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

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

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

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
Download Course Brochure

Certification

  • Certificate of Completion from Tertiary Courses - Upon meeting at least 75% attendance and passing the assessment(s), participants will receive a Certificate of Completion from Tertiary Courses.
  • 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
  • SkillsFuture Credit
  • PSEA
  • UTAP
  • SFEC
  • Absentee Payroll
  • MCES

3 Review(s) | Add Your Review

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 Singapore-registered companies can tap on $10000 SFEC to cover out-of-pocket expenses.Click here to submit SkillsFuture Enterprise Credit

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. Click here for SkillsFuture Credit submission

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. Click here to submit UTAP

Once you are eligible for PSEA, please download and fill up the PSEA Withdrawal Form and email to us. 

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

Promotion Code

Your will get 10% discount voucher for 2nd course onwards if you write us a Google review.

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:

Hardware: Window or Mac Laptops

Appeal Process

  1. The candidate has the right to disagree with the assessment decision made by the assessor.
  2. When giving feedback to the candidate, the assessor must check with the candidate if he agrees with the assessment outcome.
  3. If the candidate agrees with the assessment outcome, the assessor & the candidate must sign the Assessment Summary Record.
  4. If the candidate disagrees with the assessment outcome, he/she should not sign in the Assessment Summary Record.
  5. If the candidate intends to appeal the decision, he/she should first discuss the matter with the assessor/assessment manager.
  6. If the candidate is still not satisfied with the decision, the candidate must notify the assessor of the decision to appeal. The assessor will reflect the candidate’s intention in the Feedback Section of the Assessment Summary Record.
  7. The assessor will notify the assessor manager about the candidate’s intention to lodge an appeal.
  8. The candidate must lodge the appeal within 7 days, giving reasons for appeal 
  9. The assessor can help the candidate with writing and lodging the appeal.
  10. he assessment manager will collect information from the candidate & assessor and give a final decision.
  11. A record of the appeal and any subsequent actions and findings will be made.
  12. An Assessment Appeal Panel will be formed to review and give a decision.
  13. The outcome of the appeal will be made known to the candidate within 2 weeks from the date the appeal was lodged.
  14. The decision of the Assessment Appeal Panel is final and no further appeal will be entertained.
  15. Please click the link below to fill up the Candidates Appeal Form.

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

Angel Koh

Angel Koh has over 15 years experience with the maritime and defence industry building information systems for full scale development programs; working with a myriad of programming and computing languages and tools, ranging from programming languages like C# and Java to computing languages like Octave and ArcGis. His specialization is in the field of data fusion and mapping. He is always passionate to adopt new technologies and skills to add to his repertoire of computer knowledge.

In his free time, he likes to tinker with his RigidBot 3D printer, building simple household objects with Adobe 123D Design and OpenSCAD.

 

Review

Customer Reviews (3)

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)

Write Your Own Review

You're reviewing: WSQ - Practical Design of Experiment (DoE) for Engineers and Researchers

How do you rate this product? *

  1 star 2 stars 3 stars 4 stars 5 stars
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