Digital transformation to empower smart production for Industry 3.5 and an empirical study for textile dyeing

被引:55
|
作者
Ku, Chien-Chun [1 ]
Chien, Chen-Fu [1 ]
Ma, Kang-Ting [2 ]
机构
[1] Natl Tsing Hua Univ, Dept Ind Engn & Engn Management, Hsinchu 30013, Taiwan
[2] Minist Sci & Technol, Artificial Intelligence Intelligent Mfg Syst AIMS, Hsinchu 30013, Taiwan
关键词
Smart production; Digital transformation; Textile dyeing machine scheduling; Industry; 3.5; Decision support system; Traditional industry; MANUFACTURING BIG DATA; GENETIC ALGORITHM; UNISON FRAMEWORK; COLOR SEQUENCE; TFT-LCD; SYSTEM; MAINTENANCE; OPTIMIZATION; PERFORMANCE; CAPABILITY;
D O I
10.1016/j.cie.2020.106297
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Most of traditional industries in emerging countries may not be ready to migrate for Industry 4.0 directly. There is a need of effective solutions to support digital transformation of traditional industries. Textile industry is facing global competition for mass customization to address dynamic customer demands. To enable the challenge from mass production to build-on-demand with small lot size and diversified product mixes, this study aims to develop a solution to support traditional industries to adopt smart manufacturing and empower digital transformation. Following a framework as systematic approach to collect, identify, and analyze related steps and decisions for an organization, a decision support system for dyeing machine scheduling is developed to empower smart manufacturing and break down information silos. In particular, setup time for textile dyeing operations is sequence-dependent, and products of different types and colors require setups for tank cleaning. The results have shown the practical viability of the proposed approach and Industry 3.5. Indeed, the developed solution has been implemented in a textile company in Taiwan.
引用
收藏
页数:11
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