Results 41 to 50 of about 2,894,071 (294)

Big Data Disruptions. How Industrie 4.0 will Impact Industrial Robotics

, 2015
In the presentation BIG DATA DISRUPTIONS: HOW INDUSTRIE 4.0 WILL IMPACT INDUSTRIAL ROBOTICS Thomas Bauernhansl explains why robots will be the future tool for personalized production.
Bauernhansl, Thomas
core   +1 more source

A Novel Approach to Estimate the Transition Temperature via Dynamic Nanoindentation

Advanced Engineering Materials, EarlyView.
A new dynamic nanoindentation‐based method was developed that uses the stiffness ratio as an indicator of the elastic–plastic deformation contributions at different temperatures. The approach successfully identified transition temperatures in ferritic steel and distinguished them from continuously ductile austenitic steel.
Stefan Zeiler, Nikolaus Kostwein, Ronald Schnitzer, Christian Mitterer, Verena Maier‐Kiener   +4 more
wiley   +1 more source

Enabling Fog-based Industrial Robotics Systems

, 2020
Low latency and on demand resource availability enable fog computing to host industrial applications in a cloud like manner. One industrial domain which stands to benefit from the advantages of fog computing is robotics.
Nolte, Thomas,, Papadopoulos, Alessandro,, Venito, Alexandre,, Desai, Nitin,, Salman Shaik, Mohammad,, Schulte, Stefan,, Bakhshi Valojerdi, Zeinab,, Karagiannis, Vasileios,, Struhar, Vaclav,, Dao, Van-Lan,   +9 more
core   +1 more source

Rotary 3D Printing With Integrated Electroplating

Advanced Engineering Materials, EarlyView.
A rotary material extrusion platform integrates localized copper electroplating with printing and encapsulation to fabricate cylindrical polymer–metal structures containing fully embedded, low‐resistance conductive pathways that enable internal Joule heating and thermally activated shape‐memory responses.
Antonio Zagaria, Nicola Larovere, Moslem Mohammadi, Gianluca Percoco, Ali Zolfagharian, Gianni Stano   +5 more
wiley   +1 more source

Exploring the Impact of Robotics on Industrial Automation and Society

, 2023
Exploring the Impact of Robotics on Industrial Automation and ...
John A. Smith
core   +1 more source

Impact of the Process Atmosphere During Hot Isostatic Pressing on the Near‐Surface Composition of an Additively Manufactured Austenitic High‐Interstitial Steel

Advanced Engineering Materials, EarlyView.
A high interstital austenitic steel is additively manufactured and postdensified by HIP to eliminate gas porosity. Thereby, the loss of N and Mn in Ar HIP atmosphere is investigated. Further, HIP using N2 atmosphere is investigated which led to excessive nitride formation.
F. Großwendt, J. Hahn, J. Kimm, S. Weber, J. Lentz   +4 more
wiley   +1 more source

Mitigating Creep Anisotropy and Enhancing Performance in Additively Manufactured Ni‐Based Superalloys: A Review

Advanced Engineering Materials, EarlyView.
Additive manufacturing introduces pronounced microstructural and crystallographic anisotropy in Ni‐based superalloys, resulting in orientation‐dependent creep deformation and damage. This review identifies the key microstructural origins of creep anisotropy, examines their influence on dominant deformation mechanisms, and highlights processing ...
Chandan Kumar, Shobhit Pratap Singh, Gaurav Mohanty, Praveen Kumar   +3 more
wiley   +1 more source

Robotic Industrialization [PDF]

, 2015
In this volume, concepts, technologies and developments in the field of building-component manufacturing - based on concrete, brick, wood and steel as building materials and on large-scale prefabrication, delivering complex, customized components and products - are introduced and discussed.
Thomas Bock, Thomas Linner
openaire   +1 more source

AI and blockchain applications in industrial robotics

, 2023
The ever-evolving industrial landscape poses challenges for businesses, particularly in the field of robotics. Performance optimization, data security, and harnessing emerging technologies are crucial for staying competitive.
Tabassum N., Biradar R. C., Hegde N., Geetha D., Lazarescu M.   +4 more
core   +1 more source

Investigation of Resonance Characteristics of More Than 10 000 Metal‐Coated Silicon MEMS Cantilevers Using Machine Learning

Advanced Engineering Materials, EarlyView.
More than 10 000 metal‐coated silicon MEMS cantilevers are fabricated and characterized to build a large‐scale experimental dataset spanning multiple vibrational modes. Machine learning algorithms are benchmarked to predict resonance frequency and quality factor, with ensemble based models achieving accuracy approaching experimental uncertainty.
Sina Zare Pakzad, Saurabh Thorat, Andre Loch Gesing, Dominik Huber, Christopher Zellner, Patrick Egger, Georg Pfusterschmied, Ulrich Schmid, Michael Schneider   +8 more
wiley   +1 more source