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Training on
Uncover Design of Experiments (DoE)
Understanding variation to experimental design process

Klang Valley
09 & 10 AUG, 2017
" understand applicability and concept of DOE in details
followed by analysis and interpretation of results
in a simple and understandable manner ..."

Scientists and Engineers no longer can afford to experiments in a trial-and-error manner, changing one factor at a time, the way Edison have done in developing the light bulb. A far more effective method is to apply a computer-enhanced, systematic approach to experimentation, one that considers all factor simultaneously. This approach is known as Design of Experiments (DoE), and corporations across the globe are adopting it as a cost effective way to solve serious problems afflicting to their operations.

DoE provides information about the interaction of factors and the way the total system works, something not obtainable through testing one factor at a time while holding other factor constant. Another advantage of DoE is that it shows how interconnected factors respond over a wide range of values, without requiring the testing of all possible values directly.


Course Benefits

This 2 day course intends to meet the needs of professionals, engineers and researcher, begins with the fundamentals of Design of Experiments (DoE) methods and continues with concepts, principles and requirements. Topics include full factorial designs, fractional factorial designs, screening designs, the response surface methodology and reliability DOE., with intensive, hands-on training using latest software tools.

Carefully selected course exercises and application examples provide participants with Theory-to-Skills Building knowledge transfer, enabling them to achieve proficiency in applications development.

Highly interactive workshop with practical examples and exercises to understand applicability and concept of DOE in details followed by analysis and interpretation of results in a simple and understandable manner. Statistical software Design Expert will be used during the workshop

Course Outline

  • Basic Statistical Concepts
    • Concept of variation
    • Normal distribution & probability using standard normal curve
    • Hypothesis testing concepts
    • Basic statistical test
      (z-test, t-test, 2-t-test & ANOVA)

  • Design of Experiments
    • The Experimental Design Process
    • Screening and Optimization designs.
    • Terminologies of DoE
    • Basic Principles of DoE
    • Selection of appropriate designs

  • Factorial Designs
    • Full Factorial designs at two level (2K)
    • Fractional Factorial Design (2K-P)
    • Phenomenon of Confounding
    • Understanding of Centre-Point, Blocking & Randomization
    • Analyzing of DoE Results
      (Significant Factors, Main Effect, Interacton Effects, Residuals)
    • Prediction Equation and Optimizing Response

  • Plackett Burman Screening Design
  • Response Surface Designs
    • Central Composite Designs
    • Box Behnken Designs

  • Hands-on Exercises
  • Summary and Conclusion

Who Should Attend
The courses have been designed for individuals: Involved in R&D, product development, process optimization, quality control & monitoring. Professional scientists, researchers, improvement engineers and managers involved in quality engineering, S.Q.C / SPC, production, Laboratory and quality assurance and regulatory affairs.

Math skills, knowledge of basic statistics. No prior knowledge of Design-Expert is required to attend this program.

Note: Due to the nature of the course and the learning expectations, the availability seats are limited. You need to register early to obtain confirmation of your space.

09 & 10 AUG, 2017 @ MY

Venue : Klang Valley
10 % Early Registration Discount before 09 JUL 2017
10 % Group Discount for 3 or more from same organization

Sign Up Now

Other upcoming courses to enrich and enhance your technical computing capability and data anaysls skill-set, Just click onto the Title to find out more details.

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