Using cutting temperature and chip characteristics with neural network BP and LSTM method to predicting tool life

Chen, Shao-Hsien; Lin, Yu-Ting

doi:10.1007/s00170-023-11570-3

Cited by 4 publications

(1 citation statement)

References 24 publications

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“…The development of production systems, the creation of a digital environment to support the technological process [2][3][4][5][6][7] with access to CNC systems [8][9][10] and the monitoring of information about the cutting from sensors [11][12][13][14] has made it possible to increase the requirements for accuracy and improve the design complexity of tool designs [15][16][17][18][19][20]. In this connection, to ensure production flexibility, it is necessary to use such flexible methods of technological preparation as the possibilities for producing various standard sizes of end mill designs are wide.…”

Section: Introductionmentioning

confidence: 99%

Digital twin of the technological process for grinding helical flutes of a cutting tool

Pivkin

2024

Real-Time Processing of Image, Depth, and Video Information 2024

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Helical flutes are the most important elements of axial cutting tools. The technological process for manufacturing helical flutes is multifactorial, complex and difficult to quickly calculate online. The production of flutes is carried out on a multiaxis grinding machine with a conical or cylindrical grinding wheel. The task is also complicated by the fact that in more than one section the shape of the helical flute does not match the grinding wheel. Therefore, the development of technology and its preparation requires a long time. The work proposes a digital twin for the production of helical flutes with the input results of processing 40 variants of technological processes and compares them with the results of processing images of helical surfaces in real time. The work for the first time established an analytical connection between the shape of the grinding wheel, the geometry of the front helical surface of the cutter, the trajectory of movement and the location of the wheel, structured into a system of signals from sensors with a controlled monitoring effect per unit of time. This made it possible to install real-time control indicators to assess accuracy in the processing area and, based on the indicator, to form a control action to ensure the production of suitable products. This work allows us to lay the crating for a new direction in the field of industrial production of cutting tools. The use of real-time data in the current time window to evaluate future spatio-temporal information of the process state makes it possible to continuously adjust the movement of the grinding wheel with a given error and deviation, which is ensured by a continuous analytical solution that takes into account the basic geometric parameters of the cutter and the grinding wheel.

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