In statistics, response surface methodology (RSM) explores the relationships between several explanatory variables and one or more response variables. RSM is an empirical model which employs the use of mathematical and statistical techniques to relate input variables, otherwise known as factors, to the response.

Response Surface Methodology, RSM (also known as Response Surface Modeling) is a technique to optimize the response (s) when two or more quantitative factors are involved. The dependent variables are known as responses, and the independent variables or factors are primarily known as the predictor variables in response surface methodology.

如果自变量个数较少（2~3个），则 响应曲面设计 （RSM，Response Surface Methodoligy）是最好的方法之一。 我们通常的做法是：先用二水平的 因子实验 的数据，拟合一个 线性回归方程，如果发现有弯曲的趋势，则希望拟合一个含二次项的回归方程，使模型更加准确。

A RSM is DOE with specially designed arrays for calculating interactions and quadratic responses. This document is an introduction of the RSM functionality of Develve for more information how to conduct a RSM see Setting up a Response surface test (RSM). Select DOE in the statistical mode drop-down menu to start a Design of experiment.

2024年4月12日 · Response surface methodology (RSM) is a helpful statistical approach for maximizing processes and products. It examines the connections between multiple influencing factors and related outcomes. RSM brings together math and statistics to come up with an empirical model showing what’s happening.

In Factorial/RSM the factor levels are set completely independent of each other. Examples of the factors could be temperature, speed, type of material. In formulation and mixture DOE’s instead of factors we have ingredients. The equivalent of the levels in Factorial DOE will be the proportions of the ingredients in Mixture DOE.

Box-Behnken Design, BBD for the response surface methodology, RSM, is specially designed to fit a second-order model, which is the primary interest in most RSM studies. To fit a second-order regression model (quadratic model), the BBD only needs three levels for each factor (Figure 15), rather than five levels in CCD (Figure 14).

Analyze and Explain Response Surface Methodology. Let’s analyze the data for the human comfort study provided in Video 3. Video 6 provides detailed analysis of RSM using Minitab, and its explanations. Human Comfort vs the Temperature and Humidity Study Data. * Note. The data set used in the video is different from this data set. Video 6.

A RSM is advanced DOE with specially designed arrays for calculating interactions and quadratic responses. When comparing a standard DOE with a RSM the DOE gives a 2D image of the output of 1 factor, a RSM produces a 3D image of the output of 2 factors in one image.

Response surface methodology (RSM) uses statistics and mathematics to model the behavior of the response variable (related to the properties of the studied product) in the function of two or more extraction variables.