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Nowadays, instant decision making through applying available vast raw data has been considered as one of the main challenges in various industries. Accurate and quick decisions can lead to enhancement of the product quality, especially in continuous production lines. Meanwhile, the quality outputs take several hours to be determined. In addition, stoppages during production procedure could result in changing the feature settings and affecting the product quality. Herein, a new hybrid approach has been proposed to address the mentioned challenges faced by industries. In the first step of the suggested model, the data mining approach was utilized to predict the possible required stoppages and their duration. Then, the real production time of order was obtained through the improved time series classification model based on fuzzy support vector machine and genetic algorithm. Afterward, the product quality level …