Learn modern experimental strategy, including factorial and fractional factorial experimental designs, designs for screening many factors, designs for optimization experiments, and designs for complex experiments such as those with hard-to-change factors and unusual responses. There is thorough coverage of modern data analysis techniques for experimental design, including software. Applications include electronics and semiconductors, automotive and aerospace, chemical and process industries, pharmaceutical and bio-pharm, medical devices, and many others. You can see an overview of the specialization from Dr. Montgomery here.
What you'll learn
Understand factorial and fractional factorial experimental designs
Learn to design experiments for screening and optimization
Apply experimental design techniques in various industries
Use software tools for data analysis in experimental design
Course objectives
To equip students with the skills to design effective experiments
To help students analyze and interpret experimental data
To prepare students for real-world applications in various sectors