Multi-cutter selection and cutter location (CL) path generation for five-axis end-milling (finish cut) of sculptured surfaces

Geng, Lin; Zhang, Y. F.; Li, H. Y.

doi:10.1007/s00170-013-5213-5

Cited by 8 publications

(2 citation statements)

References 16 publications

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“…Using multi-tool combinations and automatic toolchanging technology on the same CNC can improve the machining e ciency of complex machining features [21,22]. Adequate methods of cutting tool combination were proposed to solve the practical machining problems, which mainly focuses on improving the machining e ciency, such as complex cavity [23], surface milling [24,25], and multigroove [26].…”

Section: Introductionmentioning

confidence: 99%

A comprehensive cutting tool adaptation method of multi-feature part based on evolutionary game

Huo,

Zhou,

Liu

et al. 2023

Preprint

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The adaptation of cutting tools is the key link of machining, although a lot of work has been done to achieve tool selection for single features, relatively little research on tool scheme adaptation for multi-feature parts as a whole. In order to take into account the factors of matching, efficiency, cost, manufacturability, and environment, a comprehensive optimization method of a multi-feature tool scheme is proposed in this work. Firstly, the critical tool of a complex feature is defined, and a tool combination method with complex single features is proposed to generate an efficient tool strategy. Secondly, a tool scheme optimization model of multi-feature parts is constructed, where each machining feature is mapped to a game player in the model space, and the set of available tools is mapped to the player strategies. In addition, the classical evolutionary game algorithm is improved to adapt to the model, according to the large difference in the number and type of features of parts. Finally, a square test piece is taken as an example to verify the proposed method, and the results show that the method presented in the paper can efficiently obtain the customer-preferred tool scheme.

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Section: Introductionmentioning

confidence: 99%

A comprehensive cutting tool adaptation method of multi-feature part based on evolutionary game

Huo,

Zhou,

Liu

et al. 2023

Preprint

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“…These literatures are mainly focused on tool sequence optimization. In addition, Geng et al (2013) present a new method for selecting the optimal multi-cutter set for five-axis finish machining. Meng et al (2014) present a new method of the optimal barrel cutter selection for the flank milling of blisk.…”

Section: Introductionmentioning

confidence: 99%

Tool selection method based on transfer learning for CNC machines

et al. 2018

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Abstract. Owing to the changes in product requirements and development of new tool technology, traditional tool selection approach based on the human experience is leading to time-consuming and low efficiency. Under the cooperation of historical data resource accumulated by manufacturing enterprises, with human expert resource, a new tool selection mechanism can be established. In this paper, we apply transfer learning to tool selection issue. Starting from the foundation of migration, we showed a unified expression of expert experience and process case in a multi-source heterogeneous environment. Then, we propose a transfer learning algorithm (TLrAdaBoost) based on AdaBoost, which uses a small amount of target domain data (expert experience sample) and a large number of source domain low-quality data (process case sample), to build a high-quality classification model. Experimental results show the effectiveness of the proposed algorithm.

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Optimizing wire-cut EDM parameters through evolutionary algorithm: a study for improving cost efficiency in turbo-machinery manufacturing

Sen,

Dasgupta,

Bhowmik

2024

Int J Interact Des Manuf

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Multi-cutter selection and cutter location (CL) path generation for five-axis end-milling (finish cut) of sculptured surfaces

Cited by 8 publications

References 16 publications

A comprehensive cutting tool adaptation method of multi-feature part based on evolutionary game

A comprehensive cutting tool adaptation method of multi-feature part based on evolutionary game

Tool selection method based on transfer learning for CNC machines

Optimizing wire-cut EDM parameters through evolutionary algorithm: a study for improving cost efficiency in turbo-machinery manufacturing

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