Stereo nerve network: systematic construction, computational process, and intelligent manufacturing

Abstract Based on the characteristics of intelligent manufacturing and the theory of technology diffusion, this paper constructs a cellular automata model with government support policy, information exchange, technology maturity, diffusion intermediary, and market competition as the influencing factors and analyzes the influence mechanism of the first three main factors on the diffusion of intelligent manufacturing technology in industrial clusters using MATLAB. This paper also makes an empirical analysis of the diffusion of intelligent manufacturing technology in the bearing industry cluster in Xinchang County and finds that the results are basically consistent by comparing the simulation data with the fit degree of the real data. In this paper, the diffusion intermediary and government support policy have the greatest influence on the application of intelligent manufacturing in small- and medium-sized enterprises, and the model proposed in this paper is effective.

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Intelligent manufacturing of color blended yarn: Color matching algorithm and manufacturing process through computer numerically controlled ring spinning system

Journal of Engineered Fibers and Fabrics ◽

10.1177/15589250211006539 ◽

2021 ◽

Vol 16 ◽

pp. 155892502110065

Author(s):

Peng Cui ◽

Yuan Xue ◽

Yuexing Liu ◽

Xianqiang Sun

Keyword(s):

Intelligent Manufacturing ◽

Prediction Algorithm ◽

Ring Spinning ◽

Blended Yarn ◽

Spun Yarn ◽

Computer Numerically Controlled ◽

Ring Spun Yarn ◽

High Production ◽

Color Prediction ◽

Textile Products

Yarn-dyed textiles complement digital printing textiles, which hold promise for high production and environmentally friendly energy efficiencies. However, the complicated structures of color-blended yarns lead to unpredictable colors in textile products and become a roadblock to developing nonpollution textile products. In the present work, we propose a framework of intelligent manufacturing of color blended yarn by combining the color prediction algorithm with a self-developed computer numerically controlled (CNC) ring spinning system. The S-N model is used for the prediction of the color blending effect of the ring-spun yarn. The optimized blending ratios of ring-spun yarn are obtained based on the proposed linear model of parameter W. Subsequently, the CNC ring-spinning frame is used to manufacture color-blended yarns, which can configure the constituent fibers in such a way that different sections of yarn exhibit different colors.

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