产品寿命周期质量特性重要度识别模型

Importance degree recognition model of quality characteristics within product's life cycle

针对产品质量特性(Quality Characteristics,QCs)重要度人工识别困难的情况,提出了基于人工神经网络(ANNs)技术的产品寿命周期QCs重要度识别模型。首先提取QCs特征参数并对其归一化,建立QCs特征参数向量,其次利用ANNs技术确定QCs特征参数重要度,建立QCs特征参数重要度向量,然后再次利用ANNs并以QCs特征参数重要度向量为模型的输入,建立QCs重要度识别模型,最后给出产品寿命周期QCs重要度识别框图,指导产品寿命周期QCs重要度的识别。仿真实例验证了所提理论与方法的正确性和有效性。

Based on the condition that the artificial cognition of importance degree for product quality characteristics （QCs） is difficult,the importance degree recognition model of the product quality characteristics within the entire life cycle was proposed by using the artificial neural networks （ANNs） technology in this paper.First is to extract the QCs characteristic parameters and normalized to establish the QCs characteristics parameter vector,the second is to determine the importance degree of QCs characteristic parameters by using ANNs technology and establish the importance vector of QCs characteristic parameters,and furthermore the establishment of a recognition model of importance degree of QCs was carried out by making use of ANNs once again and using QCs important characteristic parameter vector as a model input,and finally the recognition block diagram of importance degree of product＇s quality characteristics within its entire life cycle was given,guiding its recognition of the importance degree of production＇s quality characteristics within its entire life cycle.The correctness and effectiveness of the proposed theory and methods are verified by simulation examples.