This course introduces the principles and practical applications of Statistical Process Control (SPC) in the microelectronics packaging industry. Students explore statistical methods used to monitor manufacturing processes, evaluate quality, reduce variation, and improve process performance.
Topics include the evolution of quality management, Six Sigma methodologies, and the DMAIC framework. Students learn to apply descriptive statistics, conduct measurement system analyses, select and interpret control charts, and calculate process capability indices to determine whether manufacturing processes meet specified requirements.
Through practical applications and statistical software tools, students develop the skills to analyze process data, evaluate stability and capability, and support data-driven quality improvement in microelectronics packaging and manufacturing.
This course includes 15 lectures divided by topic into 5 modules. Each module concludes with a brief assessment.
Format: Online, asynchronous
Platform: Canvas via nanoHUB
Estimated Time: 7 hours
Level: Advanced Undergraduate/Graduate Student
Prerequisites: Engineering mathematics and introductory probability and statistics
Instructor: Professor Dhruv Bhate of Arizona State University
Course Objectives
Describe the evolution of quality, identifying the critical contributions of key historical figures to the quality movement, and place major movements in appropriate historical order.
Articulate the important components of Six Sigma. Be able to identify major requirements of each step in the DMAIC process.
Identify and calculate useful descriptive statistics. Demonstrate the ability to perform statistical analyses – choose the appropriate formula to apply, calculate it correctly, and make appropriate interpretations.
Conduct a measurement system analysis. Compute the statistics and properly interpret the results. Identify appropriate next steps, based on results.
Demonstrate the ability to use statistical process control in a variety of situations. Choose the appropriate SPC chart to use for monitoring and/or controlling variation. Demonstrate the ability to appropriately construct and interpret the chart in a variety of situations. Recognize a situation that does not meet underlying assumptions and be able to recommend appropriate steps to make SPC valid and useful.
Construct and interpret capability indices. Demonstrate ability to construct indices by hand and using software and make appropriate interpretations.
Develop familiarity with how to use modern software in performing a measurement system analysis, construction of control charts, evaluation of process stability and capability.
Request Course Enrollment
To enroll in this course, complete the course registration form. The SCALE team will review your request and arrange enrollment in the Canvas course on nanoHUB.