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首页> 外文会议>ASME international design engineering technical conferences and computers and information in engineering conference 2014 >IDENTIFICATION OF MANUFACTURABILITY CONSTRAINTS THROUGH PROCESS SIMULATION AND DATA MINING
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IDENTIFICATION OF MANUFACTURABILITY CONSTRAINTS THROUGH PROCESS SIMULATION AND DATA MINING

机译：通过过程模拟和数据挖掘来确定可制造性

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摘要

With continued demands on high-quality and low-cost products, designers are increasingly required to explore the use of new materials and manufacturing processes. The design for manufacturability rules for unconventional materials and processes will be of great value to improve component manufacturability. Instead of going through years of trial-and-error practice to gain some "rule of thumb" design guidelines, this paper proposed a knowledge-based computational method for manufacturability constraint modeling (MCM) through process simulation, design of experiment, and data mining. With the input of geometric attributes for local critical features of a component, the pre-trained manufacturability constraint model will output the manufacturability prediction and the confidence of the prediction. The 2D visualization of the manufacturability prediction facilitates the interpretation by the human designers, and provides her with concurrent and intuitive manufacturability feedback and directed re-design suggestions. The preliminary result on mild steel stamping process demonstrated the feasibility of the method.
机译：随着对高质量和低成本产品的不断需求，越来越多的设计师要求探索新材料和制造工艺的使用。非常规材料和工艺的可制造性规则设计对于提高组件的可制造性将具有重要价值。本文没有经过多年的反复试验来获得一些“经验法则”的设计准则，而是提出了一种基于知识的可制造性约束建模（MCM）的计算方法，该方法通过过程仿真，实验设计和数据挖掘来实现。通过输入部件局部关键特征的几何属性，预训练的可制造性约束模型将输出可制造性预测和预测的置信度。可制造性预测的2D可视化有助于人工设计人员进行解释，并为她提供并发且直观的可制造性反馈和有针对性的重新设计建议。低碳钢冲压工艺的初步结果证明了该方法的可行性。

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