Results 101 to 110 of about 5,074,594 (286)

An FEM-based approach for tool wear estimation in machining

, 2016
This study presents an FEM-based approach to predict the rate of flank wear evolution for uncoated cemented carbide tools in longitudinal turning processes. This novel approach combines the concept of experimental design and Response Surface Methodology (
Gruber, Hans, Sadik, Ibrahim,, Nyborg, Lars, Nyborg, Lars,, Malakizadi, Amir,, Sadik, Ibrahim, Gruber, Hans,, Malakizadi, Amir   +7 more
core   +1 more source

A Geometrically Transient Platform for Bioelectronic Implants

Advanced Materials, EarlyView.
Minimally invasive bioelectronic implants often compromise performance for smaller sizes. To resolve this optimization dilemma, a wireless bioelectronic implant with a transient geometry is introduced (MiFi). The origami‐inspired device miniaturizes up to sixfold for syringe insertion and autonomously unfolds post‐implantation.
Selin Olenik, John D. Goodwin, Atharv Naik, Philip Coatsworth, Ioi Chit Cheung, Farbod Amirghasemi, Anies Sohi, Ehsan Abedi, Tayeb Tadlaoui, Maral P. S. Mousavi, Andriy S. Kozlov, Victoria Salem, Andrew S. Cowburn, Firat Guder   +13 more
wiley   +1 more source

Prediction of wheel profile wear and crack growth - comparisons with measurements

, 2016
A model which can predict the length of the surface crack and crack depth in rails was developed in a previous study by the authors B. Dirks, R. Enblom, A. Ekberg, M. Berg (2015) [].
Berg, Mats,, Enblom, Roger,, Dirks, Babette,   +2 more
core   +1 more source

Autonomous Folding of Soft Matter From Living Polymers

Advanced Materials, EarlyView.
Origami structures are endowed with “living” polymer creases that grow, remodel, and stiffen in response to nutrient solutions. This post‐fabrication growth enables autonomous folding, iterative regrowth, and mechanical tuning involving origami assemblies, such as cranes, Miura‐ori tessellations, rigid and non‐rigid square‐twist patterns, establishing ...
Jiahe Huang, Tuo Zhao, Shixi Zang, Deep Malu, Huajian Ji, Glaucio H. Paulino, Yuhang Hu   +6 more
wiley   +1 more source

Development of tool life prediction system for square end-mills based on database of servo motor current value

Journal of Advanced Mechanical Design, Systems, and Manufacturing
Accurate prediction of tool life is crucial for reducing production costs and enhancing quality in the machining process. However, such predictions often rely on empirical knowledge, which may limit inexperienced engineers to reliably obtain accurate ...
Hiroyuki KODAMA, Makoto SUZUKI, Kazuhito OHASHI   +2 more
doaj   +1 more source

Soft Skins With Reversible Thickness Morphing: Materials, Mechanisms, and Applications

Advanced Materials, EarlyView.
Evolution of electronic skin (e‐skin) technologies toward adaptive, multifunctional soft skins. Phase I highlights early rigid and discrete sensory interfaces. Phase II shows the transition toward flexible, stretchable, and large‐area e‐skin. Phase III captures the emergence of computational e‐skin.
Oliver Ozioko, Chiamaka Akah, Ravinder Dahiya   +2 more
wiley   +1 more source

Experimental Study of the Wear of Diamond Coated Micro End Mills [PDF]

, 2010
The demand for the miniaturization of complex components has led to the growth of manufacturing methods capable of producing truly three dimensional parts using traditional en-gineering materials with favorable mechanical properties.
Sumant, Anirudha V., Torres, Christopher D., Boyat, Alexandra M., Carpick, Robert W., Pfefferkorn, Frank E., Adiga, Vivekananda P.   +5 more
core  

Designing an Artificial Neural Network Based Model for Online Prediction of Tool Life in Turning [PDF]

International Journal of Advanced Design and Manufacturing Technology, 2015
Artificial neural network is one of the most robust and reliable methods in online prediction of nonlinear incidents in machining. Tool flank wear as a tool life criterion is an important task which is needed to be predicted during machining processes to
A. Salimiasl, A. Özdemir, I. Safarian
doaj  

Data‐Driven Materials Science for Energy‐Sustainable Applications

Advanced Materials, EarlyView.
Data‐driven approaches powered by artificial intelligence are transforming materials discovery for energy sustainability. This review examines how auto‐generated high‐quality materials databases and domain‐specific language models accelerate research in photovoltaics, thermoelectrics, batteries and magnetic materials. Applications involve extraction of
Jacqueline M. Cole
wiley   +1 more source

Milling-Force Prediction Model for 304 Stainless Steel Considering Tool Wear

Machines
The high-performance alloy, 304 stainless steel, is widely used in various industries. However, its material properties lead to severe tool wear during milling processes, significantly increasing milling force and adversely impacting machining quality ...
Changxu Wang, Yan Li, Feng Gao, Kejun Wu, Kan Yin, Peng He, Yunjiao Xu   +6 more
doaj   +1 more source