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#### Duration :

2 days ( 9am – 5pm )

English

#### Who should attend:

• Those who want to know a strategy for improving their business quality.

• The importance of achieving world-class quality standards are increasingly becoming a primary concern as a business strategy.
• Statistical Design of Experiment (DOE) is a proven technique that continues to show increasing use in these industries. As the R&D function comes under increasing pressure to produce fast and more accurate results, industrial researches and engineers are turning to use this DOE tool to further improve quality and increase productivity.
• Through experimentation, changes are intentionally introduced into this process or system in order to observe their effect on the performance characteristics or response of the system or process. A statistical approach is the most efficient method for optimizing these changes.
• Using ad hoc or heuristic approach can and may be used; however the investigation becomes more efficient if it is with the same correct statistical tools.
• A clear definition of DOE is provided and its three primary objections are stated and carried through.

Participants will be able to understand the :

• Benefits of DOE
• Stages of investigation to undertake DOE practices.
• Principle of DOE and where should it be used.
• Terminology used in DOE practices

Participants will be able to determine :

• The variable (s) and their magnitude that influences the response.
• The levels of these variables.
• How to manipulate these variables to control the re-sponse.
• Lecture with key points, coaching, interactive discussion

•  Group dynamic and exercise to ensure participants grasp the topics presented.

• QC Role Play and Group Presentations

• QC Tools exercise and Industrial samples are used to stimulate actual nature of failure that has taken place.

DAY 1

Introduction of the DOE Practices.

• DOE definition and understanding
• Understanding the benefits of DOE
• Understand the stages of investigation to undertake DOE practices

Overview of the DOE Practices.

• Understand the principles of DOE and its uses
• Understand the terminology used in DOE practices
• Basic statistic and example

Hypotheses Testing and the Decision Making Process

Probability of Error for Hypothesis Testing

• Level of confidence and consequences of a wrong decision
• Test and t Distribution definition
• One-Sample Test

Testing of Hypotheses using ANOVA

• F Test
• F Distribution