Abstract
The abrasive tools are the weakest element in the grinding process system, to which great attention is being paid by scientific and industrial collectives. Eleven highly porous wheels (HPWs) were tested: CBN30 (B76, B107, B126, B151) 100 OVK27-КF40; CBN30 B107 100 OVKC10-КF40; CBN30 B126 100(M, L) VK27- (КF25, КF40); LKV50 (B107, B126) 100 (M, O) VK27-КF40. Assessment of the surface topography was carried out by roughness parameters R a , R max , and S m (GOST 25472-82), which were considered random variables with their position and dispersion measures. Two artificial intelligence systems – fuzzy logic (FL) and neural networks (NN) – were used to analyze the HPW’s cutting capability (CC). In both cases, the best CC was predicted for grinding with CBN30 (B76 and B151) 100 OVK27-КF40 and LKV50 (B107) 100 OVK27-KF40. In the absence of a training process in FL modeling, the assessments for the wheels with a low CC were less reliable.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
