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Efforts for Excellence

Certification in Six Sigma

Total Quality Excellence
service-certification-in-six-sigma
Six Sigma is a highly disciplined process that helps us focus on developing and delivering near-perfect 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

Six Sigma (White Belt)

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, Plan-do-check-act (PDCA) cycle)
  • Control Tools and Documentation (Control plan, Control Charts)

Six Sigma (Yellow Belt)

Program Objective : Six Sigma (Yellow Belt)

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

  • Use the five-step D-M-A-I-C 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, Plan-do-check-act (PDCA) cycle, Cost-benefit analysis)
  • Control Tools and Documentation (Control plan, Control Charts, Document control)

Six Sigma (Green Belt)

Program Objective : Six Sigma (Green Belt)

  • Learning Function of Six Sigma

  • Learning to lead and execute process-level 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, Value-added and non-value- 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, Short-term vs. long-term capability)

4. Six Sigma–Analyze

  • Exploratory Data Analysis (Multi-vari studies, Simple linear correlation and regression)
  • Hypothesis Testing (Basic, Tests for means, variances, and proportions, Paired-comparison, Single-factor 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

Six Sigma (Black Belt)

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. Organization-Wide Planning and Deployment

  • Organization-wide 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 decision-making 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 non-normal data, Process performance vs. specification, Short-term and long-term 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), Goodness-of-fit (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, One-factor experiments, Two-level fractional factorial experiments, Full factorial   experiments)
  • Lean Methods (Waste elimination, Cycle-time 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

Problem Solving

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 problem-solving/decision-making cycle)
  • An Introduction to Critical Thinking (Definition, Need of critical thinking)
  • Factors which influence our natural decision-making
  • Problem Analysis and Decision Making Best Practices
  • A Toolkit and evaluation of Tools and Techniques
  • Analytical Decision-Making Techniques

Minitab Basic

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)
  • Multi-vari charts
  • Regression –SLR, MLR and SPC control chart (I & MR, Xbar – R, P, U, C, nP)

Minitab Advance

Minitab Advance

  • Understand In-depth 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)
  • Multi-vari charts
  • Regression –SLR, MLR and SPC control chart (I & MR, Xbar – R, P, U, C, nP)

FMEA

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

Practical Case Study

All the programs are based on practical case study and real life data

Exercises

Hands-on exercise for the better understanding of the concepts

Interaction

Open and interactive environment for learning through sharing

Simulation

Simulation exercise for in-depth conceptual clarity

Videos

Real life relevant videos and clips for better understanding

Discussion

Networking and Discussion to retain relevant learning for longer time

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