面向智能制造的真空注型工艺质量控制方法

Quality Control Method of VC Processes for Intelligent Manufacturing

针对真空注型(VC)产品质量依赖于工艺设计人员经验,造成VC装备自动化程度低、加工柔性差、产品质量难以控制等问题,基于计算机图形学和人工智能技术,建立一种面向 VC工艺的质量控制模型.通过构建体素化模型,近似求解壁厚、均匀程度、体积等模具型腔几何特征参数;在此基础上,融合案例推理和神经网络推理技术,建立型腔几何特征参数与成形工艺间的关系模型,充分利用历史案例,实现初始工艺参数的智能推荐;利用基于规则的模糊逻辑推理方法,挖掘工艺设计人员经验,对试模后的产品缺陷进行智能修正.生产实例说明,基于上述思想方法和推理机制的质量控制模型有较好的推理和质量控制能力.

According to the problems that the VC product quality was difficult to be controlled,low automation of VC equipment and poor flexible processing,depended on the experience of process designers,a quality control model for VC processes was established based on the computer graphics and artificial intelligence.By constructing the voxel model,the geometric parameters of the cavity,such as wall thickness,uniformity and volume,were approximated.On the basis of this,case-based reasoning and network-based reasoning technology were used to establish the relationship model between cavity geometrical parameters and forming processes,which made full use of the historical processing cases to achieve intelligent recommendation of initial processing parameters;then technicians’ experiences were excavated to correct product defects by fuzzy inference after trial mode.The examples show that the quality control model based on the above thought method and reasoning mechanism has better reasoning and quality control ability.