Design and Analysis of Experiments (DoE) (Accredited)

Design and Analysis of Experiments (DoE) (Accredited), available at $84.99, has an average rating of 4.7, with 48 lectures, 5 quizzes, based on 218 reviews, and has 1311 subscribers.

You will learn about Master the fundamentals of the Design of Experiments (DoE) using simple and understandable examples, ensuring a solid grasp of key concepts. Learn to design and analyze experiments systematically to study the relationship between various inputs (factors) and key outputs (responses). Perform screening using Plackett-Burman designs to identify significant factors with fewer experimental runs. Understand and implement modeling using full factorial, fractional factorial, and split plot designs to explore the effects of multiple factors. Optimize processes using Central Composite Design (CCD) for fine-tuning and achieving optimal performance. Gain a quick refresher on ANOVA and Regression Analysis to interpret the results of your experiments accurately and confidently. Develop a clear understanding of important DoE concepts such as blocking, analysis of covariance, replication, confounding, and design resolutions. Apply DoE techniques through practical examples, such as coffee tasting and catapult experiments, to reinforce learning and make complex concepts more relatable Increase your career prospects by mastering DoE, a critical component in quality improvement, process optimization, and research and development. Gain recognition from peers and management for your expertise in designing and analyzing experiments, making you a valuable asset in any organization. This course is ideal for individuals who are Quality Engineers or Quality Managers or All Engineers or Performance Improvement Professionals or Any one who wants to understand the behaviour of a complex process to achieve desired outcome It is particularly useful for Quality Engineers or Quality Managers or All Engineers or Performance Improvement Professionals or Any one who wants to understand the behaviour of a complex process to achieve desired outcome.

Enroll now: Design and Analysis of Experiments (DoE) (Accredited)

Summary

Title: Design and Analysis of Experiments (DoE) (Accredited)

Price: $84.99

Average Rating: 4.7

Number of Lectures: 48

Number of Quizzes: 5

Number of Published Lectures: 48

Number of Published Quizzes: 5

Number of Curriculum Items: 53

Number of Published Curriculum Objects: 53

Original Price: $74.99

Quality Status: approved

Status: Live

What You Will Learn

Master the fundamentals of the Design of Experiments (DoE) using simple and understandable examples, ensuring a solid grasp of key concepts.
Learn to design and analyze experiments systematically to study the relationship between various inputs (factors) and key outputs (responses).
Perform screening using Plackett-Burman designs to identify significant factors with fewer experimental runs.
Understand and implement modeling using full factorial, fractional factorial, and split plot designs to explore the effects of multiple factors.
Optimize processes using Central Composite Design (CCD) for fine-tuning and achieving optimal performance.
Gain a quick refresher on ANOVA and Regression Analysis to interpret the results of your experiments accurately and confidently.
Develop a clear understanding of important DoE concepts such as blocking, analysis of covariance, replication, confounding, and design resolutions.
Apply DoE techniques through practical examples, such as coffee tasting and catapult experiments, to reinforce learning and make complex concepts more relatable
Increase your career prospects by mastering DoE, a critical component in quality improvement, process optimization, and research and development.
Gain recognition from peers and management for your expertise in designing and analyzing experiments, making you a valuable asset in any organization.

Who Should Attend

Quality Engineers
Quality Managers
All Engineers
Performance Improvement Professionals
Any one who wants to understand the behaviour of a complex process to achieve desired outcome

Target Audiences

Quality Engineers
Quality Managers
All Engineers
Performance Improvement Professionals
Any one who wants to understand the behaviour of a complex process to achieve desired outcome

Note: Students who complete this course can apply for the certification exam by Quality Gurus Inc. and achieve the Verified Certification from Quality Gurus Inc. It is optional, and there is no separate fee for it. Quality Gurus Inc. is the Authorized Training Partner (ATP # 6034) of the Project Management Institute (PMI®) and the official Recertification Partner of the Society for Human Resource Management (SHRM®)

The verified certification from Quality Gurus Inc. provides you with 5.0 pre-approved PMI PDUs and 5.0 SHRM PDCs at no additional cost to you.

This course is accredited by The CPD Group (UK). You are eligible to claim 5.0 CPDs for this course (Accreditation# 1016190)

The design of experiments is a systematic approach of studying the relationship between various inputs (factors) on the key output (response).

This is the basics to the intermediate level course. In this course, we start with a basic understanding of the Design of Experiments (DoE) process by performing manual calculations on simpler processes.

Because this course will be taken by students from various sectors, we have kept the case studies simpler by using examples such as coffee tasting and catapult. These simple examples will help students focus on the concepts rather than the specific case studies.

This course assumes that you do not have any prior knowledge of the Design of Experiments, but you do have a basic understanding of statistics principles, such as ANOVA and Regression. However, we will review these two topics (ANOVA and Regression) to provide adequate knowledge to interpret the DoE results.

The course consists of video lectures, readings, and quizzes that help build upon each other so that by the end of the course, you have gained a firm grasp of the topics covered.

Topics Covered:

Section 1. Basics of Design of Experiments: We will start this course by understanding the definitions of common terms used in DoE. You will clearly understand factorial and partial factorial designs, as these will be explained using a coffee-tasting example. In addition, we will also use the catapult experiment to understand the variation in processes.

Other concepts that are covered in this section include: Blocking, Analysis of Covariance, Replication, Confounding and Design Resolutions.

This section will set a strong foundation for you to understand foundational concepts.

Section 2. ANOVA and Regression: Even though you are expected to have some basic understanding of these concepts, we will still cover these two topics to provide you with sufficient knowledge to interpret the results of an experiment.

Section 3. Screening, Modelling and Optimizing:This section will cover three main milestones in any designed experiment. For screening, we will use Plackett-Burman Design to reduce the number of factors studied. In modelling, we will use full factorial, fractional factorial and Split Plot Designs (for hard-to-change factors). In the last, we will optimize the process, and for that, we will use Central Composite Design (CCD).

Continuous Professional Development (CPD) Units:

For the ASQ® Recertification Units (RUs), we suggest 0.50 RUs under the Professional Development > Continuing Education category.
For PMI® 5.0,preapproved PDUs can be provided after completing our optional/free certification exam. The detailed steps for taking Quality Gurus Inc. certification with preapproved PDUs are provided in the courses.

Course Curriculum

Chapter 1: Foundation of Design of Experiments (Definitions and Basic Concepts)

Lecture 1: 1a Introduction to Design of Experiments

Lecture 2: Quality Gurus Inc Certificate, Digital Badge, PMI PDUs, SHRM PDCs (Optional)

Lecture 3: 1b Dependent and Independent Variables

Lecture 4: 1c Purpose of DoE

Lecture 5: 1d Stages of DoE

Lecture 6: 1e Factor, Level and Treatment

Lecture 7: 1f Two Factors Two Levels Experiment

Lecture 8: 1g Plots for Two Factors Two Levels Experiment

Lecture 9: 1h Regression Equation for Two Factors Two Levels Experiment

Lecture 10: 1i Minitab Demonstration: Two Factors Two Levels Experiment

Lecture 11: 1j Two Factors Two Levels with Interaction

Lecture 12: 1k Regression Equation for for 2×2 Experiment with Interaction

Lecture 13: 1l Minitab Demo 2×2 Experiment with Interactions

Lecture 14: 1m Catapult Experiment with 2 Factors

Lecture 15: 1n Noise Factors Three Types

Lecture 16: 1o Blocking

Lecture 17: 1p Analysis of Covariance

Lecture 18: 1q Replication and Repetition

Lecture 19: 1r Catapult Experiment with 2 Replications

Lecture 20: 1s Minitab Demo – Catapult Experiment with 2 Replications

Lecture 21: 1t Adding the Third Factor

Lecture 22: 1u Three Factors Regression Equation

Lecture 23: 1v Results of Three Factors Experiment

Lecture 24: 1w Minitab Demo – Three Factors Experiment

Lecture 25: 1x Three Factors Experiment with Center Point

Lecture 26: 1y Minitab Demo Experiment with Center Point

Lecture 27: 1z Partial Factorial Design Introduction

Lecture 28: 1z1 Confounding in Partial Factorial Design

Lecture 29: 1z2 Design Resolution

Chapter 2: Understanding ANOVA and Regression (A Quick Overview)

Lecture 1: 2a ANOVA

Lecture 2: 2b Regression Getting Started

Lecture 3: 2c Assumptions in Regression

Lecture 4: 2d Comparing Models

Lecture 5: 2e R Square Predicted

Lecture 6: 2f Model Simplification

Chapter 3: Screening, Modelling and Optimizing Designs

Lecture 1: 3a Screening Designs

Lecture 2: 3b Plackett Burman Design Demonstration

Lecture 3: 4a Types of Factorial Designs

Lecture 4: 4b Split Plot Design

Lecture 5: 4c Minitab Demo – Split Plot Design

Lecture 6: 4d Catapult Full Factorial Design

Lecture 7: 4e Minitab Demo – Catapult Full Factorial Design – Part 1

Lecture 8: 4f Minitab Demo – Catapult Full Factorial Design – Part 2

Lecture 9: 5a Response Surface Designs

Lecture 10: 5b Central Composite Design

Lecture 11: 5c Minitab Demo – Central Composite Design

Chapter 4: Resources

Lecture 1: Course Slides

Chapter 5: BONUS

Lecture 1: BONUS LECTURE

Instructors

Sandeep Kumar, Quality Gurus Inc.
Experienced Quality Director • Six Sigma Coach • Consultant

Rating Distribution

1 stars: 1 votes
2 stars: 3 votes
3 stars: 14 votes
4 stars: 75 votes
5 stars: 125 votes

Frequently Asked Questions

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You can view and review the lecture materials indefinitely, like an on-demand channel.

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