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Statistical Process Control (SPC) for TQM
New
Statistical Process Control (SPC) for TQM
Master the 7 QC Tools, Control Charts, Process Capability and Six Sigma Fundamentals
Created bySubburaj Ramasamy
Last updated 6/2026
English
What you'll learn
- Understand the principles and importance of Statistical Process Control (SPC) in Total Quality Management (TQM).
- Distinguish between common-cause variation and special-cause variation in processes.
- Apply the Seven Basic Quality Control (QC) Tools to analyze and improve process performance.
- Construct and interpret Histograms, Pareto Charts, Cause-and-Effect Diagrams, Check Sheets, Scatter Diagrams, Control Charts, and Stratification techniques.
- Select the appropriate control chart for different types of process data.
- Develop and interpret X̄-R, X̄-MR, p, np, c, and u control charts.
- Calculate and establish control limits for variables and attribute control charts.
- Apply SPC tools and techniques to manufacturing, service, and software processes.
- Understand the role of SPC in achieving customer satisfaction and organizational excellence.
- Gain practical knowledge through worked examples, case studies, and real-world applications.
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Course content
6 sections • 27 lectures • 5h 58m total length
Requirements
- logical thinking
Description
Statistical Process Control (SPC) for TQM
Master the 7 QC Tools, Control Charts, Process Capability and Six Sigma Fundamentals
In today's competitive environment, organizations must consistently deliver high-quality products and services while minimizing defects, reducing variation, and improving customer satisfaction. Statistical Process Control (SPC) is one of the most powerful methodologies for achieving these objectives and forms a cornerstone of Total Quality Management (TQM).
This comprehensive course introduces learners to the principles and practices of Statistical Process Control and demonstrates how data-driven quality management techniques can be used to monitor, control, and improve organizational processes.
The course begins with the fundamentals of quality management and process variation before introducing the Seven Basic Quality Control (QC) Tools widely used in manufacturing, service industries, and software development. Learners will then explore the theory and application of control charts for variables and attributes, enabling them to distinguish between common-cause and special-cause variation and make informed decisions based on statistical evidence.
In addition, the course introduces process capability concepts and provides an overview of Six Sigma fundamentals, including DPMO, Sigma Levels, DMAIC methodology, Critical-to-Quality (CTQ) characteristics, and the relationship between SPC and Six Sigma.
What You Will Learn
• Understand the principles and importance of Statistical Process Control (SPC)
• Apply the Seven Basic Quality Control (QC) Tools for quality improvement
• Construct and interpret Histograms, Pareto Charts, Cause-and-Effect Diagrams, Check Sheets, Scatter Diagrams, Control Charts, and Stratification techniques
• Understand process variation and distinguish between common and special causes
• Develop and interpret X̄-R, X̄-mR, p, np, c, and u control charts
• Establish and interpret control limits
• Monitor and improve process performance using SPC techniques
• Understand process capability and its role in quality improvement
• Learn the fundamentals of Six Sigma, DPMO, Sigma Levels, DMAIC, and CTQ
• Apply quality improvement concepts to manufacturing, service, and software processes
Who Should Take This Course?
• Quality Engineers and Quality Assurance Professionals
• Manufacturing, Production, and Process Engineers
• Quality Managers and Operations Managers
• Industrial Engineering and Management Students
• Software Quality and Reliability Professionals
• Lean and Six Sigma Practitioners
• Anyone interested in TQM, SPC, and Continuous Improvement
Course Features
• Clear and systematic explanations
• Practical examples and case studies
• Industry-oriented approach
• Coverage of both classical SPC and introductory Six Sigma concepts
• Suitable for beginners as well as practicing professionals
Whether you are a student, engineer, manager, quality professional, or continuous improvement practitioner, this course will equip you with the knowledge and practical skills required to understand, implement, and benefit from Statistical Process Control and modern quality management techniques.
Who this course is for:
- This course is designed for quality professionals, engineers, managers, supervisors, students, and practitioners who wish to understand and apply Statistical Process Control (SPC) techniques for process monitoring and quality improvement. The course will be particularly valuable for: • Quality Engineers, Quality Analysts, and Quality Assurance Professionals seeking practical knowledge of SPC and quality control tools. • Manufacturing Engineers, Production Engineers, and Process Engineers involved in process monitoring, defect reduction, and continuous improvement initiatives. • Quality Managers, Production Managers, and Operations Managers responsible for maintaining process stability and improving organizational performance. • Students of Engineering, Management, and Industrial Engineering who wish to develop industry-relevant quality management skills. • Professionals preparing for careers in Quality Management, Operational Excellence, Lean Manufacturing, or Six Sigma. • Software Quality Assurance and Software Reliability professionals interested in understanding the application of statistical quality techniques to software processes. • Anyone interested in Total Quality Management (TQM), continuous improvement, and data-driven decision-making. No prior knowledge of Statistical Process Control is required. The course begins with the fundamentals and progressively develops the learner's ability to apply the Seven QC Tools and Control Charts in real-world situations.