Course Details
Course Details
What You'll Learn
Topic 1 Fundamentals of Design of Experiment
Introduction to Design of Experiment (DoE)
Dependent and Independent variables
Purpose of DoE
Stages of DoE
Factor, Level and Treatment
Introduction to single factor experiments
One-Way Analysis of Variance (ANOVA)
Decomposition of the Sum of Squares
Topic 2 Factorial DoE
Introduction to Factorial DoE
Main Effects and Interactions between factors
Why using Factorial DoE
Two-Factors Two-Levels (2^2) DoE
Regression equation for 2^2 DoE
2^2 experiment with Interactions
Regression model for 2^2 DoE with Interactions
Analysis of Variance (ANOVA) of 2^2 DoE
Adding the third factor – 2^3 DoE
ANOVA of 2^3 DoE
Regression model for 2^3 DoE
General 2^k DoE
Analysis procedure of any 2^k DoE
Blocking a replicated design
Analysis a 2^k DoE with blocks as replicates
Confounding a 2^k DoE in blocks
Topic 3 Fractional Factorial DoE
Introduction to Fractional Factorial DoE
One-Half fraction designs
Confounding in partial factorial design
Design resolution
ANOVA of fractional DoE
One-Quarter fraction designs
Topic 4 Screening, Modeling and Optimizing DoE
Screening designs
Plackett Burman design
Taguchi design
Response Surface Method (RSM)
Central Composite Design (CCD)
Assessment
- Written Exam
- Practical Exam
Course Info
Minimum Entry Requirement
Knowledge and Skills
- Able to operate using computer functions
- Minimum 3 GCE ‘O’ Levels Passes including English or WPL Level 5 (Average of Reading, Listening, Speaking & Writing Scores)
Attitude
- Positive Learning Attitude
- Enthusiastic Learner
Experience
- Minimum of 1 year of working experience.
Target Age Group: 18-65 years old
Minimum Software/Hardware Requirement
Software:
You will need the following for this course:
Hardware: Windows PC or Mac laptop
Funding Eligibility Criteria
Self-sponsored learners (individuals)
- Singapore Citizens and Singapore Permanent Residents aged 21 and above.
- Up to 50% course fee funding. Singapore Citizens aged 40 and above receive up to 70% under the Mid-career Enhanced Subsidy (MCES).
- Singapore Citizens aged 25 and above can pay the remaining fee with SkillsFuture Credit.
Company-sponsored learners
- Singapore Citizens and Singapore Permanent Residents who are direct employees of the sponsoring company.
- Up to 50% course fee funding, or up to 70% for employees of SMEs (Enhanced Training Support for SMEs) and for Singapore Citizens aged 40 and above. An SME has no more than 200 employees or an annual turnover of no more than $100 million.
- Employers can also claim Absentee Payroll funding for employees who attend during working hours.
- Eligible companies can offset their out-of-pocket fees with SkillsFuture Enterprise Credit (SFEC).
Conditions for all funded learners
- Attendance is taken digitally with Singpass for every session, including the assessment.
- You must complete the course and pass all assessments (assessed as Competent).
- If these conditions are not met, the funding is clawed back and the learner or employer pays the full course fee.
- 9% GST is charged on the full course fee before funding.
- Promo and discount codes cannot be used on funded courses.
- Any balance after funding can be paid in cash, with SkillsFuture Credit, with PSEA (Singapore Citizens with a PSEA), or partly reimbursed by UTAP for NTUC members.
How to Apply SkillsFuture Credit Claim for Individuals
Singapore Citizens aged 25 and above can use their SkillsFuture Credit (base tier) to pay the course fee after funding. The $4,000 mid-career top-up cannot be used for this course.
- Register for this course as self-sponsored and tell us you will use SkillsFuture Credit. Do not pay the amount you plan to claim.
- We email you an invoice showing the course fee after funding.
- From 60 days before the course starts, and no later than the course start date, log in to MySkillsFuture with Singpass and click Claim credits.
- Click Submit a Claim and search for this course by its course code, TGS-2024051249.
- Select your class start date, enter the course fee payable after funding and the amount of credit to claim, then upload the invoice (PDF, JPG or PNG, under 4MB).
- Review, accept the terms and click Agree and Submit. The credit is paid directly to us; processing can take up to 14 working days.
Changing or withdrawing: cancel the claim on MySkillsFuture at least one day before the course starts. If your class date changes, cancel the claim and submit a new one with the new date.
How to Apply SkillsFuture Enterprise Credit (SFEC)
SFEC helps companies pay for employee training. The current SFEC ends on 30 November 2026, and a redesigned SFEC starts on 1 December 2026.
Current SFEC: classes ending on or before 30 November 2026
- Eligible companies received a one-off $10,000 credit, notified by letter to their Corppass administrator. Eligibility generally required at least 3 Singapore Citizen or PR employees and Skills Development Levy contributions.
- SFEC covers up to 90% of the company's out-of-pocket course fee after other subsidies.
- Check your company's SFEC eligibility and balance on EnterpriseSG.
- Register your Singapore Citizen or PR employee for a class that ends by 30 November 2026, as company-sponsored, and pay the course fee after funding.
- Your employee attends and completes the course. We submit the attendance and assessment results to SWDA.
- No separate claim is needed. SFEC is calculated automatically once the course fee grant is approved and is paid quarterly to your company's IRAS GIRO or PayNow Corporate account.
Any unused balance of the current SFEC expires on 30 November 2026.
Redesigned SFEC from 1 December 2026
Companies with at least 3 resident employees receive a fresh $10,000 in an online SFEC wallet that offsets out-of-pocket fees upfront at enrolment, instead of reimbursing them afterwards. SWDA has not yet published the support rates and claim steps; see OurWorkforce or our SFEC guide.
How to Apply UTAP (NTUC Members)
NTUC members can claim 50% of the unfunded course fee under the Union Training Assistance Programme (UTAP), capped at $250 a year (aged below 40) or $500 a year (aged 40 and above). The cap is shared with UTAP claims for AI tool subscriptions.
Eligibility: you must be an NTUC member paying full membership fees, with your membership paid up before and during the course and when you claim. The course must not be fully paid for by your employer or another source.
- Make sure your NTUC membership is paid up before the course starts.
- Register for this course with us and pay the course fee after funding and SkillsFuture Credit.
- Attend at least 75% of the course and sit all assessments.
- Within 6 months after the course ends, go to the NTUC U Portal, open UTAP under E-services, log in with Singpass and choose Course Fee Claim.
- Enter the nett course fee you paid (after all subsidies and SkillsFuture Credit, including GST), and upload your invoice or receipt and your certificate or result slip (PDF, JPG or PNG, up to 5MB each).
- NTUC usually pays the claim within 4 weeks of submission.
Read more in our UTAP guide.
How to Apply PSEA
Singapore Citizens with a Post-Secondary Education Account (PSEA), which stays open until around the year you turn 31, can use it to pay the course fee after funding for PSEA-approved courses. You can also use a sibling's PSEA after your own has been used up.
- Check that this course shows the PSEA tag on its MySkillsFuture page.
- Check your PSEA balance on MOE's Student Finance System with Singpass.
- Download and complete the PSEA withdrawal form, then submit it to us.
- We submit the withdrawal request to MOE. You (and your sibling, if you are using their account) authorise it in the Student Finance System. Nothing is withdrawn without this authorisation.
- MOE pays us directly. If you have already paid, we refund the amount covered by PSEA.
More details: MOE PSEA overview.
Appeal Process
If you disagree with an assessment decision, you have the right to appeal.
- When the assessor gives you feedback, say whether you agree with the outcome. If you agree, you and the assessor sign the Assessment Summary Record; if you disagree, do not sign it.
- Discuss the decision with the assessor or the assessment manager first.
- If you are still not satisfied, tell the assessor you intend to appeal. The assessor records this in the feedback section of the Assessment Summary Record and informs the assessment manager.
- Lodge your appeal within 7 days, giving your reasons, using the Candidate Appeal Form. The assessor can help you write and lodge it.
- An Assessment Appeal Panel reviews the information from you and the assessor and makes a decision. A record of the appeal and its outcome is kept.
- You will be told the outcome within 2 weeks of lodging the appeal. The panel's decision is final.
Job Roles
Job Roles
- Process Engineer
- Quality Assurance Engineer
- Product Development Engineer
- Manufacturing Engineer
- Research Scientist
- Data Analyst
- Operations Manager
- Continuous Improvement Manager
- Industrial Engineer
- Test Engineer
- R&D Manager
- Laboratory Technician
- Engineering Consultant
- Process Improvement Specialist
- Lean Six Sigma Specialist
- Project Manager
- Production Manager
- Quality Control Specialist
- Statistical Analyst
- Technical Consultant
Trainers
Trainers
Dr. Alvin Ang is a data analytics and digital transformation expert with more than 20 years of experience in applied research, engineering innovation, and data-driven decision-making. He holds a PhD in Information Systems and has worked with numerous public and private sector organizations to implement analytical frameworks that enhance operational efficiency and quality management. His expertise spans statistical modeling, process optimization, and experimental design, making him a sought-after consultant and trainer in the fields of engineering analytics and applied research.
In this course, Dr. Ang focuses on translating complex experimental design methodologies into practical applications for engineers and researchers. His sessions emphasize structured problem-solving, data validation, and statistical inference using real-world case studies. Learners benefit from his deep expertise in process optimization and his ability to connect data science with experimental design for improved innovation and research outcomes.
Teddy Yip Fook Khin is a senior technology consultant and educator with extensive experience in IT systems, AI integration, and data analytics. Over the past 20 years, he has led projects in data modeling, statistical analysis, and process improvement for industries including manufacturing, engineering, and business services. As a certified ACLP trainer, Teddy combines technical depth with instructional clarity, guiding learners to master analytical techniques for problem-solving and continuous improvement.
In this course, Teddy introduces participants to the principles of Design of Experiments and their role in enhancing product quality and process control. His sessions focus on applying statistical design methods to real-world engineering challenges using tools such as Minitab and Python. Learners gain practical insights into experimental setup, analysis, and interpretation, equipping them to drive data-based optimization in research and engineering environments.
Liew Sing Loon is an experienced educator and professional engineer with a strong background in applied research, process design, and learning development. He holds the
from the Institute for Adult Learning (IAL) and has over 15 years of experience in technical training, curriculum design, and engineering innovation. His expertise spans across process optimization, problem-solving methodologies, and technology-enabled learning, making him a valuable resource for engineers and researchers seeking structured analytical skills.
In this course, Liew focuses on helping participants understand the practical application of Design of Experiments for improving system performance and reliability. His sessions integrate real-world engineering examples with structured experimental design concepts to ensure learners can apply techniques effectively in research and production settings. Learners gain hands-on experience in planning, executing, and analyzing experiments that enhance innovation and data-driven decision-making.
Review
Customer Reviews (4)
- A resourceful trainer who makes DoE easy to understand Review by Course Participant/Trainee
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I have attended the course "Practical Design of Experiment (DoE) for Engineers and Researchers" taught by Dr. Alvin Ang at the Tertiary Infotech Academy. Dr. Ang uses a wide variety of examples to illustrate Taguchi designs, mixture designs, full and fractional factorial designs, Plackett-Burman designs, Box-Behnken designs, Response Surface Methodology, and other experimental optimization techniques. He demonstrated how Minitab can be used to generate these experimental designs, analyze the data, and generate various plots to visualize the results. Dr. Ang is a very resourceful trainer and has included many personal experiences to make the course engaging. He explains all concepts clearly and in a manner that is easy to understand. He has also demonstrated how generative artificial intelligence tools can assist in DoE. Dr. Ang is very experienced in his field of work; he has worked on Procter and Gamble's Supply Chain Redesign and has helped the Research Director of The Logistics Institute Asia Pacific to prepare a proposal for Singapore General Hospital's home delivery of medication. Furthermore, Dr. Ang has five publications on the topic of Kanban Systems and Operations Research. Overall, Dr. Ang is a strong communicator and I enjoyed being taught by him. (Posted on 10/26/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Average Rating: 5.0 Review by Course Participant/Trainee
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N/A (Posted on 5/22/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Average Rating: 3.7 Review by Course Participant/Trainee
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Classrooms is hot in the afternoon and was not clean, very dusty (Posted on 5/21/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment - Average Rating: 3.7/5 Review by Course Participant/Trainee
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N/A (Posted on 3/12/2026)1. Do you find the course meet your expectation? 2. Do you find the trainer knowledgeable in this subject? 3. How do you find the training environment
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