| Summary: | 碩士 === 逢甲大學 === 紡織工程所 === 94 === Diversified products mix and precise quality control are important factors for cost controlling in the weaving production operation. This research utilizes open questionnaire study to analyze the important factors which cause fabric width shrinkage. These factors are then used as the input parameters for artificial neural network model design.
Results show that the artificial neural network prediction model can be used to predict the Shrinkage amount of greige fabric width when weaving finished. The accuracy can be reached to more than 92%. The factors which influence fabric width shrinkage are structure, yarn types, yarn count, yarn twist, yarn density, weave density, and cover factor, etc.
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