Stability and Capability in Quality Improvement from Coursera

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.

What's inside

Syllabus

Understanding Process Variation, Process Control and Control Charts

In this module, you will learn how to define a process and break it down into components for the purpose of identifying potential sources of variation. You will learn how to classify variation into common and special causes through the use of a control chart. You’ll discover the Taguchi Loss function, and how it relates to the philosophy of quality, and its association to the product control and process control cycles. You will learn the basic anatomy of a control chart as well as the process used to create a control chart, and common errors encountered when using a control chart in practice. You will be able to calculate an appropriate sample size, as well as determine when a process is in control or out of control based on statistical rules.

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

In this module, you will learn how to select the appropriate chart given information on sample size and data type. You’ll learn how to create and interpret control charts with subgroups for variables data, as well as how to create them in R. You will also create and interpret control charts with a sample size of one data that is normally distributed. You'll learn how to monitor other statistics using the Individuals and Moving Range Chart. Finally, you will interpret the control charts for statistical control / stability.

X and Moving Range Charts for Non-Normally Distributed Data

In this module, you will learn how to create an X and Moving Range Chart when the underlying distribution is not normally distributed. You’ll learn how to calculate control limits for the X and MR Charts with LogNormal transformed distribution and exponential distribution. Additionally, you will learn how to fit a distribution to the data and calculate control limits associated with the selected distribution. Finally, you will interpret the control charts for statistical control / stability.

Process Capability

In this module, you will learn how to compare process variation to customer specifications. You’ll learn the three indices associated with capability measures and the three indices associated with performance measures. Additionally, you will learn to assess capability and performance when the data are not normally distributed.

Control Charts for Discrete Data

In this module, you will learn how to create and analyze control charts for discrete data. You will learn how to differentiate between data that are Binomial and data that are Poisson distributed in order to select the appropriate control chart. Additionally, you will learn to assess capability using an appropriate discrete probability model.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Appropriate for professionals seeking to improve their data analysis skills in process control and management

Suitable for learners with a working knowledge of statistics and probability

Provides a strong foundation in statistical process control techniques and their application in real-world scenarios

Coursework can be applied towards a Master's degree in Data Science from CU Boulder

Utilizes R software for hands-on exercises and data analysis

Taught by instructors with industry experience in data analytics and process improvement

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Stability and Capability in Quality Improvement with these activities:

Statistical Methods for Quality Improvement

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Review the book for a more thorough understanding of the statistical methods used in quality improvement.

View The Six Sigma Handbook, Sixth Edition: A... on Amazon

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Read the book.
Take notes on the key concepts.
Complete the exercises at the end of each chapter.

Introduction to Statistical Quality Control

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Review the book for a more thorough understanding of the fundamental principles of statistical quality control.

View Applied Statistics and Probability for... on Amazon

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Read the book.
Take notes on the key concepts.
Complete the exercises at the end of each chapter.

Write an R Script for Statistical Process Control

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Develop an R script to apply statistical process control techniques to a dataset.

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Install the necessary R packages.
Load the dataset into R.
Create control charts for the data.
Perform statistical tests to identify any out-of-control points.

Six other activities

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Interpret Statistical Process Control Charts

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Practice interpreting control charts to identify and analyze process variability and stability.

Browse courses on Control Charts

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Download data sets with known process patterns.
Create control charts in R for the data sets.
Analyze the control charts to identify any patterns or deviations.
Write a report summarizing the findings and recommendations.

Statistical Process Control Study Group

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Join or start a study group with other students to discuss statistical process control concepts and work on problems together.

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Find a group of students who are interested in forming a study group.
Decide on a meeting time and place.
Prepare for each meeting by reading the assigned material and working on problems.
Attend the meetings and actively participate in the discussions.

Control Chart Exercises

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Practice creating and interpreting control charts to improve your understanding of process stability and statistical control.

Browse courses on Control Charts

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Find a dataset that contains process data.
Create a control chart for the data.
Interpret the control chart to identify any out-of-control points.

Design a Statistical Sampling Plan

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Develop a sampling plan to ensure that samples are representative of the population and provide reliable data for analysis.

Browse courses on Sampling

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Determine the purpose and objectives of the sampling plan.
Define the population of interest.
Select the appropriate sampling method.
Calculate the sample size.
Develop a sampling procedure.

Statistical Process Control Presentation

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Create a presentation on statistical process control to demonstrate your understanding of the concepts and principles.

Browse courses on Statistical Process Control

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Choose a specific topic within statistical process control to focus on.
Research the topic and gather information from credible sources.
Create a presentation that includes an introduction, body, and conclusion.
Practice your presentation and get feedback from others.

Process Improvement Project

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Start a project to improve a process in your workplace or community using statistical process control techniques.

Browse courses on Process Improvement

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Identify a process that needs improvement.
Collect data on the process.
Analyze the data using statistical process control techniques.
Develop and implement a plan to improve the process.
Monitor the process to ensure that the improvements are sustained.

Career center

Learners who complete Stability and Capability in Quality Improvement will develop knowledge and skills that may be useful to these careers:

Management Consultant

Management consultants are responsible for advising clients on how to improve their businesses. They work with clients to identify problems, develop solutions, and implement changes. This course may be useful for management consultants because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help management consultants to identify problems more accurately and to develop more effective solutions.

See salaries and explore the career path for Management Consultant

Project Manager

Project managers are responsible for planning and executing projects. They work with other departments to ensure that projects are completed on time, within budget, and to the required quality standards. This course may be useful for project managers because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help project managers to identify and mitigate risks more effectively and to ensure that projects are completed successfully.

See salaries and explore the career path for Project Manager

Business Analyst

Business analysts are responsible for analyzing business processes and identifying opportunities for improvement. They work with other departments to develop and implement solutions that improve efficiency and effectiveness. This course may be useful for business analysts because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help business analysts to identify opportunities for improvement more accurately and to develop more effective solutions.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians are responsible for collecting, analyzing, and interpreting data. They work with other departments to identify trends and patterns and to make recommendations for improvement. This course may be useful for statisticians because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help statisticians to identify trends and patterns more accurately and to make better recommendations for improvement.

See salaries and explore the career path for Statistician

Data Analyst

Data analysts are responsible for collecting, analyzing, and interpreting data. They work with other departments to identify trends and patterns and to make recommendations for improvement. This course may be useful for data analysts because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help data analysts to identify trends and patterns more accurately and to make better recommendations for improvement.

See salaries and explore the career path for Data Analyst

Operations Manager

Operations managers are responsible for overseeing the production process. They work with other departments to ensure that products are produced efficiently and meet quality standards. This course may be useful for operations managers because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help operations managers to improve productivity and reduce costs.

See salaries and explore the career path for Operations Manager

Process Engineer

Process engineers are responsible for designing and improving manufacturing processes. They work with other departments to ensure that products are produced efficiently and meet quality standards. This course may be useful for process engineers because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help process engineers to improve productivity and reduce costs.

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Quality Assurance Manager

Quality assurance managers are responsible for developing and implementing quality assurance programs. They work with other departments to ensure that products and services meet quality standards. This course may be useful for quality assurance managers because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help quality assurance managers to improve product quality and reduce costs.

See salaries and explore the career path for Quality Assurance Manager

Industrial Engineer

Industrial engineers are responsible for designing and improving work processes. They work with other departments to ensure that products and services are produced efficiently and meet quality standards. This course may be useful for industrial engineers because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help industrial engineers to improve productivity and reduce costs.

See salaries and explore the career path for Industrial Engineer

Manufacturing Engineer

Manufacturing engineers are responsible for designing and improving manufacturing processes. They work with other departments to ensure that products are produced efficiently and meet quality standards. This course may be useful for manufacturing engineers because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help manufacturing engineers to improve productivity and reduce costs.

See salaries and explore the career path for Manufacturing Engineer

Quality Control Inspector

Quality control inspectors are responsible for ensuring that products meet quality standards. They inspect products, identify defects, and take corrective action. This course may be useful for quality control inspectors because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help quality control inspectors to improve product quality and reduce costs.

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Quality Engineer

Quality engineers are responsible for developing and implementing quality assurance programs. They work with other departments to ensure that products and services meet quality standards. This course may be useful for quality engineers because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help quality engineers to improve product quality and reduce costs.

See salaries and explore the career path for Quality Engineer

Reliability Engineer

Reliability engineers are responsible for designing and improving the reliability of products and services. They work with other departments to ensure that products and services are reliable and meet customer expectations. This course may be useful for reliability engineers because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help reliability engineers to improve product reliability and reduce costs.

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Six Sigma Black Belt

Six Sigma Black Belts are responsible for leading and implementing Six Sigma projects. They work with other departments to identify and eliminate waste and improve quality. This course may be useful for Six Sigma Black Belts because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help Six Sigma Black Belts to identify and eliminate waste more effectively and to improve quality.

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Lean Six Sigma Master Black Belt

Lean Six Sigma Master Black Belts are responsible for leading and implementing Lean Six Sigma projects. They work with other departments to identify and eliminate waste and improve quality. This course may be useful for Lean Six Sigma Master Black Belts because it teaches them how to analyze data to identify sources of variation and how to create control charts to monitor processes. This knowledge can help Lean Six Sigma Master Black Belts to identify and eliminate waste more effectively and to improve quality.

See salaries and explore the career path for Lean Six Sigma Master Black Belt