In this study, dyeing parameters, such as dye conc., sodium sulphide conc., salt conc., and time, have been statistically framed through full-factorial design software to generate sets of experimental variables. Cotton has been dyed using all these sets of variables separately, and then evaluated for respective surface colour strength (K/S), and colour fastness properties, such as fastness to light, washing and rubbing. The outputs thus generated are then analyzed using ANN to generate a big data, by which dyer can predict any shade. This will help in eliminating the rigorous laboratory trials and forecasting colour strength & quality of dyeing well before the dyeing process is materialized. The whole data sets are then uploaded in cloud computing to enable to acquire the data. It is observed that by assigning diffent values of K/S on cloud, the dyeing parameters can be obtained to achieve desired output in further application.

中文翻译：

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自动上色技术，以预测染色参数以获得所需的色泽和牢度

在这项研究中，已经通过全因子设计软​​件对染色参数（例如染料浓度，硫化钠浓度，盐浓度和时间）进行了统计分析，以生成实验变量集。使用所有这些变量分别对棉花进行染色，然后评估各自的表面色强度（K / S）和色牢度特性，例如耐光性，耐洗性和耐摩擦性。然后使用ANN分析由此生成的输出，以生成大数据，染色者可以通过该大数据预测任何阴影。这将有助于消除严格的实验室试验，并在实现染色工艺之前很好地预测染色的色强度和质量。然后将整个数据集上传到云计算中，以获取数据。据观察，通过在云上分配K / S的不同值，