基于BP神经网络的生产效能评价方法

Production Efficiency Evaluation Method Based on BP Neural Network

随着新一代信息技术飞速发展,航空制造“数智化”转型诉求愈加强烈,然而产线数字化、智能化改造进程中,缺乏科学的生产效能评价手段,难以准确识别制造薄弱环节。面对这一严峻挑战,提出一种基于BP神经网络的生产效能评价方法:构建一种生产效能评价体系,对影响生产效能的关键因素指标进行分析,选取适合的度量元集合并量化;以生产周期、生产质量为目标参数,引入BP神经网络,构建历史数据集训练,形成生产效能评价模型;通过实际制造数据对生产效能评价模型进行仿真测试,验证了所提方法的有效性和科学性。

With the rapid development of a new generation of information technology,the demand for intelligent transformation of aviation manufacturing is becoming more and more intense.However,in the process of digital and intelligent transformation of production lines,there is a lack of scientific production efficiency evaluation means,which makes it difficult to accurately identify the manufacturing weak links.To face this serious challenge,this paper proposes a production efficiency evaluation method based on Back Propagation neural network.First,a production efficiency evaluation system is constructed to analyze the key factor indicators affecting the production efficiency and select and quantify a suitable set of metric elements.Then,based on the target parameters of production cycle and production quality,BP neural network is introduced to construct the historical data set training to form the production efficiency evaluation model.Finally,experiments on the production effectiveness evaluation model using actual manufacturing data validate the effectiveness and scientificity of the method proposed in this paper.