search for




 

Analysis of influence factor for the woven speed on the drying process
Journal of the Korean Data & Information Science Society 2019;30:631-43
Published online May 31, 2019;  https://doi.org/10.7465/jkdi.2019.30.3.631
© 2019 Korean Data and Information Science Society.

Suk-gon Yang 1 · Hwa-Jung Lee 2 · Byeong-Gyu Seo 3 · Suk-Bok Kang 4

1Advanced processing development center, DYETEC, 3Department of Patient Experience Index, Semagroup , 24Department of Statistics, Yeungnam University
Correspondence to: Professor, Department of Statistics, Yeungnam University, Gyeongbuk, 38541, Korea. E-mail: sbkang@yu.ac.kr
Received April 23, 2019; Revised May 16, 2019; Accepted May 16, 2019.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
This paper find out a important variables for the woven speed based on the collected data from a woven fabric dyeing and drying process. Relevant variables were identified and used in a correlation analysis in order to select highly correlated variables with the woven speed, which provides an important information for setting the duration and temperature of the drying process. Based on the results, the processing weight is divided into five levels and a regression model is proposed for the average woven speed based on the processing weight, the processing density, the average temperature difference, the average temperature of the chamber, the average moisture level, and the average moisture proportion for each weight level. As a result, the average moisture proportion is included in all models as it has the greatest effect on the average woven speed except on the second level of processing weight.
Keywords : Average woven speed, drying time, multiple linear regression analysis, polyester, processing density, processing weight, temperature, verage moisture proportion.