SIX-SIGMA BELTs

A Six-Sigma Green Belt (SSGB) is a qualified professional who has a knowhow of Six-Sigma philosophies & principles, DMAIC approach including various statistical & analytical methods, problem solving tools & techniques. They work along with Six-Sigma Black Belt (SSBB) professionals at various levels in continuous improvement projects.

A Six-Sigma Black Belt (SSBB) is a professional who, over & above green belt level skills, thoroughly understands advanced statistical & analytical tools, can demonstrate leadership skills, manage changes, facilitate teams and evaluate business impact of continuous improvement projects.

FOR WHOM

Professionals from Quality, Engineering, R&D, Manufacturing & Supply Chain functions.

Leaders, experts & practitioners of Continuous Improvement & Operational Excellence initiatives.

Decision makers and aspirants from Data Science & Analytics domains.

Existing Green/Black Belt professionals may also attend the program to gain indepth & practical knowledge on advanced concepts.

Freshers or working professional looking for better career opportunities or industry change

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BODY OF KNOWLEDGE


Contents for GB & BB Additional Contents for BB
Foundation
  • Fundamentals of Quality, Continuous Improvement & Problem Solving
  • History, Philosophy & Evolution of Six-Sigma
  • Where & when to use Six-Sigma
  • Overview of DMAIC & DMADV approach
  • Planning & Deploying Six-Sigma Initiative
  • Alignment with Business Processes & Measures
  • Leadership & team facilitation
  • Managing project & changes
  • Interface with Business Analytics, AI & ML
Statistics, Analytics & Quantitative Techniques
  • Types of Data / Scale, Statistical Terms
  • Descriptive Statistics & Inferential Statistics
  • Graphical Analysis
  • Understanding shape, Location & Dispersion
  • Sampling, Bias, Risk & Confidence Level/Interval
  • Normal Distribution & Central Limit Theorem
  • Descriptive, Predictive & Prescriptive Analytics
  • Other Continuous & Discrete Distributions
  • Advanced Inferential Statistics
  • Forecasting
  • Multivariate analysis
  • Linear Programming & Optimization Basics
  • Montecarlo Simulations
  • Using Minitab
Define
  • Identifying & validating opportunity (KPM Tree, Stratification & Prioritization, Project Risk Assessment, Project Charter)
  • Plant-Process-Product-Problem Studies (Problem Definition, Process Mapping & Walkthrough)
  • Quick-win identification & implementation
  • Voice of Customer, Voice of Business, Cost of Poor Quality
Measure
  • Understanding variables to be measured
  • Measurement System Analysis (Average Range & Range Methods, Visual Inspection Method)
  • Data collection & stratification
  • Stability Study (Control Charts for attributes and variables)
  • Capability & Performance Studies (Cp, Cpk, Pp, Ppk, DPMO, DPMU, RTY, sigma level, etc)
  • Advance Measurement System Analysis (ANOVA Method, Signal Detection & Kappa methods, MSA for Destructive & Automatic Inspections, Cg / Cgk, etc)
  • Advanced Capability & Performance Studies (Cpm, Percentile Method)
  • Identifying & transforming non-normal data (Box-Cox Transformation)
Analyze
  • Hypothesis Testing Concepts (null & alternate hypothesis, power & confidence level, alpha & beta errors, various types of comparisons)
  • Establishing relationship between variables (Scatter, Correlation; Simple & Multiple Linear Regression)
  • Normality & Independence test; Test for Variances, Means & proportions
  • Multivary Chart
  • Logistic Regression
  • Non-parametric tests (Test for Medians)
  • Process FMEA
  • Design of Experiments (DOE) - Factorial, Placket Burman & Taguchi
  • Component Search, Paired Comparisons, Variable Search
Improve
  • Ideation, Idea evaluation (prioritization matrix,Pugh Matrix, Matrix Data Analysis)
  • Pilot implementation & result verification
  • TRIZ
  • Hypothesis Testing for Validating Solutions
  • B vs C Test
Control
  • Control Plans
  • SPC, Poka-Yoke, Visual Controls, Layered Audits
  • Documentation, Training & Closure
  • Financial evaluations (B/C Ratio, NPV, IRR,Payback, etc)

CERTIFICATION

Participants would be recognized as “Certified Six-Sigma Green Belt or Black Belt” upon successfully completing respective course and qualifying comprehensive evaluation which includes

  • Attendance (30%)
  • Class Participation (20%)
  • Quizzes (20%)
  • Simulations / Assignments (30%)

Minimum 60% score is required to qualify comprehensive evaluation.

Those who do not qualify comprehensive evaluation will be issued “Certificate of Participation”

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WHY LEANEXT



“Our program is aimed at building competency for applying advance level Six-Sigma methodology to solve complex business problems, drive continuous improvement and achieve Operational Excellence”


  • Trainer with thorough domain knowledge and hands-on experience of applying Lean Six-Sigma across manufacturing, process & service industries
  • Practical guidelines on problem solving tools & techniques arranged in a systematic & effective manner.
  • Application oriented approach in addition to building strong fundamentals
  • Latest & advanced curriculum benchmarked with international certifications
  • Contents designed to cater needs of diverse industry applications.
  • Blended approach for better engagement & effective learning.
  • Instructor led live virtual & Interactive sessions with examples, cases & videos.
  • Simulations and activities for experiential learning.
  • Hands-on practice on Minitab Software and Excel.
  • Soft copy of reference materials, books & project templates.
  • Session recordings available for limited missed sessions for limited period.
  • Online Guidance on real-life project within 6 months of completing training


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