Drafting Force Forecasting Using Genetic Programming

Ildephonse Nibikora; Jun Wang

doi:10.4028/www.scientific.net/AMR.175-176.355

Paper Titles

Preparation and Characteristics of Electrospun Polypropylene Fibers: Effect of Organic Solvents
p.337

Poly(L-Lactide) Composite Nanofibers Incorporating POSS-MWNTs
p.341

Experimental Development of Lumbar Supporter and its Evaluation by EMG
p.345

Production of Silk Sericin Nanofibers
p.348

Drafting Force Forecasting Using Genetic Programming
p.355

Automatic Inspection of Silk Spinning Yarn Fineness
p.360

Feature Extraction Using Auto-Regression Spectral Analysis for Fabric Defect Detection
p.366

Automatic Inspection of Silk Fabric Density Based on Multi-Scale Wavelet Analysis
p.371

The Design of Untwisted Yarn-Dyed Dobby Double-Faced Fabric
p.376

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 175-176Drafting Force Forecasting Using Genetic...

Drafting Force Forecasting Using Genetic Programming

Abstract:

Genetic programming was used to find out a mathematical model for drafting force from drafting process parameters on the drawing frame, which fits the experimental data as much as possible. The study used rayon fibers as the raw material in the mini-draw frame. The process parameters on the draw frame such as front roller speed, front roller draft, back roller speed and back roller draft as variables were investigated. The paper used the principle that there is linear relationship between drafting force and deformation from the strain gauges in the sensor. The data obtained from online measurement device was used for training and testing on the genetic programming. A comparison between experimental and predicted data was done. The results show very good agreement between the experimental and predicted values. Furthermore, this article shows that genetic programming can provide further use for setting up the machine process parameters without requiring an expert in the field.