Rule and branch-and-bound algorithm based sequencing of machining features for process planning of complex parts

Wei Wang, Yingguang Li () and Lingling Huang
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Wei Wang: Nanjing University of Aeronautics and Astronautics
Yingguang Li: Nanjing University of Aeronautics and Astronautics
Lingling Huang: Nanjing University of Aeronautics and Astronautics

Journal of Intelligent Manufacturing, 2018, vol. 29, issue 6, No 11, 1329-1336

Abstract: Abstract The machining sequence of machining features is vital to achieve efficient and high quality manufacturing of complex NC machining parts. In most feature-based process planning system, the machining features are sequenced as the lowest level unit. However, a single machining feature of complex parts such as aircraft structural parts is usually machined by multiple machining operations. The one-to-many mappings between the machining features and the machining operations cause the increase of the non-cutting tool path. In order to solve this problem, some types of machining features of complex parts are decomposed into several sub-machining features that are associated with a single machining operation individually according to the rules which are abstracted from the machining process of complex parts. Benefitting from the decomposition, the sub-machining features from different machining feature can be assembled into a sub-machining feature in order to avoid the cutting tool marks. The different types of sub-machining features are sequenced in the light of some rules which are also extracted from the machining process of complex parts. And the branch-and-bound algorithm are employed to sequence the same type sub-machining features to minimum the non-cutting tool path. A pilot feature-based process planning system has been developed based on this research, and has been used in some aircraft manufacturers in China.

Keywords: Process planning; Machining features; Feature sequencing; Operation sequencing; Rule-based reasoning; Branch-and-bound Algorithm (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10845-015-1181-y

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