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HYBRID TRAINING !!! FINANCE FOR NON FINANCE PROFESSIONALS (18 & 19 FEB 2025)
GEOMETRIC DIMENSIONING AND TOLERANCING (GD&T) 17 & 18 Feb 2025
ATTENTION !!! DESIGN OF EXPERIMENT (DOE) (12 & 13 March 2025)
GRAB 3 FREE 1 !!!
Please call 012-588 2728
email to pearl-otc@outlook.com
FACE-TO-FACE PUBLIC PROGRAM
DESIGN OF EXPERIMENT (DOE)
Venue : Dorsett Grand Subang Hotel, Selangor (SBL Khas / HRD Corp Claimable Course)
Date : 12 March 2025 (Wed) | 9am – 5pm By Venu
13 March 2025 (Thu) | 9am – 5pm . .
INTRODUCTION
Design of experiments, also called experimental design, is a structured and organized way of conducting and analyzing controlled tests to evaluate the factors that are affecting a response variable. Experimental design and optimization are tools that are used to systematically examine different types of problems that arise within, e.g., research, development and production. It is obvious that if experiments are performed randomly the result obtained will also be random. Therefore, it is a necessity to plan the experiments in such a way that the interesting information will be obtained.
In an experiment, we deliberately change one or more process variables (or factors) in order to observe the effect the changes have on one or more response variables. The (statistical) design of experiments (DOE) is an efficient procedure for planning experiments so that the data obtained can be analyzed to yield valid and objective conclusions.
LEARNING OBJECTIVES
This program is designed to enable participants to learn the fundamental theory about Design of Experiment, and to use it in a practical situation such as Research and Development, Process Optimization and other possible applications.
Here are the learning objectives for the two days training program; after completing this program, participants will be able to:
- Understand the methodology of design of experiments
- Plan a design of experiment
- Explain the importance of each concept used in design of experiments
- Recognize variables in an experiment and how they interact
- Understand how to create and use an analysis of variance (ANOVA) table
- Understand how to conduct and analyze the results of a contrast test
- Identify the advantages, disadvantages, assumptions and hypotheses related to various types of designs, including completely randomized design, completely randomized block design, Latin Square design, and factorial designs
- Analyze the results of designed experiments
TARGET GROUP
Process Engineers, R & D Engineers/Scientist, and other technical based individual, working with process Improvement.
LANGUAGE
- English
- Bahasa Malaysia
DURATION
Time: 9.00 a.m. - 5.00 a.m.
Days: 2 days
OUTLINE OF WORKSHOP
DAY 1
1. Introduction - Introduction to DOE
2. Full Factorial Design - One Factor at A Time - Coding Factors - Factorial Design - Calculating Main and Interaction Effects - Creating Full Factorial Design - Analyzing DOE results - Plotting Main and Interaction Effects Plot - Replication, Centre Point and Blocking - Model Reduction. - Limitation of Full Factorial Design
Activity - DOE catapult/Helicopter simulation Workshop |
DAY 2
1. Introduction - Why Fractional Factorial Design?
2. Fractional Factorial Design - Screening Design - Fractional Factorial Design - Alias Relationship and Confounding Factors - Design Resolution - Fold Over Design - Sample size determination for 2 level factorial Design
3. DOE for Variance Reduction and Response Optimizer - DOE for variance reduction - Creating and Analyzing DOE for Variance Reduction. - Response Optimizer Introduction - Response Optimizer Strategy - Multiple Response Optimizer
Activity - DOE catapult/Helicopter simulation Workshop
|
** Certificate of attendance will be awarded for those who completed the course
ABOUT THE FACILITATOR
VENU
Mr Venu, been advocate and consultant in Quality and Analytics subjects for about 12 years . Started is career after completed his higher education in University Malaya majoring in Material Engineering in Motorola in 2006. Trained by Motorola Inc in Six Sigma methodology. He been well versed Quality methods and process Improvement methods. As a Motorola’s Six Sigma practicing engineer , he was not only well versed in the theoretical concept but hands on approach in solving complex problems, driving process improvement activities, and leading quality drives across organization.
In later part of is career he was involved in Big data Analytics, and spend considerable time, on implementing Analytics Concepts, such Artificial Intelligence on Manufacturing process, automated decision making and predictive concept manufacturing. He is one of the chosen team to drive Industry 4.0 in Western Digital when the concept was introduced in 2012.
His tenure in Western Digital marked the time where manufacturing process being automated by data driven decision making and relaying less on human dependent manual labor. His participation in Industrial 4.0 core team was instrumental to drive this change across organization. His team was actively involved creating and implementing artificial modeling to reduce effort spend to find root cause. This much relieved the engineers to focus more actual improvement and other task instead of fire fighting to find root causes.
In his 12 years in major MNC’s, where he is exposed to many real-life case studies in many engineering and high technology manufacturing. A part of his career, he have been involved actively in training organization in six sigma, process improvement, analytics and other related subject for the last 7 years.
His well versed in his subject matters and very passionate about sharing is knowledge with everyone. As a trainer he truly understand the need for knowledge of both quality and analytics and how to make both work supplementing each other in order to bring organization to the new industrial age.
1. Subject Matter Expertise
2. Career Experience
Process Improvement Consultant/Manager
Jcy International Bhd
(2015- 2016)
Function Includes
- Driving Continuous Improvement for overall organization, playing vital roles identifying possible improvement area. Drive beneficial projects with key stakeholders.
- Mentor and consult green/black belt project with focusing quality, delivery and Cost.
- Train organization on process improvement and analytical method to enhance data-based decision skills.
- Consult and advice overall quality improvement to drive excellent manufacturing culture.
Senior Staff Engineer
Western Digital Corp
HDD Analytics
(2012 -2015)
Dual function role with HDD Analytics group as Operational Analytics Expert and Master Black Belt Consultant.
________________________________________________________________________________________________________________________________________________________
Senior Process Development Engineer
Infineon Technologies
Power Product Division
(2011- 2012)
Process development Engineer for Infineon Power Package Division. Focusing Process and product Development for front end process. Lead package Development for PO programs form R & D stage to HVM (High Volume Manufacturing).
_______________________________________________________________________________________________________________________________________________________
Process and Equipment Engineer
Freescale Semiconductor (formerly Motorola Inc.)
Flip Chip Process and Product Engineering
(2006 – 2011)
Responsible for Motorola’s Flip Chip front end assembly process. Function include continuous process improvement using six sigma methodology, handling customer concern regarding Flip Chip assembly process, ensure material/process/equipment as per accordance to ensure flawless manufacturing process.
(SBL Khas / HRD Corp Claimable Course)
TRAINING FEE | |
2 days Face-to-Face Public Program |
RM 2,250.00/pax (excluded 8% SST) |
Group
Registration: Register
3 participants from the same organization, the 4th participant is FREE.
|
We hope you find it informative and interesting and we look forward to seeing you soon.
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or email to pearl-otc@outlook.com
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Pearl
by "sump@otcmarketing.com.my" <sump@otcmarketing.com.my> - 03:51 - 21 Jan 2025