Results 61 to 70 of about 5,320,548 (290)
A GAN-Based Multi-Sensor Data Augmentation Technique for CNC Machine Tool Wear Prediction
IEEE Access, 2023 The prediction of CNC machine tool wear is limited due to the scarcity of data in industry. A sufficient amount of experimental and real-live factory data is missing to train accurate supervised machine learning prediction models.
Yuechi Jiang +2 more
doaj +1 more source
Arthritis Care &Research, EarlyView.Objective Estimating the incidence and prevalence of symptomatic hand osteoarthritis (OA) in the Dutch population using a validated algorithm that integrates free‐text data from primary care electronic health records (EHRs). Methods This retrospective cohort study used the Integrated Primary Care Information database, including EHRs from approximately ...
Onur Kaya +7 more
wiley +1 more source
Arthritis Care &Research, Accepted Article.Objectives This study synthesised the content and reporting completeness of published physical therapist‐led interventions for glenohumeral osteoarthritis (GHOA). Methods This systematic review undertook electronic database searches in PubMed, EMBASE, Cochrane, CINAHL and PEDro (until June 2025) for any peer‐reviewed articles/studies describing ...
Daha G Muhammad +5 more
wiley +1 more source
Analysis of Tool Wear in GH4169 Material Milling Process
Lubricants, 2023 Nickel-based superalloy GH4169 is a material with strong mechanical properties and is difficult to process. In order to reduce tool wear during material processing and improve the workpiece surface processing quality, based on the finite element ...
Xueguang Li +3 more
doaj +1 more source
Adaptive Foam 3D Printing of Ultralight and Multifunctional Materials
Advanced Engineering Materials, EarlyView.Adaptive foam 3D printing, enabled by expandable microspheres, imparts cellular structures to thermoplastic and thermosetting polymers, manufactured through a variety of processes including fused filament fabrication, direct ink writing, digital light processing, and inkjet printing.
Nariman Rajabifar, Amir Ameli
wiley +1 more source
Journal of the Japan Society of Precision Engineering, 1985 This paper describes details of a prediction system of tool wear. The system is based on the wear characteristic equation and the three-dimensional cutting model relating to formation of a lateral curl of chip which have been proposed in the previous papers.
Katsuhiro MAEKAWA, Takeaki KITAGAWA
openaire +3 more sources
Micro-Milling Tool Wear Monitoring via Nonlinear Cutting Force Model
Micromachines, 2022 Mechanistic cutting force model has the potential for monitoring micro-milling tool wear. However, the existing studies mainly consider the linear cutting force model, and they are incompetent to monitor the micro-milling tool wear which has a ...
Tongshun Liu, Qian Wang, Weisu Wang
doaj +1 more source
Entropy‐Driven Design of Low‐Melting‐Point Alloys via Compositionally Complex Strategy
Advanced Engineering Materials, EarlyView.Conventional low‐melting‐point alloys (LMPAs) are limited by a narrow compositional space and inherent property trade‐offs. This review presents an entropy‐driven design strategy that overcomes these limitations, ushering in a new class of low‐melting‐point compositionally complex alloys (LMCCAs).
Yinghui Shang +6 more
wiley +1 more source
Applied Sciences, 2023 Real-time tool condition monitoring (TCM) is becoming more and more important to meet the increased requirement of reducing downtime and ensuring the machining quality of manufacturing systems.
Zhimeng Li +5 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.This study examines Invar composites reinforced with titanium carbide (TiC) and titanium nitride (TiN) using laser powder bed fusion (LPBF). It presents the influence of reinforcements on microstructure, tensile properties, and thermal expansion. Results show that TiC effectively strengthens Invar while maintaining low thermal expansion, whereas TiN ...
Ayodeji Nathaniel Oyedeji +3 more
wiley +1 more source