面向绿色制造的涤纶低弹丝生产关键工艺参数优化

Optimization of key process parameters for polyester drawn textured yarn orientedto green manufacturing

为了实现涤纶低弹丝生产过程绿色低碳制造,文章以加弹工艺为研究对象,提取关键工艺参数并考虑实际约束条件,构建以涤纶低弹丝韧度最大、碳排放最小及能量效率最高为综合目标的多目标优化模型。采用信噪比与改进综合赋权的灰色关联分析相结合的方法,将模型优化从多目标向单目标转化;通过Box-Behnken Design试验设计获取试验数据,基于响应曲面法建立灰色关联度与关键工艺参数之间的二阶响应模型,进而应用遗传算法对优化模型进行求解。最后,通过算例验证与分析,结果表明该模型更为合理地优化了涤纶低弹丝生产过程中的关键工艺参数,在保证纤维质量的同时使碳排放量较传统工艺条件下降低了3.81%,提高了能源利用效率。

In order to realize green and low carbon manufacturing of polyester drawn textured yarn(P-DTY),the texturing process was selected as the research object,and the key process parameters were extracted.Besides,the actual constraints were considered to establish a multi-objective optimization model with the maximum toughness,the minimum carbon emission and the maximum energy efficiency of P-DTY as the comprehensive objective.The model optimization was transformed from multi-objective to single objective by combining signal-to-noise ratio and grey correlation analysis with improved comprehensive weighting.Then,Box-Behnken Design was used to obtain test data,and a second-order response model between the gray correlation degree and key process parameters was established based on the response surface method.Further,genetic algorithm was applied to solve the optimization model.Finally,the results of example verification and analysis show that the model is more reasonable,because it optimized the key process parameters in the production process of P-DTY,which can reduce the carbon emission by 3.81%and improve energy use efficiency under the precondition of ensuring fiber quality,compared with the traditional process.