Decoding of Factorial Experimental Design Models Implemented in Production Process Keywords: Mathematical modeling; design of experiments; functions; coding; decoding; variable; regression coefficients info:eu-repo/semantics/article CMC-COMPUTERS MATERIALS & CONTINUA volume: 71 number: 1 startpage: 1661 endpage: 1675 http://creativecommons.org/licenses/by/4.0/legalcode eng 2022 application/pdf 297425 bytes Abstract: The paper deals with factorial experimental design models decoding. For the ease of calculation of the experimental mathematical models, it is convenient first to code the independent variables. When selecting independent variables, it is necessary to take into account the range covered by each. A wide range of choices of different variables is presented in this paper. After calculating the regression model, its variables must be returned to their original values for the model to be easy recognized and represented. In the paper, the procedures of simple first order models, with interactions and with second order models, are presented, which could be a very complicated process. Modelswithoutandwiththemutualinfluenceofindependentvariablesdiffer. The encoding and decoding procedure on a model with two independent first-order parameters is presented in details. Also, the procedure of model decoding is presented in the experimental surface roughness parameters models’ determination, in the face milling machining process, using the first and second order model central compositional experimental design. The simple calculation procedure is recommended in the case study. Also, a large number of examples using mathematical models obtained on the basis of the presented methodology are presented throughout the paper. https://unilib.phaidrabg.rs/o:6073 doi:10.32604/cmc.2022.021642 Savkovic, Borislav Kovac, Pavel Dudic, Branislav Gregus, Michal