The Development of a Digital Twin of a Cutting Tool for Mechanical Production
| Authors: Kabaldin Y.G., Shatagin D.A., Kuzmishina A.M. | Published: 15.04.2019 |
| Published in issue: #4(709)/2019 | |
| Category: Mechanical Engineering and Machine Science | Chapter: Technology and Equipment for Mechanical and Physico-Technical Processing | |
| Keywords: cutting tool, neural network models, digital twin, choice of coating composition, tool wear |
A digital model (twin) of a cutting tool based on neural network modeling is proposed in this work. It is shown that the developed virtual model makes it possible to optimize the composition and structure of wear-resistant coating and to determine the processing modes that ensure the maximum wear resistance of the cutting tool. The optimization can be performed before the actual manufacturing of the cutting tool by varying the input data of the neural network has taken place. A digital passport of the cutting tool allows the consumer to avoid buying a counterfeit product. Information security issues are considered.
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