Quality Control and Process Improvement with Minitab

How do organizations consistently deliver high-quality products and services while minimizing waste? The answer lies in data-driven quality control and systematic process improvement. This text-based course introduces you to the core principles of quality management and guides you through executing essential statistical analyses using Minitab. You will transition from understanding basic quality concepts to confidently interpreting control charts, capability analyses, and diagnostic plots. By learning how to translate process data into actionable insights, you will be equipped to identify defects, reduce variability, and support continuous improvement initiatives in any production or service environment. What you'll learn: - Understand foundational quality control concepts, including variability, Six Sigma principles, and the DMAIC framework - Navigate the Minitab interface to input, organize, and manage process data effectively - Construct and interpret Statistical Process Control (SPC) charts for both variable and attribute data - Perform process capability studies to determine if a system meets customer specifications - Apply hypothesis testing and regression analysis in Minitab to identify root causes of quality issues - Analyze measurement systems to ensure data integrity before making critical process decisions. This course begins with key terminology and the foundational philosophy of quality improvement before moving into step-by-step written walkthroughs of statistical tools in Minitab. You will read through practical scenarios, study clear data tables, and learn exactly how to interpret software outputs to make informed, data-driven decisions. This course is designed for beginners, aspiring quality analysts, production supervisors, and process engineers with no prior experience in Minitab or advanced statistics. Start reading today to master the fundamentals of statistical quality control and elevate your process improvement skills.