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Choose and implement an experimental design – #136
Context
You want to :
- Optimise the performance of your processes by using experimental designs to identify the most influential variables and combinations of variables to control, and define the best setting for these variables.
Objectives
- Know how to pre-identify the variables to be studied through hypothesis testing.
- Understand the basic statistics concepts associated with experimental design.
- Know how to conduct and analyse the results of factorial designs.
- Know how to identify a curve in the response and model the response surface.
- Know how to identify the most robust settings.
- Understand the conditions for successful implementation of experimental designs.
- Plan an experimental design in your own company.
Recommanded for
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Industrialization managers
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Process managers
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Quality/QHSE managers, engineers and technicians.
Prerequisites
No prerequisites.
Pedagogy
- The teaching method used is fun and is based on a case study to put the trainees in a situation.
- Use of the MINITAB software (a demonstration version can be obtained on the MINITAB website).
Evaluation mode
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Validation by the trainer of the ability to apply the concepts and tools taught through situational exercises.
Course materials
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Participant’s file containing the presentations delivered during the training and the exercise materials.
To go further
Consulting services: EURO-SYMBIOSE can assist you in the concrete implementation in your company. Contact us to know more about it.
Key definitions and principles.
Screening designs (Plackett Burman design and Taguchi design).
Pre-select the factors to be studied in a factorial design.
Experimental designs for filtering.
Full factorial experimental designs.
Model the response surface.
Optimize the response.
Review and assessment of the method.
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