Design of Experiment (DOE) Response Surface Methods (RSM) for Wafer Etching with R in 10 Minutes

Design of Experiment (DOE) Response Surface Methods (RSM) and Central Composite Designs to Optimize Wafer MOSFET Polysilicon Gate Etching Production with R in 10 Minutes. we will introduce a statistical experiment method to find the best equipment settings, the method of Response Surface. Engineers will need to ensure the profile of the polycrystalline silicon gates isotopic, that is, the walls of the etch lines should be vertically perpendicular to the substrate in all directions. Design of Experiments or DOE is a systematic way to discover how physical factors impact outputs. In practice, it saves a lot of research time because experiments are easier with existing lab research equipment than starting theoretical research. Almost any researcher can set up experiments, but not becoming an expert on something they only need once. The key here is how to do the experiment, the correct way. There are two steps in any experiment design study. First, design an experiment; Second, analyze the experiment data. Response surface methodology or RSM is a type of DOE. It uses a sequence of designed experiments to discover the best variable settings that lead to an optimal response or region. RSM usually starts with first-order factorial or fractional factorial experiments to identify among candidate variables the ones affect the response variable(s) of interest. Then proceed to more complicated experiment design, such as the central composite design or CCD, where we fit a second-degree polynomial model. We see here the fitted-surface in the case of two factors, there are either “Peak”, “Hillside”, “Rising Ridge” or “Saddle Point”. Historically RSM has led to huge scientific and technological breakthroughs, therefore is considered as the core industrial competency. [optimize medium compositions and bioprocess control parameters in biofuel production, the effect of precursor dosage, precursor type, and temperature on diesel production] The central composite design, along with Box-Behnken design, is the most widely used design for RSM. CCD contains an embedded factorial or fractional factorial design with center points. Then they are augmented with a group of `star points' to allow estimation of curvature. Let’s take a look at this two-factors CCD design. Engineers began with a full- or fractional-factorial experiment and identified two important factors, then augment the experiments by performing on the star points along the axials. The star points represent new extreme for each factor. The combined settings become a CCD plan. The three important CCD properties are: ORTHOGONALITY: That is the individual effects of all the factors can be estimated independently without (or with minimal) confounding, with minimum variance, and the estimates are uncorrelated. ROTATABILITY: That is the design points are rotating about the center of the factor space. UNIFORMITY: That is, the center points are uniform in precision