4.6 Article

Application of a hybrid process for high precision manufacture of difficult to machine prismatic parts

期刊

出版社

SPRINGER LONDON LTD
DOI: 10.1007/s00170-014-6053-7

关键词

Hybrid process; Process planning; Fused filament fabrication; CNC machining; Inspection

向作者/读者索取更多资源

In recent years, hybrid processes, which combine various individual manufacturing processes on a single platform, have drawn significant attention due to their ability to capitalise on the advantages of independent processes whilst minimising their disadvantages. Increased material removal rate, tool life, dimensional and geometric accuracy, and reduced production times have been achieved as some typical advantages of using hybrid processes. Despite the capabilities of individual processes continuously improving, production of highly accurate and complex structures, such as internal features, without assembly is still considered to be extremely difficult due to limited tool accessibility. This paper introduces a hybrid process entitled iAtractive, combining additive (i.e. Fused Filament Fabrication, FFF), subtractive (i.e. CNC machining) and inspection, which is capable of accurately producing complex part geometries. A novel process planning algorithm is developed, which addresses the three most important factors, namely, tool accessibility, production time and dimensional accuracy. A part is first orientated in a position and then decomposed into a number of subparts. The additive operations for producing these subparts together with the build directions are determined. The machining and inspection operations are then inserted into the scheduled additive operations, respectively, ensuring that the dimensions of the produced features are within the desired tolerances. A test part with internal features has been manufactured as one complete unit, where each surface of the features was finish machined, demonstrating the efficacy of the hybrid process and the process planning algorithm.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据