Vol.71, No.1, 2022, pp.1661-1675, doi:10.32604/cmc.2022.021642
OPEN ACCESS
ARTICLE
Decoding of Factorial Experimental Design Models Implemented in Production Process
  • Borislav Savkovic1, Pavel Kovac1, Branislav Dudic2,3,*, Michal Gregus2
1 University of Novi Sad, Faculty of Technical Sciences, Novi Sad 21000, Serbia
2 Comenius University in Bratislava, Faculty of Management, Bratislava, 820054 Slovakia
3 University Business Academy, Faculty of Economics and Engineering Management, Novi Sad 21000, Serbia
* Corresponding Author: Branislav Dudic. Email:
Received 09 June 2021; Accepted 07 September 2021; Issue published 03 November 2021
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. Models without and with the mutual influence of independent variables differ. 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.
Keywords
Mathematical modeling; design of experiments; functions; coding; decoding; variable; regression coefficients
Cite This Article
Savkovic, B., Kovac, P., Dudic, B., Gregus, M. (2022). Decoding of Factorial Experimental Design Models Implemented in Production Process. CMC-Computers, Materials & Continua, 71(1), 1661–1675.
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