This course provides participants with skills to plan, conduct, and analyse DoE experiments for process and product quality improvement, highlighting its value in understanding complex variables, optimising processes, reducing variability, and making data-driven decisions.
Learning Outcome
- Describe the terminology, key basics, strategy and methodology of Design of Experiment (DoE)
- Describe and outline the methodology and steps to conduct 2 levels full and fractional factorial Design
- Create design matrix for experiments
- Conduct and interpret analysis results (graphical and numerical) produced by Minitab Statistical Software
- Draw conclusions for screening and optimisation
Methodology
The methods used here are the combination of lecture + interactive discussion + group exercise.
Pre-requisite
A basic technical background or 2-5 years of working experience in any business operation discipline.
Duration
2 Days
Target Group (who should attend)
Executives, Engineers and Managers from any organisations including Core Operation/Support/Transactional group either in manufacturing or service industries.
Day 1
- Introduction
- Terminology and key basics
- Coding for factor levels
- Design matrix
- Repeats & replicates
- Main effect and interaction analysis
- Randomisation & blocking
- Design generator
- Confounding
- Resolution
Day 2
- 2 levels full and fractional factorial design steps (practical examples)
- Problem & Objective
- Output, factor and levels Selection
- Design matrix Creation
- Data analysis
- Draw conclusion for screening and or optimisation
- Confirmation run
