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所在平台: Udemy |
课程主页: https://www.udemy.com/course/design-of-experiments-for-mixtures/
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课程名称：混合物实验设计 课程概述：欢迎参加“混合物实验设计”课程！无论您是科学家、工程师、研究人员，还是对混合物的创建、完善或创新产品感兴趣的人，这门课程将帮助您理解混合设计的基本原理。混合物在我们的日常生活中无处不在，从食谱到制药和化学配方，以及材料开发。然而，优化这些混合物通常是一项挑战，因为它们涉及多个组分，这些组分之间相互作用，决定最终产品的性质。传统的实验方法可能无法清晰理解这些相互作用，因此特为混合物设计的“实验设计”（DOE）概念应运而生。 本课程将深入探讨混合设计的基本原则。我们将首先识别何时使用混合设计而不是传统实验设计的方法，并学习如何阅读和解释三角坐标图。接下来，我们将学习在三角平面上分布设计点的最佳方法，即使用单纯形设计。之后，我们将深入研究来自食品和制药领域的多个实际案例研究，涵盖混合设计和分析的不同方面。最后，我们将讨论具有约束条件的混合变量案例研究，这些变量无法在整个混合空间内变化。 请注意，这不是初学者课程，报名“混合物实验设计”之前，需掌握一定的DOE知识。数据分析将使用R-Studio进行，尽管这不是一门R语言课程，但建议学生具备R的一定基础。课程中使用的R代码和数据文件可以下载，功能会进行简要解释，代码也可轻松调整以分析学生自己的数据。 任何进行混合实验的人都可以从本课程中受益，尤其是学术界和工业界的研究人员、硕士和博士研究生以及工程师。通过理论与实际案例的结合，您将获得设计和分析混合实验所需的技能和知识。
Welcome to "Design of Experiments for Mixtures"!Whether you're a scientist, an engineer, a researcher, or just someone interested in creating, perfecting, or innovating products with mixtures, this course will help you understand the principles of mixture designs.Mixtures are everywhere in our daily lives, from food recipes to pharmaceutical and chemical formulations, and material development. However, optimizing these mixtures is often a challenging task, as they involve multiple components, that interact among themselves to give the final properties of the product. Traditional experimental approaches may not be suitable for a clear understanding of these interactions, which is where the concept of "Design of Experiments" (DOE) specifically tailored to mixtures comes into play. This course will delve into the fundamental principles of mixture designs.We will start our journey by identifying when to use mixture designs instead of a traditional design of experiments approach and learning how to read and interpret plots in triangular coordinates. In the next step, we will learn the best approaches to distributing design points throughout a triangular surface using Simplex Designs. By then, we will be ready to dive into several real Case Studies from the food and pharmaceutical areas, covering different aspects of mixture designs and analysis. Finally, we will see Case Studies where the mixture variables have constraints and cannot vary over the whole mixture space.This is not a beginner course; it's essential to have some previous knowledge of DOE before enrolling on "Design of Experiments for Mixtures".The analysis of the data will be performed using R-Studio. This is not an R course; this way, it is desirable that students have some familiarity with R. The R codes and the data files used in the course can be downloaded, the functions will be briefly explained, and the codes can be easily adapted to analyse the student's data.Any person who performs mixture experiments can benefit from this course, mainly researchers from the academy and the industry, Master and PhD students and engineers.Through a combination of theory and practical examples, you'll gain the skills and knowledge needed to design and analyse experiments with mixtures effectively.
