Design of Experiment (DOE) for Process Optimization

LEVEL: INTERMEDIATE                    HRDF: CLAIMABLE 

Eight (8) CPD Hours approved by MBOT

TRAINERS: 

Associate Professor Dr Hanita Daud, Dr Rajalingam & ASSOCIATE PROFESSOR Dr Mahmod Othman

 

7 - 8 NOVEMBER 2023

 

MS TEAMS

 

9.00AM - 5.00PM

 

RM 1,300 FOR PROFESSIONALS

10% Discount for Early Bird (until 7 October 2023) / Group / Students

CONTENT SUMMARY

INTRODUCTION

Design of Experiment (DOE) is one of the most powerful improvement tools. It is a strategic, enabling methodology to improve process yields and product quality. At the same time, it reduces the product development time and overall costs by changing one or more process characteristics after studying their effects on the product. In recent years, DOE has been used as a key driver for many quality improvement initiatives.

This practical course addresses the essentials of DOE to ensure a successful implementation of this improvement tool. In addition, the application of Design Expert software in DOE implementation could further enhance the analysis process

COURSE CONTENT

Introduction

  • 1.1Introduction to DOE
  • 1.2 Objective of DOE
  • 1.3 Uses of DOE
  • 1.4 Rationale for Adopting DOE
  • 1.5 Reference and Software
  • 1.6 Industry Application – Actual

Statistical Analysis

  • 2.1 Mean
  • 2.2 Median
  • 2.3 Population and Sample
  • 2.4 Variance
  • 2.5 Normal Distribution
  • 2.6 Hypothesis Testing
  • 2.7 Z-Test2.8 T-Distribution
  • 2.9 Confidence Interval
  • 2.10 The F Distribution

Analysis of Variance (ANOVA) 

  • 3.1 The idea of ANOVA
  • 3.2 How to run an ANOVA
  • 3.3 One-Way ANOVA3.4 Two-Way ANOVA

Introduction to Factorial Designs

  • 4.1 Design of Factorial Experiments
  • 4.2 General 2K Factorial Designs
  • 4.3 Blocking and Confounding in the 2K Factorial Designs
  • 4.4 Fractional Factorial Designs

Correlation and Linear Regression Model

  • 5.1 Introduction to Correlation
  • 5.2 Spearman Rank Correlation Coefficient
  • 5.3 Product Moment Correlation
  • 5.4 Linear Regression
  • 5.5 Simple Linear Regression Model
  • 5.6 Estimating Parameters by Least Squares Method
  • 5.7 Assessing or Evaluate the Model
  • 5.8 Multiple Linear Regression Model



OBJECTIVES

Upon completion of this course, participants will be able to:

  • Understand the concept and principals of DOE. 
  • Apply DOE techniques to solve optimization problems. 
  • Design a full factorial DOE test matrix, in both randomized and blocked forms. 
  • Analyze and interpret full factorial DOE results using ANOVA, regression, and graphical methods
  •  Apply Response Surface Method for optimization. 
  •  Analyze and interpret the result of Response Surface Method 
  • Utilize the Expert Design software tool to analyze data


WHO SHOULD ATTEND?

  • Junior/senior data analyst
  • Marketing personnel
  • Engineers 
  • Junior/senior Lecturers
  • Executives
  • Middle managements
  • Professionals who are interested in analyzing data for business or other purposes





OUR TRAINERS

1. Associate Professor Dr. Hanita Daud (UTP)

AP Dr. Hanita Daud, is currently an Associate Professor in the Department of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS. She obtained her Ph.D. degree in 2013, from Universiti Teknologi PETRONAS in mathematical modelling. Her M.Sc. degree in 2001, from Universiti Kebangsaan Malaysia is in Artificial Intelligence. Her research interest includes mathematical/statistical modelling, non-parametric applications, and remote monitoring system. She has been actively participating in National and International exhibitions and has won numerous awards in these fields. Currently she is collaborating with industries in developing methodology to solve various applications and problems.

2. Dr. S. Rajalingam (UTP)

Dr. S. Rajalingam, is a Senior Lecturer in the Department of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS. Previously he was in the Department of Electrical and Electronic Engineering at Curtin Malaysia, conducting teaching and research in Mathematics and Statistics. He received the M.Sc. in Industrial Technology and Ph.D. degrees in Mathematics from UKM and UMS, respectively. He has a total of 25 years of working experience with 12 years in the manufacturing industries and another 13 years in education. He possesses good experience in computer laboratory sessions and some related mathematics and statistical software, such as Maple, SPSS and Expert Design.

3. Associate Professor Dr. Mahmod Othman (UTP)

AP Dr. Mahmod Othman, is currently an Associate Professor in the Department of Fundamental and Applied Sciences at Universiti Teknologi PETRONAS. He has more than 30 years working experience. He earned his doctorate in Fuzzy Evaluation from Universiti Utara Malaysia, in 2005. His research concentrated Fuzzy Time series Forecasting, Flood management and prediction and Fuzzy grading system for Harumanis mango. He has published over 50 articles in international journals and conference proceedings and has delivered over 30 lectures in the international conferences as well as five books and 3 book chapters.

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REGISTRATION FEES

PROFESSIONALS

MYR1,300*

*fee quoted does not include SST, HRDS service fee, GST/VAT or withholding tax (if applicable).

EARLY BIRD/ GROUP/ STUDENT

MYR1,170*

*fee quoted does not include SST, HRDS service fee, GST/VAT or withholding tax (if applicable).

OUR LOCATION

Centre for Advanced & Professional Education (CAPE)

 Level 16, Menara 2, Menara Kembar Bank Rakyat, 50470, Jalan Travers, Kuala Lumpur.

CALL US

+605 - 368 7558 /

+605 - 368 8485

DROP US AN EMAIL

cape@utp.edu.my