LEAN SIX SIGMA BLACK BELT TRAINING

Our IT training courses are developed with industry-standards and career-focused technologies.


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Award:
Certification
Awarding Body:
IASSC
Duration & Study Mode:
Full time, Part-time, Evening and Weekends, Virtual online
Location:
London, Flexible online
Duration: 5 Days / 5 Weeks

This five-day course is specially designed for IT professionals who have some experience with Windows Server. It is designed for professionals who will be responsible for managing storage and compute by using Windows Server 2016, and who need to understand the scenarios, requirements, and storage and compute options that are available and applicable to Windows Server 2016.

Prerequisites

  • There are no prerequisites for this Lean Six Sigma Black Belt training course. Hence, anyone can attend.
  • This certification is a prerequisite for any individual wishing to pursue Level II Black Belt Certification which does have a project requirement.

What will you gain after this course

  • By using Minitab, you can do a ‘real’ data analysis.
  • As a Black Belt in Six Sigma, you will be able to solve complicated challenges.

Jobs you can get
with a LEAN SIX SIGMA BLACK BELT TRAINING

  • Project Manager
  • Developer
  • Consultant
  • Program Manager
  • Business Development Officer

Corporate Group Training

  • Customized Training
  • Onsite / Virtual
  • Instructor-led Delivery
  • For small to large groups

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Who is this certification for?

  • This training course is highly suggested for anyone interested in improving business performance, especially managers, because the Black Belt certification demonstrates a commitment to business effectiveness development.
  • Project Engineers, Management Consultants, Process Developers, and anybody working in production are some of the additional occupations that may learn from this certificate.


Syllabus

  • The Basics of Six Sigma
  • Meanings of Six Sigma
  • General History of Six Sigma & Continuous Improvement
  • Deliverables of a Lean Six Sigma Project
  • The Problem Solving Strategy Y = f(x)
  • Voice of the Customer, Business and Employee
  • Six Sigma Roles & Responsibilities
  • The Fundamentals of Six Sigma
  • Defining a Process
  • Critical to Quality Characteristics (CTQ’s)
  • Cost of Poor Quality (COPQ)
  • Pareto Analysis (80:20 rule)
  • Basic Six Sigma Metrics
  • Selecting Lean Six Sigma Projects
  • Building a Business Case & Project Charter
  • Developing Project Metrics
  • Financial Evaluation & Benefits Capture
  • The Lean Enterprise
  • Understanding Lean
  • The History of Lean
  • Lean & Six Sigma
  • The Seven Elements of Waste
  • Process Definition
  • Cause & Effect / Fishbone Diagrams
  • Process Mapping, SIPOC, Value Stream Map
  • Failure Modes & Effects Analysis (FMEA)
  • Six Sigma Statistics
  • Basic Statistics
  • Descriptive Statistics
  • Normal Distributions & Normality
  • Graphical Analysis
  • Measurement System Analysis
  • Precision & Accuracy
  • Bias, Linearity & Stability
  • Gage Repeatability & Reproducibility
  • Variable & Attribute MSA
  • Process Capability
  • Capability Analysis
  • Concept of Stability
  • Attribute & Discrete Capability
  • Monitoring Techniques
  • Patterns of Variation
  • Multi-Vari Analysis
  • Classes of Distributions
  • Inferential Statistics
  • Understanding Inference
  • Sampling Techniques & Uses
  • Central Limit Theorem
  • Hypothesis Testing
  • General Concepts & Goals of Hypothesis Testing
  • Significance; Practical vs. Statistical
  • Risk; Alpha & Beta
  • Types of Hypothesis Test
  • Hypothesis Testing with Normal Data
  • 1 & 2 sample t-tests
  • 1 sample variance
  • One Way ANOVA
  • Hypothesis Testing with Non-Normal Data
  • Mann-Whitney
  • Kruskal-Wallis
  • Mood’s Median
  • Friedman
  • 1 Sample Sign
  • 1 Sample Wilcoxon
  • One and Two Sample Proportion
  • Chi-Squared (Contingency Tables)
  • Simple Linear Regression
  • Correlation
  • Regression Equations
  • Residuals Analysis
  • Multiple Regression Analysis
  • Non- Linear Regression
  • Multiple Linear Regression
  • Confidence & Prediction Intervals
  • Residuals Analysis
  • Data Transformation, Box Cox
  • Designed Experiments
  • Experiment Objectives
  • Experimental Methods
  • Experiment Design Considerations
  • Full Factorial Experiments
  • 2k Full Factorial Designs
  • Linear & Quadratic Mathematical Models
  • Balanced & Orthogonal Designs
  • Fit, Diagnose Model and Center Points
  • Fractional Factorial Experiments
  • Designs
  • Confounding Effects
  • Experimental Resolution
  • Lean Controls
  • Control Methods for 5S
  • Kanban
  • Poka-Yoke (Mistake Proofing)
  • Statistical Process Control (SPC)
  • Data Collection for SPC
  • I-MR Chart
  • Xbar-R Chart
  • U Chart
  • P Chart
  • NP Chart
  • Xbar-S Chart
  • CuSum Chart
  • EWMA Chart
  • Control Methods
  • Control Chart Anatomy
  • Subgroups, Impact of Variation, Frequency of Sampling
  • Center Line & Control Limit Calculations
  • Six Sigma Control Plans
  • Cost Benefit Analysis
  • Elements of the Control Plan
  • Elements of the Response Plan

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