Efforts for Excellence
Certification in Six Sigma
Total Quality Excellence
Six Sigma is a highly disciplined process that helps us focus on developing and delivering nearperfect products and services. Why ”Sigma“? The word is a statistical term that measures how far a given process deviates from perfection. The central idea behind Six Sigma is that if you can measure how many “defects” you have in a process, you can systematically figure out how to eliminate them and get as close to “zero defects” as possible. We have designed a systematic Training & Consulting approach to understand DMAIC & DMADV and its practical application.Lean is possible through distinct techniques such as flow charts, just in time, total quality management, workplace redesigning, and total productive maintenance. It focuses on delivering value to customers. A number of tools are deployed by the lean management system to link customer value to the process and people.
Shaping up Quality
OUR COURSES
Glance at Our Organizational core values
Program Objective : Six Sigma (White Belt)

Learning of Six Sigma methods (Overview)

Understanding of Six Sigma positioning roles

Variability introduction
Program Contents
1. Six Sigma Fundamentals
 Six Sigma Foundations and Principles
 Lean Foundations and Principles
 Six Sigma Roles and Responsibilities
 Team Basics
2. Define Phase
 Project Identification (Voice of Customer, Project Selection)
 Project Management (PM) Basics (Project charter, Communication plan)
3. Measure Phase
 Basic Statistics
 Data Collection plan
4. Analyze Phase
 Process Analysis Tools (LEAN tools)
 Root Cause Analysis
 Data Analysis (Basic distribution types, Common and special cause)
5. Improve and Control Phases
 Improvement Techniques (Kaizen and kaizen blitz, Plandocheckact (PDCA) cycle)
 Control Tools and Documentation (Control plan, Control Charts)
Program Objective : Six Sigma (Yellow Belt)

Learning of Six Sigma concepts and relate to the overall business objectives.

Use the fivestep DMAIC model to improve processes

Participate in the development of a project charter

Build and understand process maps, Pareto charts, affinity diagrams, trend charts, control charts, and histograms

Identify the root cause of a problem

Understand failure mode and effects analysis to set priorities for improvement

Document process changes and use a control plan to prevent backsliding.
Program Contents
1. Six Sigma Fundamentals
 Six Sigma Foundations and Principles
 Lean Foundations and Principles
 Six Sigma Roles and Responsibilities
 Team Basics
 Quality Tools and Six Sigma Metrics (Quality tools, Six Sigma metrics)
2. Define Phase
 Project Identification (Voice of Customer, Project Selection, Stakeholder analysis, Process inputs and outputs)
 Project Management (PM) Basics (Project charter, Communication plan, Project planning, Project management tools, Phase reviews)
3. Measure Phase
 Basic Statistics
 Data Collection (Data collection plans, Qualitative and quantitative data, Data collection techniques)
 Measurement System Analysis (MSA terms, Gauge reputability and reproducibility {GR&R})
4. Analyze Phase
 Process Analysis Tools (LEAN tools, FMEA)
 Root Cause Analysis
 Data Analysis (Basic distribution types, Common and special cause)
 Correlation and Regression (Correlation, Regression)
 Hypothesis Testing
5. Improve and Control Phases
 Improvement Techniques (Kaizen and kaizen blitz, Plandocheckact (PDCA) cycle, Costbenefit analysis)
 Control Tools and Documentation (Control plan, Control Charts, Document control)
Program Objective : Six Sigma (Green Belt)

Learning Function of Six Sigma

Learning to lead and execute processlevel improvement projects

Learn to collect process data and develop process maps

Develop statistical hypotheses using simple statistical tools

Apply problem solving and quantifiable tools to an improvement project brought to class on the first day

Learn how to execute the six sigma methodology
Program Contents
1. Six Sigma and the Organization
 Six Sigma and Organizational Goals (Value of Six Sigma, Organizational drivers and metrics, Organizational goals and Six Sigma projects)
 Lean Principles in the Organization (Lean concepts and tools, Valueadded and nonvalue added, Theory of constraints)
 Design for Six Sigma (DFSS) in the Organization (Quality function deployment (QFD), Design and process failure mode and effects analysis (DFMEA & PFMEA), Road maps for DFSS)
2. Six Sigma–Define
 Process Management for Projects (Process elements, Owners and stakeholders, Identify customers, Collect customer data, Analyze customer data, Translate customer requirements)
 Project Management Basics (Project charter and problem statement, Project scope, Project metrics, Project planning tools, Project documentation, Project risk analysis & Closure)
 Management and Planning Tools
 Business Results for Projects (Process performance metrics, Failure mode and effects analysis (FMEA))
 Team Dynamics and Performance (Team stages and dynamics design, Six Sigma and other team roles and responsibilities, Team tools, Communication)
3. Six Sigma–Measure
 Process Analysis and Documentation (Process modeling, Process inputs and outputs)
 Probability and Statistics (Drawing valid statistical conclusions, Central limit theorem and sampling distribution of the mean, Basic probability concepts)
 Collecting and Summarizing Data (Types of data and measurement scales, Data collection methods, Techniques for assuring data accuracy and integrity, Descriptive statistics, Graphical methods)
 Probability Distributions
 Measurement System Analysis
 Process Capability and Performance (Process capability studies, Process capability indices, Process performance vs. specification, Process performance indices, Shortterm vs. longterm capability)
4. Six Sigma–Analyze
 Exploratory Data Analysis (Multivari studies, Simple linear correlation and regression)
 Hypothesis Testing (Basic, Tests for means, variances, and proportions, Pairedcomparison, Singlefactor analysis of variance (ANOVA), Chi square)
5. Six Sigma–Improve and Control
 Design of Experiments (DOE) (Basic terms, Main effects)
 Statistical Process Control (SPC) (Objectives and benefits, Rational subgrouping, Selection and application of control charts, Analysis of control charts)
 Implement and Validate Solutions
 Control Plan
Program Objective : Six Sigma (Black Belt)

Achieve significant improvements in critical business processes.

Apply statistical and problem solving tools to an improvement project brought to class on the first day.

Collect, analyze, and quantify data that enable process improvements.

Establish and define process capability and Identify and eliminate dominant process variation sources.

Characterize and optimize processes by computing and applying statistical techniques.

Design, simulate, and execute designed experiments that depict validated improvement.

Learn how to plan and implement process control to hold project gains.
Program Contents
1. OrganizationWide Planning and Deployment
 Organizationwide Considerations (Fundamentals of Six Sigma and lean methodologies, Six Sigma, lean, and continuous improvement methodologies, Relationships among business systems and processes, Strategic planning and deployment for initiatives)
 Leadership (Roles and responsibilities, Organizational roadblocks and change management)
2. Organizational Process Management and Measures
 Impact on Stakeholders
 Benchmarking
 Business Measures (Performance measures, Financial measures)
3. Team Management
 Team Formation (Team types and constraints, Team roles and responsibilities, Team member selection criteria, Team success factors)
 Team Facilitation (Motivational techniques, Team stages of development, Team communication)
 Team Dynamics (Group behaviors, Meeting management, Team decisionmaking methods)
4. Team Training
 Needs assessment, Delivery, Evaluation
5. Define
 Voice of the Customer (Customer Identification, Customer data collection, customer requirements)
 Business Case and Project Charter (Business case, Problem statement, Project scope, Goals and objectives, Project performance measurements, Project charter review)
 Project Management (PM) Tools
 Analytical Tools
6. Measure
 Process Characteristics (Process flow metrics, Process analysis tools)
 Data Collection (Types of data, Measurement scales, Sampling, Data collection plans and methods)
 Measurement Systems (Measurement system analysis (MSA), Measurement systems across the organization, Metrology)
 Basic Statistics (Basic statistical terms, Central limit theorem, Descriptive statistics, Valid statistical conclusions)
 Probability (Basic concepts, Distributions)
 Process Capability (Process capability indices, Process performance indices, General process capability studies, Process capability for attributes data, Process capability for nonnormal data, Process performance vs. specification, Shortterm and longterm capability)
7. Analyze
 Measuring and Modeling Relationships Between Variable (Correlation coefficient, Linear regression, Multivariate tools)
 Hypothesis Testing (Terminology, Statistical vs. practical significance, Sample size, Point and interval estimates, Tests for means, variances, and proportions, Analysis of variance (ANOVA), Goodnessoffit (chi square) tests, Contingency tables, Nonparametric tests)
 Failure Mode and Effects Analysis (FMEA)
 Additional Analysis Methods (Gap analysis, Root cause analysis, Waste analysis)
8. Improve
 Design of Experiments (DOE) (Terminology, Design principles, Planning experiments, Onefactor experiments, Twolevel fractional factorial experiments, Full factorial experiments)
 Lean Methods (Waste elimination, Cycletime reduction, Kaizen, Other improvement tools and techniques)
9.Control
 Control Statistical Process Control (SPC) (Objectives, Selection of variables, Rational subgrouping, Control chart analysis)
 Other Controls (Total productive maintenance (TPM), Visual controls)
 Maintain Controls (Measurement system reanalysis, Control plan)
 Sustain Improvements (Lessons learned, Documentation, Training for process owners and staff, Ongoing evaluation)
10. Design for Six Sigma (DFSS) Framework and Methods
 Common DFSS Methodologies
 Design for X (DFX)
 Robust Designs
Program Objective : Problem Solving

Learn how to accurately identify the real problem in a given situation

Learn problem analysis best practices  using your decision time most effectively

Work through the steps of problem solving and decision making

Make important decisions with the greatest likelihood of generating expected

Learn valuable techniques and methodologies to expand your critical thinking ability

Adopt a more creative approach in solving problems
Program Contents
1. Problem Solving
 Introduction (Definition of problem, Steps in Defining a Problem, The problemsolving/decisionmaking cycle)
 An Introduction to Critical Thinking (Definition, Need of critical thinking)
 Factors which influence our natural decisionmaking
 Problem Analysis and Decision Making Best Practices
 A Toolkit and evaluation of Tools and Techniques
 Analytical DecisionMaking Techniques
Minitab Basic

Basic Minitab

Understand structure

Understand basic tools of Minitab

Correct data structure for analysis in Minitab

Create and interpret graph in Minitab
Program Contents
1. Minitab Basic
 Introduction to Statistical software – Minitab
 Basic graphs and Charts
 Normality testing basic
 Process Capability, MSA (ANOVA Method)
 Hypothesis test (1T test, 2T test, Test for equal variance, 1 way, 2 way, 1P, 2P, chi square)
 Multivari charts
 Regression –SLR, MLR and SPC control chart (I & MR, Xbar – R, P, U, C, nP)
Minitab Advance

Understand Indepth data structure in Minitab

Create and interpret advance graphs in Minitab

Understand advance tools in Minitab

Detailed tools and interpretation in DMAIC phases
Program Contents
1. Minitab Advance
 Introduction to Statistical software – Minitab
 Basic graphs and Charts
 Normality testing basic
 Process Capability, MSA (ANOVA Method)
 Hypothesis test (1T test, 2T test, Test for equal variance, 1 way, 2 way, Balance ANOVA, 1P, 2P, chi square)
 Multivari charts
 Regression –SLR, MLR and SPC control chart (I & MR, Xbar – R, P, U, C, nP)
FMEA

Identifying Failure modes assessing risk

Determining causes and occurrence

Develop a model to reduce failure mode

Improving the process
Program Contents
1. FMEA
 Introduction to FMEA
 Types of FMEA’s
 Developing Functions
 Function and Modelling
 Developing Failure Modes
 Determining Effects & Severity Ratings
 Determining Cause & Occurrence Ratings
 Controls & Detection Rating
 Assessing Risk