Design of experiments (DOE) is a systematic, efficient method that enables scientists and engineers to study the relationship between multiple input variables (aka factors) and key output variables (aka responses). It is a structured approach for collecting data and making discoveries.

LEARNING OUTCOME

1. Understand the concept of DOE

2. Able to compute uncertainty using t-test, z-test & ANOVA

3. Able to perform factorial experiment

4. Understand the fractional factorial

WHO SHOULD ATTEND THIS COURSE

1. Engineers and scientists who want to optimise and improve the performance of their processes, products, or systems.

2. Quality control and quality assurance professionals who want to understand the impact of different factors on the quality of their products and services.

3. Six Sigma professionals who want to use DOE as a tool for reducing process variability and improving process capability.

4. Product and process design engineers who want to optimise their designs and reduce the risk of failures.

5. Researchers and statisticians who want to learn the principles and techniques of DOE and apply them in their research studies.

METHODOLOGY

This is an immersive, hands-on course where trainees will be learning and immediately applying what they learn through practical-based projects. In this training, the instructor will explain DOE fundamentals and show practical examples. 

COURSE OUTLINE

(THIS IS A 2 DAY TRAINING PROGRAMME)

1. Introduction to DOE concept

What is DOE

When to use DOE

Why use DOE

Trial and error method

One factor at a time (OFAT) method

What is Hypotheses

5 main steps Hypotheses

What are Null and Alternative Hypotheses

Descriptive vs Inference Statistic

Confidence intervals

Hypothesis testing

2. T-test & Z-test

T-Test

One-sample, two-sample, or paired t test?

T test function in statistical software

Z Test

When you can run a Z Test

3. ANOVA

What is ANOVA?

What Does “One-Way” or “Two-Way Mean?

What are “Groups” or “Levels”?

What Does “Replication” Mean?

Examples using Excel

4. Factorial Experiment

Basic Definitions and Principles

Examples

5. Data Storage and Persistence

Working with Shared Preferences

Understanding SQLite database

Implementing CRUD operations in SQLite

Working with Room Persistence Library

6.  Fractional Factorial Experiment

Introduction

The One-Half Fraction of the 2k Design