Results 81 to 90 of about 77,670 (214)

A practical method to monitor tool wear in end milling using a changing cutting force model that requires no additional sensors

, 2021
Kazuki Kaneko, Isamu NISHIDA, Ryuta Sato, Keiichi SHIRASE   +3 more
openalex   +2 more sources

Tool Wear State Identification Based on SVM Optimized by the Improved Northern Goshawk Optimization. [PDF]

Sensors (Basel), 2023
Wang J, Xiang Z, Cheng X, Zhou J, Li W.
europepmc   +1 more source

Research on Tool Wear Prediction Method Based on CNN-ResNet-CBAM-BiGRU. [PDF]

Sensors (Basel)
Sun B, Wang H, Zhang J, Zhang L, Wu X.
europepmc   +1 more source

Tool Wear Issues in Hot Forging of Steel. [PDF]

Materials (Basel), 2023
Krawczyk J, Łukaszek-Sołek A, Śleboda T, Lisiecki Ł, Bembenek M, Cieślik J, Góral T, Pawlik J.   +7 more
europepmc   +1 more source

Cutting parameter-tool material interaction on PcBN tool wear behaviour in ductile iron machining. [PDF]

Sci Rep
Wang P, Li X, Jiu Y, Yin H, Zhang Y.
europepmc   +1 more source

Multivariate time series data of milling processes with varying tool wear and machine tools. [PDF]

Data Brief, 2023
Denkena B, Klemme H, Stiehl TH.
europepmc   +1 more source

Hole Surface Topography and Tool Wear in CFRP Drilling

, 2016
Gérard Poulachon, J.C. Outeiro, Christophe Ramirez, Victorien André, Guillaume Abrivard   +4 more
openalex   +1 more source

The Effects of Lubricooling Ecosustainable Techniques on Tool Wear in Carbon Steel Milling. [PDF]

Materials (Basel), 2023
Villarrazo N, Caneda S, Pereira O, Rodríguez A, López de Lacalle LN.   +4 more
europepmc   +1 more source

A Knowledge-Embedded Deep Learning Model for Online Monitoring of Tool Wear with Variable Cutting Parameters

Bo Zhou, Jianjian Wang, Pingfa Feng, Xiangyu Zhang, Dingwen Yu, Jianfu Zhang   +5 more
openalex   +1 more source

Tool Wear Condition Monitoring Method Based on Deep Learning with Force Signals. [PDF]

Sensors (Basel), 2023
Zhang Y, Qi X, Wang T, He Y.
europepmc   +1 more source