Leading With Designed Experiments: Anova And Taguchi Methods

How to Analyze Data and Design Statistical Experiments for Improved Analytical Decision Making

What you'll learn

A detailed overview of Design of Experiments (DOE) in the manufacturing context

How DOE can improve your decision making skills

What is Design of Experiments? Are where are they commonly used?

Critical terms and definitions

The Two Types of Experimental Error

What is ANOVA? How is it used in decision making?

Real-life examples of 1-way and 2-way ANOVA in Microsoft Excel

An Overview of Full Factorial Experiments

Fractional Factorial Experiments and the Taguchi Methods

Examples of Taguchi Methods used to solve complex manufacturing problems

Downloadable Excel templates

Requirements

Basic understanding of descriptive statistics

Basic understanding of manufacturing

Description

As the complexity of your manufacturing processes increase with the addition of input variables like speeds, feeds, temperature, and machine types, you ability to "trail and error" your way into an optimal process decreases. So often, manufacturing professionals fail to recognize that well-designed process experiments can lead to fewer defects, higher production rates, and improved mechanical properties.In this course, "Leading with Designed Experiments: ANOVA and Taguchi Methods", you will learn how to design, conduct, and analyze the results of process experiments in a manner that leads to those optimal results you desire.More specifically, you will learn:A detailed overview of Design of Experiments (DOE) in the manufacturing contextHow DOE can improve your decision making skillsWhat is Design of Experiments? Are where are they commonly used?Critical terms and definitionsThe Two Types of Experimental ErrorWhat is ANOVA? How is it used in decision making?Real-life examples of 1-way and 2-way ANOVA in Microsoft ExcelAn Overview of Full Factorial ExperimentsFractional Factorial Experiments and the Taguchi MethodsExamples of Taguchi Methods used to solve complex manufacturing problemsAnd MUCH MORE!!In addition to the 3+ hours of instructional video, when you sign up for this course, you also get:3 tests (with Answer Keys) to verify your learning progressA Microsoft Excel workbook containing the 5 worksheets with 1-way and 2-way ANOVA's used in the course17 Real-life case studies used in the course instructionALL SLIDES FOR THE CLASS in a pdf formatLifetime access to all course materials … the videos, exams, slides and Excel worksheets.Q&A access to the instructors via UdemyWith the case study approach used in this class, you will now only learn the key concepts, terminology, and methods used in ANOVA, DOE and Taguchi methods, but you will get to see how real-life manufacturing problems are framed for analysis.So if you are a quality, industrial, or manufacturing engineer or manager, and want to advance your analytical problem solving skills, then this is the class for you!!! SIGN UP TODAY!!

Overview

Section 1: Introduction

Lecture 1 Introduction to the Course

Lecture 2 Overview of Decision Making with Experiments

Lecture 3 Course Slides

Lecture 4 The Challenge

Lecture 5 The Benefits of Statistical Decision Making

Lecture 6 Case #1, Tube Cutting, Pt 1

Lecture 7 Case #1, Tube Cutting, Pt 2

Lecture 8 Terms and Definitions

Lecture 9 What is Design of Experiments?

Lecture 10 The Two Error Types

Lecture 11 Test #1

Lecture 12 What's Next?

Lecture 13 Understanding ANOVA

Lecture 14 Microsoft Excel, Data Analysis Add On

Lecture 15 Downloadable Excel Spreadsheets

Lecture 16 Case #2, One Way ANOVA

Lecture 17 Case #3, Two Way ANOVA

Lecture 18 Case #4, Assembly Line Workers

Lecture 19 Case #5, High School Test Scores

Lecture 20 Case #6, Battery Life

Lecture 21 Test #2

Lecture 22 Full and Fractional Factorial Methods

Lecture 23 Introducing Full Factorial Methods

Lecture 24 Case #7, Full Factorial

Lecture 25 Taguchi Methods, An Alternative to Full Factorial

Lecture 26 Taguchi Terminology and Concepts

Lecture 27 The Eight Steps of a Taguchi Experiment

Lecture 28 Supplementary Table and Main Effects

Lecture 29 Thoughts on Software

Lecture 30 Case #8, L4 Experiment, Electrical Current

Lecture 31 Case #9, L4 Fuel Pump

Lecture 32 Case #10, L4 Injection Molding

Lecture 33 Case #11, L8 Bond Strength

Lecture 34 Case #12, L8 Heat Treating

Lecture 35 Case #13, L8 Bearing Wear

Lecture 36 Case #1 Revisited, L8

Lecture 37 Case #14, L8 Tile Defects

Lecture 38 Case #15, L8 Baking Example

Lecture 39 Case #17, L16 Welding Strength

Lecture 40 Test #3

Lecture 41 References and Closing Comments

Lecture 42 Conclusion to the Course

Lecture 43 Bonus Lecture

Industrial engineers, Manufacturing engineers,Quality managers, Quality engineers, Quality technicians,Manufacturing managers, Continuous improvement professionals