Design of Experiments (DOE) with JMP for Manufacturing Engineers

Why should you attend?

This course provides a comprehensive exploration of the design of experiments (DOE) tailored for manufacturing engineers, utilizing the powerful JMP software platform. Participants will begin by understanding the fundamental principles and terminology of DOE, emphasizing its advantages over traditional one-factor-at-a-time experimentation. Through hands-on sessions, learners will navigate the JMP interface and explore sample datasets to solidify their understanding. Building on this foundation, the course delves into essential statistical concepts necessary for effective experimental design. Students will learn to interpret variability in manufacturing processes and apply hypothesis testing and confidence intervals using JMP. The course further explores factorial designs, both full and fractional, teaching participants how to create, analyze, and interpret these experiments within a manufacturing context. The curriculum also covers advanced topics such as response surface methodology (RSM) and mixture designs for formulation optimization. Learners will engage in practical exercises to design RSM experiments and optimize multiple responses simultaneously. Robust design methods are introduced to enhance process robustness through Taguchi methods and signal-to-noise ratios. Finally, participants will apply their knowledge in a capstone project that simulates real-world manufacturing challenges. This project emphasizes team-based experimental design and execution, culminating in results presentation and implementation planning. By the end of the course, students will be equipped with the skills to effectively implement DOE strategies in manufacturing settings.