Research on Tool Wear Monitoring Technology Based on Variational Mode Decomposition and Back Propagation Neural Network Model. [PDF]
Wang K, Wang A, Wu L.
europepmc +1 more source
Experimental and Numerical Studies of Tool Wear Processes in the Nibbling Process. [PDF]
Bohdal Ł+5 more
europepmc +1 more source
On the Wear of Carbide Tools in Machining Cast Iron Roll
Ryozo Kitagawa, Kitao Okusa
openalex +2 more sources
Epitaxial piezoelectric α‐quartz/Si BioNEMS sensors, made using soft chemistry, effectively detect the Chikungunya virus. They have a mass sensitivity of 205 pg Hz−1 in liquid and can detect the virus at a limit of 9 ng mL−1. This development enables high‐frequency mass devices for point‐of‐care testing in healthcare and other electronic applications ...
Raissa Rathar+12 more
wiley +1 more source
DeepTool: A deep learning framework for tool wear onset detection and remaining useful life prediction. [PDF]
Kamat P, Kumar S, Kotecha K.
europepmc +1 more source
Machine Learning Approaches for Monitoring of Tool Wear during Grey Cast-Iron Turning. [PDF]
Tabaszewski M+5 more
europepmc +1 more source
LipoGels: Robust Self‐Lubricating Physically Cross‐Linked Alginate Hydrogels Embedded with Liposomes
Physically cross‐linked alginate hydrogels embedded with 1,2‐dipalmitoyl‐sn‐glycero‐3‐phosphocholine liposomes (LipoGels) are prepared under optimized conditions to avoid shrinkage and achieve structural uniformity. LipoGels demonstrate robust mechanical strength (Young's modulus ≈1 MPa), excellent lubrication (friction coefficient ≈0.021), and ...
Tao Ma+4 more
wiley +1 more source
Characterizing the tool wear morphologies and life in milling A520-10%SiC under various lubrication and cutting conditions. [PDF]
Saberi M, Niknam SA, Hashemi R.
europepmc +1 more source
Tool Wear Effect on Surface Integrity in AISI 1045 Steel Dry Turning. [PDF]
Magalhães LC+5 more
europepmc +1 more source