Intelligent Processing of Materials

研究的目标是制定、实施和 试验改进复合材料控制的新概念 制造过程 先进复合材料制造 昂贵、劳动密集且易于产生高的零件报废 rates. 原材料成本仅占总量的5 ~ 15% 制造成本。 新兴技术，如人工 智能和基于模型的控制，结合增强的 了解聚合物加工科学和技术，提供 一个协同的机会，以促进最先进的， 复合材料制造 一种将在线过程模型与 实验加工知识的研究。 系统 旨在是自适应的，并调整处理条件， 补偿原材料或产品要求的变化。 由于加工知识获取的困难和 这种知识的不稳定性，不断更新的策略 也需要改进。 为了实现这一点，一种方法 用于从过去的操作历史中捕获控制知识， 该过程是建议的。 这些创新的结果是 智能加工策略，减少零件报废 从而降低整体制造成本。 这个概念将 在选定的流程上实施和测试，即 复合材料的高压釜固化。

The objective of the research is to develop, implement and test novel concepts for improved control of composite materials manufacturing process. Advanced composite materials manufacturing is expensive, labor intensive and prone to high part rejection rates. Raw materials costs are only 5 to 15% of the total manufacturing cost. Emerging technologies such as artificial intelligence and model-based control, combined with increased understanding of polymer processing science and technology, provide a synergistic opportunity to advance the state of the art in composite manufacturing. A strategy that combines an on-line process model with experimential processing knowledge will be researched. The system is intended to be adaptive and adjust the processing conditions to compensate for changes in raw materials or product requirements. Due to the difficulty of acquiring the processing knowledge and the volatile nature of this knowledge, a strategy for constant updating and improvement is also required. To achieve this, a methodology for capturing control knowledge from past operational histories of the process is suggested. The result of these innovations is an intelligent processing strategy that will reduce part rejection rate and hence the overall manufacturing cost. The concept will be implemented and tested on a selected process, namely the autoclave curing of composites.