Design and Analysis of Experiments (DoE)

Focused View

Sandeep Kumar, Quality Gurus Inc.

4:40:21

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1 - Foundation of Design of Experiments Definitions and Basic Concepts

1 - 1a Introduction to Design of Experiments.mp4

07:58

2 - 1b Dependent and Independent Variables.mp4

03:35

3 - 1c Purpose of DoE.mp4

04:51

4 - 1d Stages of DoE.mp4

06:44

5 - 1e Factor Level and Treatment.mp4

11:04

6 - 1f Two Factors Two Levels Experiment.mp4

05:44

7 - 1g Plots for Two Factors Two Levels Experiment.mp4

07:28

8 - 1h Regression Equation for Two Factors Two Levels Experiment.mp4

05:03

9 - 1i Minitab Demonstration Two Factors Two Levels Experiment.mp4

08:20

10 - 1j Two Factors Two Levels with Interaction.mp4

07:20

11 - 1k Regression Equation for for 2x2 Experiment with Interaction.mp4

07:32

12 - 1l Minitab Demo 2x2 Experiment with Interactions.mp4

05:20

13 - 1m Catapult Experiment with 2 Factors.mp4

13:50

14 - 1n Noise Factors Three Types.mp4

05:53

15 - 1o Blocking.mp4

05:16

16 - 1p Analysis of Covariance.mp4

01:58

17 - 1q Replication and Repetition.mp4

04:21

18 - 1r Catapult Experiment with 2 Replications.mp4

08:28

19 - 1s Minitab Demo Catapult Experiment with 2 Replications.mp4

05:30

20 - 1t Adding the Third Factor.mp4

07:32

21 - 1u Three Factors Regression Equation.mp4

04:58

22 - 1v Results of Three Factors Experiment.mp4

05:28

23 - 1w Minitab Demo Three Factors Experiment.mp4

05:39

24 - 1x Three Factors Experiment with Center Point.mp4

06:09

25 - 1y Minitab Demo Experiment with Center Point.mp4

10:12

26 - 1z Partial Factorial Design Introduction.mp4

05:47

27 - 1z1 Confounding in Partial Factorial Design.mp4

08:45

28 - 1z2 Design Resolution.mp4

08:55

2 - Understanding ANOVA and Regression A Quick Overview

29 - 2a ANOVA.mp4

11:33

30 - 2b Regression Getting Started.mp4

05:42

31 - 2c Assumptions in Regression.mp4

05:25

32 - 2d Comparing Models.mp4

06:44

33 - 2e R Square Predicted.mp4

03:26

34 - 2f Model Simplification.mp4

06:11

3 - Screening Modelling and Optimizing Designs

35 - 3a Screening Designs.mp4

07:48

36 - 3b Plackett Burman Design Demonstration.mp4

04:40

37 - 4a Types of Factorial Designs.mp4

05:22

38 - 4b Split Plot Design.mp4

04:26

39 - 4c Minitab Demo Split Plot Design.mp4

09:56

40 - 4d Catapult Full Factorial Design.mp4

04:02

41 - 4e Minitab Demo Catapult Full Factorial Design Part 1.mp4

05:07

42 - 4f Minitab Demo Catapult Full Factorial Design Part 2.mp4

10:19

Description

Design of Experiments using Minitab: Basics, Plackett-Burman, Full/Fractional Factorial, Response Surface (CCD) Designs

What You'll Learn?

Fundamentals of the Design of Experiments (DoE) using simple to understand examples.
Screening (Plackett-Burman), Modelling (Full, Fractional Factorial and Split Plot Designs) and Optimizing (Central Composite Design) Designs
A quick refresher on ANOVA and Regression Analysis is also included to help you understand the results of analysis clearly.
Clear understanding of Blocking, Analysis of Covariance, Replication, Confounding and Design Resolutions.

Who is this for?

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

More details

Description
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 student focus on the concepts rather than focusing on 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 by using an example of coffee tasting. 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. ANOVAÂ and Regression: Even though it is expected that you 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: In this section, we will cover three main milestones in any designed experiment. For screening, we will use Plackett-Burman Design to reduce the number of factors to be 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).

Who this course is for:
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

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Education

Sandeep Kumar, Quality Gurus Inc.

Instructor's Courses

ASQ ConnEx Expert, PMI-PMP, IRCA Registered Lead Auditor, ASQ - CSSBB, CQA, CQE, CMQ/OE, IIA - CIA, NAHQ - CPHQ Sandeep Kumar has more than 35 years of Quality Management experience. He has worked as Quality Director on several projects, including Power, Oil and Gas and Infrastructure projects.In addition, he provides coaching and consulting services to implement Lean Six Sigma to improve performance. After the successful completion of ASQ vetting, Sandeep Kumar has been designated as a genuine and authorized ASQConnEx expert. ASQConnEx is an education delivery system and network that vets, designates, and connects quality subject matter experts with organizations to advance their excellence journey.His areas of specialization include Quality Assurance, ISO 9001:2015, Lean, Six Sigma, Risk Management, QMS Audits, Supplier Quality Surveillance, Supplier Pre-qualification, Construction Quality, Mechanical Inspection and Quality Training.Professional Qualifications:His professional qualifications/certifications include: • Authorized ASQ ConnEx Expert• ASQ-CSSBB, Certified Six Sigma Black Belt• ASQ-CMQ/OE Certified Manager of Quality/Organizational Excellence• PMI-PMP Certified Project Management Professional • IRCA Registered Lead Auditor (QMS-2015)• IIA-CIA Certified Internal Auditor• NAHQ-CPHQ Certified Professional in Healthcare Quality• ASQ-CSSGB, Certified Six Sigma Green Belt• ASQ-CQA Certified Quality Auditor• ASQ-CQE Certified Quality Engineer• ASQ-CSQP Certified Supplier Quality Professional

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