1. A novel reuse method of machining process knowledge for similar ruled surface blades based on dual mapping.
- Author
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Han, Feiyan, Gou, Tianmao, Zhao, Jiahao, Zhang, Chuanwei, Sun, Xiaoyun, and Zhang, Bin
- Subjects
VIBRATION (Mechanics) ,NUMERICAL control of machine tools ,AUTOMATION ,SURFACE roughness ,KNOWLEDGE transfer - Abstract
Process knowledge reuse technology can improve the computer numerical control (CNC) programming efficiency and shorten the production cycle for similar parts. However, current process knowledge reuse methods focus on retrieving similar machining cases based on the machining features or topological structures of a part, which failed to deeply consider the close relationship between the 3D part geometry and CNC machining process, can result in incomplete matches between the reused knowledge and CNC process. It is more obvious for the similar complex surface parts that the most existing reuse methods are hardly to integrate 3D part geometry with CNC machining process. To overcome the problem, a reuse method for similar ruled surface blades is proposed through dual mapping mechanism in this paper, which is based on the 3D solid mapping model and spatial transformation relationship. First of all, a dual mapping mechanism is constructed to transfer process knowledge from the parameter domain to physical domain for similar ruled surface blades. Secondly, the acquired process knowledge of the ruled surface blade is characterized to the process knowledge template by the multi-vector function, followed by its inheritability is analyzed for the process knowledge reuse. Finally, two similar ruled surface blades are machined in an experiment, the machined surfaces of both blades are smooth without obvious pits in no violent vibration machining, furthermore, the surface roughness value is 4.314 µm and 4.933 µm of the two similar blades, which can meet the requirement of semi-fishing, this result indicates the correctness and validity of the process knowledge reuse method presented in this paper. [ABSTRACT FROM AUTHOR]
- Published
- 2024
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