825 Words4 Pages

EXPERIMENTAL PROCEDURE The experiments were performed according to the Box-Behnken design which is a kind of response surface methodology. It is well known that response surface methodology or RSM is a collection of mathematical and statistical techniques useful for the modeling and analysis of problems in which a response of interest is influenced by several variables and the objective is to optimize this response. First, the material is cleaned to remove the oil, grease, dust, rust or any substance from the surface of material that would provide good adhesion of the photo resist. PCM process beings from engineering drawing or sketch that defines the precise characteristics of the part. The utilize CAD system and laser plot*…show more content…*

Response surface methodology method was used to determine optimal machining parameters for maximum material removal rate, etch factor and minimum surface roughness, undercut with less etching time. Response surface methodology (RSM) is a collection of mathematical and statistical techniques for empirical model building. By careful design of experiments, the objective is to optimize a response (output variable) which is influenced by several independent variables (input variables). Response Surface Methodology*…show more content…*

Originally, RSM was developed to model experimental responses (Box and Draper, 1987), and then migrated into the modeling of numerical experiments. The difference is in the type of error generated by the response. In physical experiments, inaccuracy can be due, for example to measurement errors while in computer experiments numerical noise is a result of incomplete convergence of iterative processes, round-off errors or the discrete representation of continuous physical phenomena. In RSM, the errors are assumed to be random. The response can be represented graphically, either in the three-dimensional space or as contour plots that help visualize the shape of the response surface. Contours are curves of constant response drawn in the xi, xj plane keeping all other variables fixed. Each contour corresponds to a particular height of the response surface. With this technique, the effect of two or more factors on quality criteria can be investigated and optimum values are obtained. In RSM design there should be at least three levels for each factor. The design expert (DE 9) software was used to develop the experiment plan for RSM. Table2. Shows the level of input

Response surface methodology method was used to determine optimal machining parameters for maximum material removal rate, etch factor and minimum surface roughness, undercut with less etching time. Response surface methodology (RSM) is a collection of mathematical and statistical techniques for empirical model building. By careful design of experiments, the objective is to optimize a response (output variable) which is influenced by several independent variables (input variables). Response Surface Methodology

Originally, RSM was developed to model experimental responses (Box and Draper, 1987), and then migrated into the modeling of numerical experiments. The difference is in the type of error generated by the response. In physical experiments, inaccuracy can be due, for example to measurement errors while in computer experiments numerical noise is a result of incomplete convergence of iterative processes, round-off errors or the discrete representation of continuous physical phenomena. In RSM, the errors are assumed to be random. The response can be represented graphically, either in the three-dimensional space or as contour plots that help visualize the shape of the response surface. Contours are curves of constant response drawn in the xi, xj plane keeping all other variables fixed. Each contour corresponds to a particular height of the response surface. With this technique, the effect of two or more factors on quality criteria can be investigated and optimum values are obtained. In RSM design there should be at least three levels for each factor. The design expert (DE 9) software was used to develop the experiment plan for RSM. Table2. Shows the level of input

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