Design of Experiment (DOE)

DOE has been used by statisticians in the industry for more than fifty years. It is only recently that managers, engineers and scientists begin to explore these methods and find out the effectiveness in problem solving, design and development. 

DOE will help to minimize the many variables that affect the yield of production in the industry. It permits many variables to be changed in a planned manner in order to come out with the most optimal values for such variable thereby saving time for production and cutting cost. It is no wonder that DOE is the most important tools used in Six Sigma Black Belt Program. 

This course will enable the participants to:
• provide means for tackling problems with long-term solutions
• improve quality of products through optimizing the variables
• reduce material waste due to frequent rejects on the product resulting from quality problems
• increase productivity by reducing quality problems
• reduce the cost of production due to the ability to detect quality problems faster

Venue:
401 Macpherson Road
#03-16/17 Macpherson Mall
Singapore 368125

AAIS Member: S$557.97/pax w/GST
Public: S$586.42/pax w/GST

(inclusive of S$17.44 registration fee, the amount is to be excluded from SkillsFuture (individuals) and SDF Funding (corporate))

Fees reflected are inclusive of 9% GST (in 2024).

This course is suitable for technical professionals as well as chemical professionals such as managers, engineers, engineering assistants and chemists involved in design, development, production, manufacturing, quality, and maintenance of the product.

Pre-Requisite:
Participants should have basic knowledge of statistics.

• Analysis and Control of Variables

  • Introduction

  • Dimension of Quality Improvement

  • Application of Statistics

  • Performance Optimization

  • Types of Experiments

  • Concluding Remarks

• Process Evaluation and Comparison

  • Statistical techniques and decision making in the face of variability

  • Evaluation and characterization of process variations

  • Comparative studies of process performance

• Multifactor Studies

  • Framework of P-optimization

  • Application of Design of Experiment

  • Factorial selection and coding

  • Factorial experiment: design and analysis

  • Two-level factorial designs

  • Interpretation of main and interaction effects

  • Significant tests for main and interaction effects

• Case Studies

AAIS reserves the right to adjust the course pricing and to re-schedule or cancel any course due to unforeseen circumstances, course commencement is subject to minimum class size requirements.