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Stability and Capability in Quality Improvement
  • Level Professional
  • Duration 10 hours
  • Course by University of Colorado Boulder
  • Offered by

About

In this course, you 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. You will create statistical process control charts for both continuous and discrete data using R software. You will analyze data sets for statistical control using control rules based on probability. Additionally, you 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. This course can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform. The MS-DS is an interdisciplinary degree that brings together faculty from CU Boulder’s departments of Applied Mathematics, Computer Science, Information Science, and others. With performance-based admissions and no application process, the MS-DS is ideal for individuals with a broad range of undergraduate education and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.

Modules

Introduction to Stability and Capability in Quality Improvement

    • 1 Videos
    • 2 Readings
    • 1 Discussion
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1 Discussions

  • Introduce Yourself!

1 Videos

  • Working in RStudio

2 Readings

  • Earn Academic Credit for your Work!
  • Course Support

Examine a Process and Break Down Components of Variation

    • 6 Videos
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6 Videos

  • Process Variation
  • Common and Special Cause Variation
  • Purpose of a Control Chart
  • Conformance Quality
  • The Product and Process Control Cycles
  • Process Dominance

Understand How to Use, Select, and Interpret Process Control Charts

    • 6 Videos
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6 Videos

  • 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

Discussion: Process Variation, Process Control, and Control Charts

    • 1 Discussion
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1 Discussions

  • Process Variation, Process Control, and Control Charts

Assessment: Process Variation, Process Control, and Control Charts

    • 1 Quiz
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1 Quiz

  • Process Variation, Process Control and Control Charts

Xbar and R Charts

    • 3 Videos
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3 Videos

  • Mean and Range Charts - Part 1
  • Mean and Range Charts - Part 2
  • Mean and Range Charts - Part 3

Xbar and S Charts

    • 2 Videos
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2 Videos

  • Mean and Standard Deviation Charts - Part 1
  • Mean and Standard Deviation Charts - Part 2

X and MR Charts - Normally Distributed

    • 4 Videos
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4 Videos

  • 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

Advanced Applications of the X and MR Chart

    • 2 Videos
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2 Videos

  • Setup Dominant Processes
  • Machine Dominant Processes

Discussion: Xbar and R / Xbar and S Charts / X and MR Charts

    • 1 Discussion
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1 Discussions

  • Xbar and R / Xbar and S Charts / X and MR Charts

Assessment: Xbar and R / Xbar and S Charts / X and MR Charts

    • 1 Quiz
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1 Quiz

  • Xbar and R / Xbar and S Charts / X and MR Charts

Introduction to X and MR Charts Non-Normal

    • 1 Videos
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1 Videos

  • Introduction

X and MR Charts - Log Transformed Non-Normal Data

    • 2 Videos
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2 Videos

  • Log Transformed Data - Part 1
  • Log Transformed Data - Part 2

X and MR Charts - Exponentially Distributed Data

    • 3 Videos
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3 Videos

  • Exponential Data - Part 1
  • Exponential Data - Part 2
  • Exponential Data - Part 3

X and MR Charts - Distribution Fitting

    • 6 Videos
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6 Videos

  • 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

Discussion: X and Moving Range Charts for Non-Normally Distributed Data

    • 1 Discussion
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1 Discussions

  • X and Moving Range Charts for Non-Normally Distributed Data

Assessment: X and Moving Range Charts for Non-Normally Distributed Data

    • 1 Quiz
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1 Quiz

  • X and Moving Range Charts for Non-Normally Distributed Data

Introduction to Capability

    • 4 Videos
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4 Videos

  • Process Control vs Process Capability
  • Capability Indices
  • Cpm and the Taguchi Loss Function
  • Capability vs Performance Measures

Capability / Performance for Normally Distributed Processes

    • 5 Videos
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5 Videos

  • 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 for Non-Normally Distributed Processes

    • 7 Videos
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7 Videos

  • 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

Discussion: Process Capability

    • 1 Discussion
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1 Discussions

  • Process Capability

Assessment: Process Capability

    • 1 Quiz
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1 Quiz

  • Process Capability

Introduction to Attribute / Discrete Control Charts

    • 1 Videos
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1 Videos

  • Introduction to Attribute Control Charts

p Charts for Attribute Data - Binomial Distribution

    • 3 Videos
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3 Videos

  • p Charts - Part 1
  • p Charts - Part 2
  • p Charts - Part 3

np Charts for Attribute Data - Binomial Distribution

    • 3 Videos
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3 Videos

  • np Charts - Part 1
  • np Charts - Part 2
  • np Charts - Part 3

c Charts for Attribute Data - Poisson Distribution

    • 3 Videos
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3 Videos

  • c Charts - Part 1
  • c Charts - Part 2
  • c Charts - Part 3

u Charts for Attribute Data - Poisson Distribution

    • 2 Videos
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2 Videos

  • u Charts - Part 1
  • u Charts - Part 2

Discussion: Attribute / Discrete Control Charts

    • 1 Discussion
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1 Discussions

  • Attribute / Discrete Control Charts

Assessment: Attribute / Discrete Control Charts

    • 1 Quiz
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1 Quiz

  • Attribute / Discrete Control Charts

Auto Summary

Discover the essentials of process stability and capability in quality improvement with this comprehensive course, perfect for professionals keen on honing their skills in statistical analysis. Dive into the world of Maths & Statistics as you learn to analyze process stability and implement statistical control using R software. You will master the creation of control charts for both continuous and discrete data, and understand the importance of a stable process before performing statistical hypothesis testing. This course is an integral part of CU Boulder’s prestigious Master of Science in Data Science (MS-DS) degree, available on Coursera. The MS-DS program is an interdisciplinary endeavor, combining expertise from the departments of Applied Mathematics, Computer Science, Information Science, and more. With no application process and performance-based admissions, it's accessible to individuals with diverse educational and professional backgrounds in relevant fields. Guided by expert instructors, the 600-minute course offers flexible subscription options, including Starter and Professional tiers. It’s tailored for those at a professional level, aiming to enhance their capability in meeting internal or external specifications and making informed decisions about process improvements. Join now and advance your career with practical, data-driven insights.

Wendy Martin
Instructor

Wendy Martin