Open AccessBuilding a wear resistance model of drilling operation using locally adaptive regression models
Author(s) -
Alexander Popov,
Vitaliy S. Karmanov
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1791/1/012021
Subject(s) - context (archaeology) , drilling , class (philosophy) , computer science , model building , regression analysis , mathematical model , mathematical optimization , engineering , mathematics , mechanical engineering , machine learning , geology , artificial intelligence , statistics , paleontology , physics , quantum mechanics
The paper deals with building mathematical models of metal cutting processes in the context of the optimum performance problem. A new class of wear resistant models called «locally adaptive models» is proposed. A practical case solution is given.