Optimizing Speed Frame Drafting Variables for Yarn Uniformity and Hairiness Using Taguchi Design

<p>Background: The drafting system configuration in speed frames significantly influences the quality of<br>spun yarn. Factors such as yarn irregularity, coefficient of variation (CV %), imperfections, and hairiness<br>are crucial parameters for evaluating yarn quality. This study compares the performance of PK 1500<br>and PK 1600 drafting systems with 3-over-3 and 4-over-4 configurations using Taguchi methods to<br>optimize drafting variables for better yarn uniformity and reduced hairiness.<br>Methodology: The study analyzed the effects of front and back top roller pressure, spacer size, and<br>overhang in the drafting region for PK 1500 (3/3 and 4/4) and PK 1600 (4/4) systems. Taguchi design<br>and analysis of variance (ANOVA) were employed to evaluate the impact of these variables on yarn<br>properties, including irregularity, CV%, imperfections, and hairiness.<br>Results: The 3-over-3 configuration of the PK 1500 drafting system outperformed the 4-over-4 setups in<br>producing yarn with lower unevenness, reduced CV%, and fewer imperfections. Additionally, the<br>hairiness was found to be significantly higher in yarns produced with the 4-over-4 configurations of both<br>PK 1500 and PK 1600 systems.<br>Conclusion: The study concluded that the 3-over-3 drafting system in the PK 1500 configuration offers<br>superior yarn quality for the tested material and machine settings. This configuration is recommended<br>for achieving optimal yarn uniformity and minimized hairiness, highlighting its advantages over 4-over4 setups.</p> <p> </p>

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-03-05
DOI
https://doi.org/10.5281/zenodo.14973747
Primary Topic
Textile materials and evaluations
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Optimizing Speed Frame Drafting Variables for Yarn Uniformity and Hairiness Using Taguchi Design

Zenodo (CERN European Organization for Nuclear Research)
Textile materials and evaluations
article

Optimizing Speed Frame Drafting Variables for Yarn Uniformity and Hairiness Using Taguchi Design

article en

Abstract

<p>Background: The drafting system configuration in speed frames significantly influences the quality of<br>spun yarn. Factors such as yarn irregularity, coefficient of variation (CV %), imperfections, and hairiness<br>are crucial parameters for evaluating yarn quality. This study compares the performance of PK 1500<br>and PK 1600 drafting systems with 3-over-3 and 4-over-4 configurations using Taguchi methods to<br>optimize drafting variables for better yarn uniformity and reduced hairiness.<br>Methodology: The study analyzed the effects of front and back top roller pressure, spacer size, and<br>overhang in the drafting region for PK 1500 (3/3 and 4/4) and PK 1600 (4/4) systems. Taguchi design<br>and analysis of variance (ANOVA) were employed to evaluate the impact of these variables on yarn<br>properties, including irregularity, CV%, imperfections, and hairiness.<br>Results: The 3-over-3 configuration of the PK 1500 drafting system outperformed the 4-over-4 setups in<br>producing yarn with lower unevenness, reduced CV%, and fewer imperfections. Additionally, the<br>hairiness was found to be significantly higher in yarns produced with the 4-over-4 configurations of both<br>PK 1500 and PK 1600 systems.<br>Conclusion: The study concluded that the 3-over-3 drafting system in the PK 1500 configuration offers<br>superior yarn quality for the tested material and machine settings. This configuration is recommended<br>for achieving optimal yarn uniformity and minimized hairiness, highlighting its advantages over 4-over4 setups.</p> <p> </p>

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 59%
Textile materials and evaluations
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Optimizing Speed Frame Drafting Variables for Yarn Uniformity and Hairiness Using Taguchi Design · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS