Six Sigma Yellow Belt: Advanced Process Optimization for Engineers

In today’s data-driven engineering landscape, the ability to translate raw numbers into actionable process improvements is a core competency. This 1-day intensive program is designed to bridge the gap between statistical theory and practical engineering application, providing a robust framework for quality analysis and operational excellence.

Program Objectives

By the end of this certification program, participants will be able to:

• Visualize Variation: Use high-level graphical tools to identify root causes and patterns within manufacturing or design data.
• Implement DMAIC: Execute the Define, Measure, Analyze, Improve, and Control framework to streamline workflows, eliminate defects, and reduce waste.
• Statistical Validation: Utilize Hypothesis testing and ANOVA (Analysis of Variance) to provide data-backed evidence for engineering decisions.
• Predictive Modeling: Apply regression analysis and correlation studies to forecast process behavior under varying conditions.

Agenda of the session

The session will be a mix of theory and practical execises. Agenda for the 1-day training will be:  

Introduction: Six Sigma overview, understanding Six Sigma, history of quality programs, the DMAIC methodology 

Define: Defining the problem, project charter, process mapping, SIPOC diagram, Cost of Poor Quality (COPQ) 

Measure: Sources for data collection, data types, descriptive statistics, testing for normality

Analyze: Determing baseline process capability Cp, CpK), selection of proper analytics tools, normality testing and z scores, hypothesis testing and tools (including Analysis of Variance, ANOVA), correlation analysis

Improve: Validation and measuring the effects of process improvements, regression analysis

Control: Types of controls, chossing and applying the proper controls (such as I-MR Xbar, p-charts and more), process monitoring, developing standard operationg procedures (SOP)

Why This Training Matters for Engineers

Engineering is often a battle against entropy and variation. This program provides the "Yellow Belt" toolkit to move beyond trial-and-error troubleshooting. By combining Lean Six Sigma history with modern statistical workouts, participants will leave with the ability to quantify their impact on the bottom line and deliver higher-quality outputs with greater efficiency 

Join us for an exclusive training course led by Professor K. Muralidharan from University of Baroda, India. With fellowships from the Royal Statistical Society (UK) and a long list of publications, Professor K. Muralidharan is renowned for his work specializing in statistics, quality management, and Six Sigma. He has published extensively on industrial statistics and reliability, amoung "Six Sigma for Organizational Excellence: A Statistical Approach (2015)" and "Statistical Methods for Quality, Reliability and Maintainability (2012)". 

The book ""Six Sigma for Organizational Excellence: A Statistical Approach" will be provided to the students during the training.

Meals and drinks are included in the session.