Methods for developing a regression model for fiber separation in waste and determining machine productivity

Raxmonkulov, Rashid, Shavkat Ermatov

Innovative Multidisciplinary Journal of Applied Technology · 2025-yil

Annotatsiya

This work investigates the formulation of a regression model to assess fibre separation efficiency and machine productivity in textile waste processing. The experiment examined two primary variables: the distance between the grid and drum pins (x₁) and the drum rotation speed (x₂), with fibre cleaning efficiency (Y₁) as the result variable. A rotating centre composite design was used to develop the experimental plan. Regression coefficients were computed and confirmed using Student’s t-test and Fisher’s criteria to confirm model adequacy. The resultant model precisely forecasts cleaning efficiency at various operational tiers. The optimal efficiency was seen at a grid-to-drum spacing of 9 mm and a drum speed of 700–740 rpm. The experimental findings demonstrated a maximum divergence of 5% from theoretical predictions, therefore affirming the model's trustworthiness. The research establishes a solid foundation for enhancing fibre cleaning apparatus and aids in augmenting the efficiency of cotton waste recycling operations.

Maqola ma’lumotlari
MualliflarRaxmonkulov, Rashid, Shavkat Ermatov
JurnalInnovative Multidisciplinary Journal of Applied Technology
NashriyotТДТУ Қўқон филиали
ISSN2995-486X, 2995-486x
Nashr sanasi2025-06-15
Jild3
Son6
Betlar20-25
TilIngliz
Ilmiy sohaTexnika
Indeksga qo‘shilgan2026-08-26

Maqolaning asl sahifasi

Kalit so‘zlar

Experimental Results, Stationary Level, Factors Under Study, Coefficient, Variance, Fisher's Criterion, RMKT

Ilmiy soha

Texnika

Iqtibos keltirish

APARaxmonkulov, Rashid, & Shavkat Ermatov (2025). METHODS FOR DEVELOPING A REGRESSION MODEL FOR FIBER SEPARATION IN WASTE AND DETERMINING MACHINE PRODUCTIVITY. Innovative Multidisciplinary Journal of Applied Technology, 3(6), 20-25. https://www.multijournals.org/index.php/innovative/article/view/3537
GOST (OAK)Raxmonkulov, Rashid, Shavkat Ermatov METHODS FOR DEVELOPING A REGRESSION MODEL FOR FIBER SEPARATION IN WASTE AND DETERMINING MACHINE PRODUCTIVITY // Innovative Multidisciplinary Journal of Applied Technology. – 2025. – T. 3, № 6. – P. 20-25.
MLARaxmonkulov, Rashid, and Shavkat Ermatov. “METHODS FOR DEVELOPING A REGRESSION MODEL FOR FIBER SEPARATION IN WASTE AND DETERMINING MACHINE PRODUCTIVITY.” Innovative Multidisciplinary Journal of Applied Technology, 3(6), 20-25, 2025. https://www.multijournals.org/index.php/innovative/article/view/3537
ChicagoRaxmonkulov, Rashid, and Shavkat Ermatov. “METHODS FOR DEVELOPING A REGRESSION MODEL FOR FIBER SEPARATION IN WASTE AND DETERMINING MACHINE PRODUCTIVITY.” Innovative Multidisciplinary Journal of Applied Technology, 3(6), 20-25 (2025). https://www.multijournals.org/index.php/innovative/article/view/3537
HarvardRaxmonkulov, Rashid, and Shavkat Ermatov (2025) ‘METHODS FOR DEVELOPING A REGRESSION MODEL FOR FIBER SEPARATION IN WASTE AND DETERMINING MACHINE PRODUCTIVITY’, Innovative Multidisciplinary Journal of Applied Technology, 3(6), 20-25. https://www.multijournals.org/index.php/innovative/article/view/3537
BibTeX
@article{raxmonkulovrashid2025,
  title = {METHODS FOR DEVELOPING A REGRESSION MODEL FOR FIBER SEPARATION IN WASTE AND DETERMINING MACHINE PRODUCTIVITY},
  author = {Raxmonkulov, Rashid and Shavkat Ermatov},
  journal = {Innovative Multidisciplinary Journal of Applied Technology},
  year = {2025},
  volume = {3},
  number = {6},
  pages = {20-25},
  url = {https://www.multijournals.org/index.php/innovative/article/view/3537}
}

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