This course is designed to guide you on how to prepare for the American Society for Quality Certified Six Sigma Black Belt (ASQ CSSBB) certification, a mark of quality excellence across industries.
The course offers insights into the statistical tools for drawing valid conclusions, depicting relationships, analyzing measurement systems, testing hypotheses, designing experiments, applying statistical process control, and leading advanced Six Sigma projects across the enterprise.
By the end of this course, you will be able to:
- Identify the statistical analysis tools required for quality and process improvement in each phase of the DMAIC methodology.
- Describe the statistical processes of each phase of the DMAIC methodology used for operational efficiency.
- Apply statistical analysis tools for representing relationships, analyzing systems, and testing hypotheses.
- Implement design experiments and apply statistical process control to streamline business processes.
This course is best suited for employees working in process improvement teams, including individuals with significant experience leading and executing Six Sigma, lean, or other quality improvement projects.
Overview
Syllabus
- Statistical analysis and tools in the measure phase
- In this module, you will learn about the various statistical tools you can use for process analysis and data collection. The module delves into the statistical technique of measurement system analysis (MSA). You will also learn how to use graphical tools to construct and interpret diagrams and charts. You will be equipped with how the results of statistical studies are used to draw valid conclusions, the distribution methods relevant to probability, and the techniques used for process capability. Finally, you will learn to interpret the difference between short-term and long-term capabilities.
- Statistical analysis and tools in the analyze phase
- In this module, you will learn how to measure and model relationships between variables. You will explore the correlation coefficient, linear regression, and multivariate tools. The module also delves into applying the key concepts of hypothesis testing, such as the significance of testing, calculating sample size, and analyzing waste. You will become acquainted with techniques such as point and interval estimates and tests for means, variances, and proportions. Additionally, you will learn the analysis of variance (ANOVA) and goodness-of-fit (chi-square) tests and the techniques for analyzing and managing risk.
- Statistical analysis and tools in the improve and control phase
- In this module, you will explore the key concepts of the design of experiments (DOE). You will also learn how to apply the principles of DOE, such as power, sample size, balance, repetition, replication, order, efficiency, randomization, blocking, interaction, confounding, and resolution. The module will take you through planning and evaluating different types of experiments in DOE and various types of Lean methods you can use for process improvement, like waste elimination, cycle-time reduction, Kaizen, and others. Additionally, the module focuses on statistical process control (SPC) and other controls that help to streamline business processes. Finally, you will learn how to sustain process improvements using methods like documentation, training, and evaluation.
- Peer review assignment
- This is a peer-review assignment based on the concepts taught in the Advanced Statistical Analysis and Tools course. In this assignment, you have been provided with a real-life scenario. You must explain how you can use process capabilities and their related metrics in process improvement.
Taught by
Skill-Up EdTech Team and E R Suresh Narain
