variable Analysis
      • Classes of Distributions
    • Inferential Statistics
      • Understanding Inference
      • Sampling
      • Sample Size
      • Central Limit Theorem
    • Hypothesis Testing
      • Hypothesis Testing Goals
      • Statistical Significance
      • Risk; Alpha & Beta
      • Types of Hypothesis Test
    • Hyp-Tests: Normal Data
      • One and Two Sample t-tests
      • One Sample Variance
      • One Way ANOVA
    • Hyp-Tests: Non-Normal Data
      • Mann-Whitney & Mood’s Median
      • Kruskal-Wallis
      • Moods Median
      • Friedman
      • 1 Sample Sign
      • 1 Sample Wilcoxon
      • 1 and 2 Proportion
      • Chi-Squared
      • Test of Equal Variances
  1. IMPROVING PHASE
    • Simple Linear Regression
      • Correlation
      • X-Y Diagram
      • Regression Equations
      • Residuals Analysis
    • Multiple Regression
      • Non-Linear Regression
      • Multiple Linear Regression
      • Confidence Intervals
      • Residuals Analysis
      • Box-Cox Transformation
      • Stepwise Regression
      • Logistic Regression
    • Designed Experiments
      • Experiment Objectives
      • Experimental Methods
      • DOE Considerations
    • Full Factorial Experiments
      • 2k Full Factorial Designs
      • Linear & Quadratic Models
      • Orthogonal Designs
      • Model & Center Points
    • Fractional Factorials
      • Designs
      • Confounding Effects
      • Experimental Resolution
  1. CONTROLLING PHASE
    • Lean Controls
      • Control Methods for 5
      • Kanban
      • Poka-Yoke
    • SPC
      • Data Collection for SPC
      • I-MR Chart
      • Xbar-R Chart
      • U Chart
      • P Chart
      • NP Chart
      • X-S chart
      • CumSum Chart
      • EWMA Chart
      • Control Methods
      • Control Chart Anatomy
      • Variation & Sampling
      • Control Limits
    • Planning for Six Sigma Control
      • Cost Benefit Analysis
      • Control Plan Elements
      • Response Plan

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