An Industrial Dyeing Recipe Recommendation System for Textile Fabrics Based on Data-Mining and Modular Architecture Design
We report a new fabric dyeing recipe recommendation system which is based on mining industrial dyeing manufacturing data and a system design with modular architecture. Unlike traditional dyeing recipe recommendation systems, our method does not rely on labor-intensive calibration works between dye c...
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Format: | Article |
Language: | English |
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IEEE
2021-01-01
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Series: | IEEE Access |
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Online Access: | https://ieeexplore.ieee.org/document/9557294/ |
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author | Xianan Qin Xiaoming John Zhang |
author_facet | Xianan Qin Xiaoming John Zhang |
author_sort | Xianan Qin |
collection | DOAJ |
description | We report a new fabric dyeing recipe recommendation system which is based on mining industrial dyeing manufacturing data and a system design with modular architecture. Unlike traditional dyeing recipe recommendation systems, our method does not rely on labor-intensive calibration works between dye concentrations and the color. Also, the system is generally designed for different dyeing tasks. We describe the framework of our method and discuss strategies that are used for building the system. The system is built in the form of modular architecture which is made up of multiple gradient boosting regression tree models (GBRT). Each GBRT has been trained for predicting dye concentrations of a dye combination set (DCS) for a fabric type. Methods for model training and typical model performance are reported in the paper as well. |
first_indexed | 2024-04-12T10:40:21Z |
format | Article |
id | doaj.art-82ed556e6cda4995978523f03357a349 |
institution | Directory Open Access Journal |
issn | 2169-3536 |
language | English |
last_indexed | 2024-04-12T10:40:21Z |
publishDate | 2021-01-01 |
publisher | IEEE |
record_format | Article |
series | IEEE Access |
spelling | doaj.art-82ed556e6cda4995978523f03357a3492022-12-22T03:36:36ZengIEEEIEEE Access2169-35362021-01-01913610513611010.1109/ACCESS.2021.31172619557294An Industrial Dyeing Recipe Recommendation System for Textile Fabrics Based on Data-Mining and Modular Architecture DesignXianan Qin0https://orcid.org/0000-0002-5625-0178Xiaoming John Zhang1National Engineering Laboratory of Textile Fiber Materials and Processing Technology, Zhejiang Sci-Tech University, Hangzhou, ChinaBeijing Institute of Mathematical Sciences and Applications (BIMSA), Beijing, ChinaWe report a new fabric dyeing recipe recommendation system which is based on mining industrial dyeing manufacturing data and a system design with modular architecture. Unlike traditional dyeing recipe recommendation systems, our method does not rely on labor-intensive calibration works between dye concentrations and the color. Also, the system is generally designed for different dyeing tasks. We describe the framework of our method and discuss strategies that are used for building the system. The system is built in the form of modular architecture which is made up of multiple gradient boosting regression tree models (GBRT). Each GBRT has been trained for predicting dye concentrations of a dye combination set (DCS) for a fabric type. Methods for model training and typical model performance are reported in the paper as well.https://ieeexplore.ieee.org/document/9557294/Data miningmanufacturing industriestextile technology |
spellingShingle | Xianan Qin Xiaoming John Zhang An Industrial Dyeing Recipe Recommendation System for Textile Fabrics Based on Data-Mining and Modular Architecture Design IEEE Access Data mining manufacturing industries textile technology |
title | An Industrial Dyeing Recipe Recommendation System for Textile Fabrics Based on Data-Mining and Modular Architecture Design |
title_full | An Industrial Dyeing Recipe Recommendation System for Textile Fabrics Based on Data-Mining and Modular Architecture Design |
title_fullStr | An Industrial Dyeing Recipe Recommendation System for Textile Fabrics Based on Data-Mining and Modular Architecture Design |
title_full_unstemmed | An Industrial Dyeing Recipe Recommendation System for Textile Fabrics Based on Data-Mining and Modular Architecture Design |
title_short | An Industrial Dyeing Recipe Recommendation System for Textile Fabrics Based on Data-Mining and Modular Architecture Design |
title_sort | industrial dyeing recipe recommendation system for textile fabrics based on data mining and modular architecture design |
topic | Data mining manufacturing industries textile technology |
url | https://ieeexplore.ieee.org/document/9557294/ |
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