Design of Experiments for Optimisation

🚀 Design of Experiments for Optimisation with Rosane Rech 🧐

Course Headline:

DoE using R: Response Surface Methodology, Lack-of-Fit, Central Composite Designs, Box-Behnken Design

Course Description:

Welcome to the intriguing world of "Design of Experiments for Optimisation"! 🎓

Experimentation is not just a series of systematic procedures; it's an art that, when executed with precision and understanding, can lead to breakthroughs in various fields. The success of your experiments hinges on the design—how you collect data significantly influences the insights you can derive from it. This course delves into the sophisticated realm of experimental design to help you optimise responses in complex systems.

Who is this course for?

• Researchers and academics in science, engineering, and beyond
• Master and PhD students looking to enhance their analytical skills
• Industry professionals aiming to improve processes and product formulations

Key Learning Points:

📈 Understanding Linear Regression Models: We'll kick off by building regression models that fit your experimental data and evaluating their adequacy. You'll learn how to handle inaccurate levels and missing observations within your data.

• Master linear regression for fitting experimental data
• Check model adequacy with central points
• Manage inaccurate levels and missing observations

Diving into Response Surface Methodology (RSM):

• Transition from a simple factorial design to fit a linear model
• Find the path of the steepest ascent for optimal conditions
• Utilise a central composite design to fit a quadratic model, maximising your response variables
• Analyse multiple responses at once with real-world examples

Exploring Advanced Experimental Designs:

• Learn how to use Box-Behnken and face-centred composite designs for optimisation
• Analyse data using R-Studio, even if you're not a seasoned R user
• Download R codes and data files to facilitate your learning journey
• Adapt and apply the provided codes to your own experimental data for analysis

Real-World Application:

The course is rich with real examples from both industry and academia, showcasing the practical application of the concepts discussed. This ensures that you can see the theories in action and understand their implications in a tangible context.

Why Choose This Course?

• Expert Guidance: Rosane Rech, an experienced instructor, will lead you through each concept.
• Comprehensive Coverage: From basic to advanced topics in Design of Experiments (DoE).
• Practical Skills: Learn how to perform analysis using R-Studio, a valuable skill for any researcher or engineer.
• Flexible Learning: Whether you're a seasoned R user or new to DoE software, this course is designed to accommodate your level of expertise.

Join Us on This Journey:

Embark on a journey to master the design of experiments with "Design of Experiments for Optimisation." Enhance your analytical capabilities, optimise your processes, and unlock the full potential of your experimental data. 🔍

Don't miss out on this opportunity to elevate your experimental design skills using R! Sign up now and transform the way you conduct and analyse experiments. 🚀⚫️📊