Lean Six Sigma Green Belt
INTRODUCTION
Six Sigma is a business strategy that focuses on improving customer requirements understanding, business systems, productivity, and financial performance. Six Sigma can be seen as a philosophy or strategy used to improve the efficiency and effectiveness of business processes to meet or exceed customers’ needs and expectations. Six Sigma is accoutered with following key elements or features, which when properly applied will ensure business success: customer focus, data driven analysis, statistically based decisions, root cause problem identification and elimination, process oriented thinking, process control mechanism to sustain improvements and sharing of results. The term ‘Lean Thinking’ refers to the use of ideas employed to improve the processes in all departments of an enterprise. Now days we are hearing about term ‘Lean Six sigma’ into a greater frequency because process implementation requires aspect of both approaches to attain positive results. Lean Six Sigma combines the power of Six Sigma i.e strategic alignment, customer focus and rigorous analytical tools with Lean focus on speed, delivering quantum leap in performance improvement with breakthrough results.
PROGRAMME OBJECTIVES
The course is targeted at students who need to develop a general awareness of Six Sigma and Lean Thinking: what it is, why it matters, what makes it successful. The aim of the course is to familiarize the students with basic quality management principles and further build on an in-depth knowledge of Six Sigma and Lean Thinking methodology to deal with problems independently. In this course, with the help of the relevant software (Minitab, iGraphx), we as a team would try to develop Six Sigma experts so that they could take up the onus of sustaining the Six Sigma movement further on their own.
PROGRAMME CONTENT
Introduction to Six Sigma Methodology; Identification, Prioritization and selection of Improvement opportunities Roles & responsibilities in Six Sigma implementation, Over view of Six Sigma Project execution [DMAIC (DefineMeasure- Analyze- Improve & Control)] 2. Development of business cases. Translating the needs of the customer into the specific requirements - Development of Project Team and Charter, Define and Map Processes to be improved (SIPOC / COPIS); Identification of Critical to Customer (CTC) / Critical to Business (CTB) characteristics. 3. Data Collection planning, Type of Data, Introduction to statistical software packages for data display and analysis, Measurement System Evaluation (Gauge R&R) for variables as well as attribute data, Understanding variation-special causes vs. common causes through dot plots, box plots, histogram and control charts, Stratification methods through Pareto, Bar Diagrams, stratified dot plot, etc, Evaluation of Process Capability and Sigma level. 4. Process mapping including activity flow chart, identification of value-added and non-value-added activities (Lean Sigma), Organizing for potential causes using cause and effect diagram, Verification/validation of causes using work place investigation (GEMBA), FMEA, Concept of correlation and Regression and use of the same in validating causes, Concepts of Test of Hypothesis, Concepts of industrial experimentation. 5. Selection and prioritization of solutions for the validated causes including concept of risk analysis, developing plan for pilot and full scale implementation. 6. Development of the process control plans, Evaluation and monitoring mechanism (SPC), process audits, comparison of results after implementation of the solutions, institutionalization and integration of the solutions, project closure.
TARGET GROUP
The Certificate programme is designed for those Practitioners and Academicians who are interested in learning a structured approach to engage their multifunctional teams and peers in effective problem definition and solution approaches for complex business challenges.
TRAINING METHDOLOGY
Through CONTINOUS LEARNING AND INTERATIVE PROGAMME, Conducting test with Real time application of projects with exposure to data analysis using simple