Regression Analysis and Optimization of Experimental Data on The Cleaning Efficiency of The Peg Screw
Abstract
The article uses regression analysis to process the results of experimental studies conducted on three parameters that determine the maximum cleaning efficiency of a peg-type screw cleaner: the peg placement pitch s, the mesh hole width b, and the screw rotation speed n. Based on the B3 second-order Boh plan, 14 experiments were conducted, and the results were summarized in the form of a complete quadratic regression equation. All ten coefficients of the equation turned out to be statistically significant (t > 2.048), and the coefficient of determination was R2 = 0.964. As a result of the canonical analysis of the response surface, it was found that the stationary point of the model is the saddle point (minimax); the most optimal combination of parameters within the studied region is s ≈ 216 mm, b ≈ 6.9 mm, n = 130 rpm, where ηo ≈ 84.2% is achieved according to the model. It is shown that the results obtained are in good agreement with the parameters of the experimental sample (b = 6 mm, n = 160 rpm) adopted on the basis of the theoretical model.
Keywords
Regression analysis, Box plan, response surface
References
Akhnazarova S. L., Kafarov V. V. Methods for Experiment Optimization in Chemical Technology. - Moscow: Higher School, 1985.
Adler Yu. P., Markova E. V., Granovsky Yu. V. Experiment Planning in Search of Optimal Conditions. Moscow: Nauka, 1976. - 279 p.
Montgomery D. K. Experiment Planning and Data Analysis: Trans. from English. - L.: Sudostroenie, 1980.
Nalimov V. V., Chernova N. A. Statistical Methods for Planning Extreme Experiments. Moscow: Nauka, 1965.
Ulugbek Muminov, Guzalkhan Muminova “Fiber waste cleaning” American journal of interdisciplinary research and developmentissn online: 2771-8948website: www.ajird.journalspark.orgvolume 35, december-2024 175p.
Download and View Statistics
Copyright License
Copyright (c) 2026 Guzal Muminova, Sharif Sulaymonov, Dilshod Madrakhimov, Ulugbek Muminov

This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors retain the copyright of their manuscripts, and all Open Access articles are disseminated under the terms of the Creative Commons Attribution License 4.0 (CC-BY), which licenses unrestricted use, distribution, and reproduction in any medium, provided that the original work is appropriately cited. The use of general descriptive names, trade names, trademarks, and so forth in this publication, even if not specifically identified, does not imply that these names are not protected by the relevant laws and regulations.

Articles
| Open Access |
DOI: