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Kuliah kimia Miss Qolbu Nurul Hidayah

  1. Nov 3

    DoE Episode 2: From Experimental Design to Process Optimisation: Response Surface Methodology

    Episode 2 Description From Experimental Design to Process Optimisation: Response Surface Methodology In this episode, we move from identifying important factors to understanding how those factors work together and how to find the best operating conditions. We begin by introducing Response Surface Methodology, or RSM, and explain why continuous factors often require more than a simple straight-line model. You will learn how quadratic terms describe curvature, how response surfaces and contour plots help us visualise process behaviour, and how designs such as Central Composite Designs, Box–Behnken designs, Definitive Screening Designs, and I-optimal designs support optimisation. The episode also explores how to optimise several responses at the same time using desirability functions. We discuss the difference between finding a mathematical optimum and finding a practical, robust operating region that can tolerate normal process variation. Finally, we look at sequential experimentation—starting with screening, moving towards improvement, and then building a detailed response surface model around the promising region. By the end of this episode, you should understand how design of experiments develops from: Finding important factors → modelling the response → predicting behaviour → optimising the process. This episode is useful for anyone working in process development, chemistry, engineering, manufacturing, formulation, or quality improvement.

    DoE Episode 2: From Experimental Design to Process Optimisation: Response Surface Methodology

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Kuliah kimia Miss Qolbu Nurul Hidayah