Course Information

  • Sessions 2 days
  • Duration 16 hrs
  • Level Beginner
  • Assessment 2 hrs

Venue

12 Woodlands Square #07-85/86/87 Woods Square Tower 1, Singapore 737715. 5 mins walk from Woodlands (NS9) MRT station.

The venue is disabled-friendly.

Skills Framework

TSC Title
Process Integration
TSC Code
ELE-SIS-5002-1.1

Funding Validity

Funding for this course is valid from 20 Nov 2024 to 19 Nov 2026. Register and complete the course within this period to qualify for funding support.

Learning Outcomes

By end of the course, learners should be able to:

  • LO1: Analyze process interactions to characterize key factors influencing performance in Design of Experiments (DoE).
  • LO2: Select suitable factorial DoE projects by evaluating relevant performance metrics.
  • LO3: Define the scope and execute fractional factorial DoE projects using problem-solving techniques.
  • LO4: Evaluate the effectiveness of DoE projects and recommend follow-up actions

Course Brochure

Certification

  • Certificate of Achievement from Tertiary Infotech Academy Pte Ltd - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Achievement from Tertiary Infotech Academy Pte Ltd.
  • OpenCerts from SkillsFuture Singapore - After passing the assessment(s) and achieving at least 75% attendance, participants will receive a OpenCert (aka Statement of Achievement) from SkillsFuture Singapore, certifying that they have achieved the Competency Standard(s) in the above Skills Framework.

WSQ - Practical Design of Experiment (DoE) for Engineers and Researchers

Course Code: TGS-2024051249
  • WSQ
  • SFC
  • PSEA
  • UTAP
  • SFEC
  • Absentee Payroll
  • MCES
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What's This Course About

This WSQ course, Practical Design of Experiment (DoE) for Engineers and Researchers, equips participants with essential skills to design, analyze, and optimize experiments for improved process performance. Participants will gain a thorough understanding of DoE fundamentals, factorial experiments, and how to apply ANOVA to assess the significance of variables. By learning how to identify key factors affecting performance, participants will be able to confidently select appropriate DoE projects and execute them with precision.

The course covers advanced topics like fractional factorial designs, screening methods, and modeling techniques such as Taguchi and Response Surface Methodology (RSM). By the end of the course, learners will be able to evaluate the effectiveness of their DoE projects and make data-driven recommendations for continuous process improvement.

WSQ Funding

Full Fee $900.00 Before GST
GST $81.00 9% of fee
Baseline Nett $531.00 SG/PR age 21+ · 50% funded
MCES / SME Nett $351.00 SG age 40+ · 70% funded
SkillsFuture Enterprise Credit (SFEC)

Eligible companies can use their $10,000 SFEC to cover up to 90% of out-of-pocket course fees for classes ending on or before 30 Nov 2026. A redesigned SFEC starts on 1 Dec 2026.

View on SkillsFuture for Business

SkillsFuture Credit (SFC)

Eligible Singapore Citizens can use their SFC to offset course fee payable after funding but the $4,000 Additional SFC (Mid-Career Support) cannot be used.

Direct Application on SkillsFuture Portal

UTAP

Eligible NTUC members can apply for 50% of the unfunded fee from UTAP, capped up to $250/year and for members aged 40 and above, capped up to $500/year.

Submit UTAP Claim

PSEA

Eligible Singapore Citizens can use their PSEA funds to offset course fee payable after funding.

Check PSEA Eligibility

  • Scroll down to “Keyword Tags” to verify for PSEA eligibility.
  • If there is “PSEA” under keyword tags, the course is eligible for PSEA.

Once you are eligible for PSEA, please download and fill up the PSEA Withdrawal Form, then submit the completed form to us:

PSEA Withdrawal FormSubmit PSEA Form

Course FeeBefore Funding

$900.00 (GST-exclusive)
$981.00 (GST-inclusive)

Course Date

* Required Fields

Additional Note

Please bring your own laptop for hands-on training. If you don't have laptop, we can provide spare laptop for training use.

Post-Course Support

  • We provide free consultation related to the subject matter after the course.
  • Please email your queries to enquiry@tertiaryinfotech.com and we will forward your queries to the subject matter experts.

Cancellation & Reschedule Policy

  • You can register your interest without upfront payment. There is no penalty for withdrawal of the course before the class commences.
  • We reserve the right to cancel or re-schedule the course due to unforeseen circumstances. If the course is cancelled, we will refund 100% for any paid amount.
  • Note the venue of the training is subject to changes due to availability of the classroom.

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.

  1. Register for this course as self-sponsored and tell us you will use SkillsFuture Credit. Do not pay the amount you plan to claim.
  2. We email you an invoice showing the course fee after funding.
  3. 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.
  4. Click Submit a Claim and search for this course by its course code, TGS-2024051249.
  5. 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).
  6. 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.
  1. Check your company's SFEC eligibility and balance on EnterpriseSG.
  2. 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.
  3. Your employee attends and completes the course. We submit the attendance and assessment results to SWDA.
  4. 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.

  1. Make sure your NTUC membership is paid up before the course starts.
  2. Register for this course with us and pay the course fee after funding and SkillsFuture Credit.
  3. Attend at least 75% of the course and sit all assessments.
  4. 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.
  5. 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).
  6. 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.

  1. Check that this course shows the PSEA tag on its MySkillsFuture page.
  2. Check your PSEA balance on MOE's Student Finance System with Singpass.
  3. Download and complete the PSEA withdrawal form, then submit it to us.
  4. 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.
  5. 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.

  1. 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.
  2. Discuss the decision with the assessor or the assessment manager first.
  3. 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.
  4. Lodge your appeal within 7 days, giving your reasons, using the Candidate Appeal Form. The assessor can help you write and lodge it.
  5. 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.
  6. 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.

Dwight Nuwan Fonseka is Head of Data Science at Plano Pte. Ltd. and an ACLP-certified trainer with deep expertise in data analytics, machine learning, and AI applications. He has extensive hands-on experience developing predictive models, RShiny dashboards, and deep learning solutions using R, Python, TensorFlow, and Keras. With a strong professional background in healthcare, finance, and customer analytics, Dwight brings an applied perspective to teaching AI, focusing on both the opportunities and risks of emerging technologies.

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
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
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)
Average Rating: 5.0 Review by Course Participant/Trainee
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
N/A (Posted on 5/22/2026)
Average Rating: 3.7 Review by Course Participant/Trainee
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
Classrooms is hot in the afternoon and was not clean, very dusty (Posted on 5/21/2026)
Average Rating: 3.7/5 Review by Course Participant/Trainee
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
N/A (Posted on 3/12/2026)

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