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This lecture provides a gentle introduction to the Design of Experiments (DOE) by the instructor, focusing on the efficiency and interactions in R&D. Starting with the historical background of DOE and its inventor, Sir Ronald Fisher, the lecture explains how DOE tackles the challenges of multifactorial environments. Through examples, the lecture illustrates how DOE enhances efficiency in experimental work, particularly in determining interactions between factors. It covers the use of Hyper-Graeco-Latin squares for DOE approach and the importance of Pareto analysis in identifying key interactions. The lecture also delves into the iterative strategy of optimizing processes using DOE, emphasizing the significance of screening designs and determining main effects and interactions. It concludes by highlighting the iterative nature of DOE in improving strategies and optimizing outcomes.