GOALI/IUCP: Improving Manufacturability of Powder Metallurgy (P/M) Superalloys by Microstructural Control
GOALI/IUCP: Improving Manufacturability of Powder Metallurgy (P/M) Superalloys by Microstructural Control
批准号:
9800430
负责人:
Ian Nettleship
金额:
$31.15万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
1998
资助国家:
美国
项目状态:
已结题
起止时间:
1998-09-01 至 2002-08-31
中文摘要
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英文摘要
DMI-9800430 Nettleship This is a Grant Opportunities for Academic Liaison with Industry (GOALI) Collaborative Research project to improve manufacturability of superalloys made using the powder metallurgy (P/M) process. Crucible Compaction Metals, a leading maker of P/M superalloys for critical applications in aerospace and energy, is the industrial partner. The academic participants are an inter-disciplinary team representing materials science and engineering and industrial and manufacturing engineering. The approach taken is to examine the P/M manufacturing process as a whole with the objective being to develop relationships of the various processing parameters to the mechanical properties of the final product. Using insights and relationships that describe how processing affects first microstructure, then final characteristics, a prescriptive model for improving manufacturability can be inferred. This model will help engineers and plant managers reduce batch variability, make continuous improvements in the processing steps, formalize successful operator actions and interventions, and ultimately design products that meet or exceed specifications while being cost effective to make. Experimental and analytical work will be conducted for the two most complex and important processing steps: inert gas atomization and hot isostatic pressing. Variables describing the beginning raw materials, the machine settings at the various manufacturing steps, the ambient conditions in the plant, operator expertise and action, and the product design will be linked to the properties of the superalloy as evidenced by detailed examination of microstructure and thorough materials testing. Using inference and inversion, the models of process-to-microstructure-to-properties can be used to prescribe the steps to be taken to improve the process.
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