近年來由於人們對於服飾穿著特性之要求漸漸的提高，各種附加機能性的織物隨之誕生，以迎合消費者在穿著時對品質特性與舒適感的追求。在特定環境條件下，對衣物表面感受與舒適性的體驗，受到織物的色差、觸感柔軟度、透濕度及熱導度性質的影響極大。現代紡織上一般採用後整理的方法來提高織物的外觀或其他性能，磨毛加工即為一種常見的後整理方法。目前在磨毛加工過程中，為符合感官變化感受與舒適性之要求，必須依各材料特性加以調整，主要方法在於加工參數的設定。本研究將織物感官品質特性的表面柔軟度(surface softness)與色差(color difference)及主要舒適特性的透濕度(water vapor transmission)及熱導度(thermal transport)，利用田口方法結合灰關聯分析(grey relational analysis) 與模糊推論(fuzzy approach)求出最佳化多重品質特性的磨毛加工參數組合。首先，對磨毛機主要之加工參數，以田口方法之實驗規劃法規劃直交表。將量測之織物表面柔軟度、色差與透濕度、熱導度數據計算雜訊比(S/N)，再進行變異數分析(analysis of variance, ANOVA)，獲得對品質特性影響較大的顯著因子，再利用灰關聯與模糊推論分析，由回應表與回應圖取得多重品質特性的最佳加工參數組合。以此最佳加工參數組合設定加工參數，可有效控制磨毛布的感官品質特性及舒適品質特性，並經由確認實驗以95%信心區間驗證實驗具有可靠性與再現性。

In recent years, as consumers have higher demands for the functionality of clothing, fabrics with additional functionality have been developed. The state of physical functionality experienced by a wearer under a given environmental condition is greatly influenced by the surface softness, color difference, thermal and moisture transport properties of the fabric. In modern textiles, finishing is generally used to improve the appearance or other properties of fabrics. Sueding is a common finishing method. In order to meet the requirements of functionality in the process of sueding, the production process must be adjusted according to the features of fabrics. The main method is the setting of processing parameters. This study focuses on the surface softness, color difference, water vapor transmission and thermal transport, which are the main functional characteristics, and uses the Taguchi method combined with grey relational analysis and fuzzy approach to acquire the combination of sueding processing parameters to optimize multiple functional characteristics. Firstly, for the main processing parameters of the sueding machine, the Taguchi Method is used to obtain orthogonal array for the experimental design. The measured surface softness, color difference, water vapor transmission and thermal transport data of the fabric are used to calculate the signal to noise (S/N) ratio. Analysis of variance (ANOVA) is conducted to obtain the significant factors with a greater impact on functional characteristics. The grey relational analysis and fuzzy approach are used to analyze and obtain the optimal combination of processing parameters of multiple functional characteristics. The quality of suede fabric can be controlled effectively by using the optimum processing parameters to set the processing parameters, and the 95% confidence interval validates the reliability and reproducibility of experiment.

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