Master statistical process control and capability analysis using R software for quality improvement.
Master statistical process control and capability analysis using R software for quality improvement.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Data Science Methods for Quality Improvement Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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Instructors:
English
What you'll learn
Create and interpret process control charts
Analyze process stability and variation
Assess process capability metrics
Handle normal and non-normal distributions
Implement quality control in R
Evaluate process improvements
Skills you'll gain
This course includes:
5.7 Hours PreRecorded video
5 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 5 modules in this course
This comprehensive course covers advanced techniques in statistical process control and capability analysis. Students learn to create and interpret various types of control charts for both normal and non-normal distributions, analyze process stability, and assess process capability against customer specifications. The curriculum emphasizes practical application using R software, covering everything from basic control charts to complex capability indices and performance measures.
Understanding Process Variation, Process Control and Control Charts
Module 1 · 2 Hours to complete
Xbar and R / Xbar and S Charts / X and MR Charts
Module 2 · 1 Hours to complete
X and Moving Range Charts for Non-Normally Distributed Data
Module 3 · 1 Hours to complete
Process Capability
Module 4 · 1 Hours to complete
Control Charts for Discrete Data
Module 5 · 1 Hours to complete
Fee Structure
Instructor
W. Edwards Deming Professor of Management
Wendy Martin is the W. Edwards Deming Professor of Management in the Lockheed-Martin Engineering Management Program at the University of Colorado Boulder, where she specializes in Quality Science. With a robust educational background, she earned her B.S. in Mechanical Engineering from Purdue University and a Master of Engineering from the University of Colorado Boulder, focusing on Six Sigma, quality systems, and applied statistics. Before her academic career, Wendy honed her skills in statistical methods through training at Luftig & Warren International and gained extensive industry experience during her 14 years at Anheuser-Busch, where she applied statistical techniques in an industrial setting.Since joining the Engineering Management program in 2014, Professor Martin has taught a variety of courses related to data analytics and quality management, including "Data Acquisition, Risk, and Estimation" and "Stability and Capability in Quality Improvement." Her expertise encompasses operational excellence, product quality, and reliability methods. In addition to her teaching responsibilities, she consults with organizations to address critical process-related challenges. Outside of academia, Wendy enjoys exploring generative AI and workflow automation, reflecting her commitment to continuous learning and innovation in both her professional and personal pursuits.
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