Research And Application On Big Data Technology Of Quality In Dyeing And Heat Setting Process

Quantitative analysis of quality factor is the key to achieve closed-loop control of quality in the process of dyeing and finishing.Nowadays,the processes with highest frequency of remake are dyeing process and heat setting process.The main reason is that till now there was no good way to quantitatively determinie the reason of dyeing defect with traditional analytical method,and not all the effects were considered during the quality analysis of heat setting.Furthermore,large amount of historical or real-time data,and big data technology,were not sufficiently utilized in these analyses.So based on these problems,the work of this project is carried out as follows:1.According to the property of dyeing process,the process of production was classified before analysis to figure out the relationship between factor and factor,factor and process,process and final indicators of quality.Then the model to predict and analyze the cascade structure quality in dyeing process was built with probability theory to determine factors that effect the dyeing defect.2.Considering the heat setting process and the mechanical structure of the stereotypes machine,the model of Bayesian reasoning based on Clique Tree propagation algorithm was adopted to establish the model of process parameters,equipment status,manual operation and quality,by which the quality factor of heat setting process was quantitatively quantified.3.Designed the framework of big data analysis system of double computing model was based on the deep analysis of the characteristics of dyeing and finishing quality data,and combined with the respective advantages of stream computing and batch computing.Furthermore I explained the function and significance of each part and specific works of the system process.While this framework lay a solid foundation for the follow-up programming.Through above researches,it can provide effective reference for realizing theclosed-loop control of quality and promoting the intelligentization of dyeing and finishing industry.And it not only enhances the precision and accuracy of the quality analysis,but also improves quality of product and increases products pass rates.