University of Colorado Boulder - Stability and Capability in Quality Improvement
- Offered byCoursera
Stability and Capability in Quality Improvement at Coursera Overview
Duration | 9 hours |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Stability and Capability in Quality Improvement at Coursera Highlights
- Flexible deadlines Reset deadlines in accordance to the schedule
- Earn a certificate upon completion from Coursera
Stability and Capability in Quality Improvement at Coursera Course details
- In this course, students will learn to analyze data in terms of process stability and statistical control and why having a stable process is imperative prior to perform statistical hypothesis testing Learners will create statistical process control charts for both continuous and discrete data using R software
- Students will analyze data sets for statistical control using control rules based on probability
- Additionally, they will learn how to assess a process with respect to how capable it is of meeting specifications, either internal or external, and make decisions about process improvement
Stability and Capability in Quality Improvement at Coursera Curriculum
Understanding Process Variation, Process Control and Control Charts
Process Variation
Common and Special Cause Variation
Purpose of a Control Chart
Conformance Quality
The Product and Process Control Cycles
Process Dominance
Control Chart Basics
Creating a Control Chart - Steps 1 and 2
Creating a Control Chart - Step 2 (continued)
Creating a Control Chart - Step 3
Creating a Control Chart - Step 4
Creating a Control Chart - Steps 5, 6 and 7
Process Variation, Process Control and Control Charts
Xbar and R / Xbar and S Charts / X and MR Charts
Mean and Range Charts - Part 1
Mean and Range Charts - Part 2
Mean and Range Charts - Part 3
Mean and Standard Deviation Charts - Part 1
Mean and Standard Deviation Charts - Part 2
Individuals and Moving Range Charts - Part 1
Individuals and Moving Range Charts - Part 2
Individuals and Moving Range Charts - Part 3
Individuals and Moving Range Charts - Part 4
Setup Dominant Processes
Machine Dominant Processes
Xbar and R / Xbar and S Charts / X and MR Charts
X and Moving Range Charts for Non-Normally Distributed Data
Introduction
Log Transformed Data - Part 1
Log Transformed Data - Part 2
Exponential Data - Part 1
Exponential Data - Part 2
Exponential Data - Part 3
Introduction to Distribution Fitting
Goodness of Fit Testing - One Distribution
Goodness of Fit Testing - Multiple Distributions
The Johnson Distribution - Part 1
The Johnson Distribution - Part 2
Selecting the Best Fit and Creating the Control Chart
X and Moving Range Charts for Non-Normally Distributed Data
Process Capability
Process Control vs Process Capability
Capability Indices
Cpm and the Taguchi Loss Function
Capability vs Performance Measures
Capability / Performance - Xbar and R chart Part 1
Capability / Performance - Xbar and R chart Part 2
Capability / Performance - Xbar and s chart Part 1
Capability / Performance - Xbar and s chart Part 2
Capability / Performance - X and MR chart
Capability / Performance - Transformed Data Part 1
Capability / Performance - Transformed Data Part 2
Capability / Performance - Transformed Data Part 3
Capability / Performance - Exponential Part 1
Capability / Performance - Exponential Part 2
Capability / Performance - Distribution Fitting Part 1
Capability / Performance - Distribution Fitting Part 2
Process Capability
Control Charts for Discrete Data
Introduction to Attribute Control Charts
p Charts - Part 1
p Charts - Part 2
p Charts - Part 3
np Charts - Part 1
np Charts - Part 2
np Charts - Part 3
c Charts - Part 1
c Charts - Part 2
c Charts - Part 3
u Charts - Part 1
u Charts - Part 2
Attribute / Discrete Control Charts
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