Prediction of the power supplied in friction-based joining process of metal-polymer hybrids through machine learning

2021 ◽  
Vol 68 ◽  
pp. 750-760
Author(s):  
F. Lambiase ◽  
V. Grossi ◽  
S.I. Scipioni ◽  
A. Paoletti
Keyword(s):  
Machine Learning ◽  
Polymer Hybrids ◽  
Joining Process ◽  
Metal Polymer

Hierarchical Metal–Polymer Hybrids for Enhanced CO 2 Electroreduction

2021 ◽  
Vol 133 (19) ◽  
pp. 11072-11077
Author(s):  
Shuaiqiang Jia ◽  
Qinggong Zhu ◽  
Mengen Chu ◽  
Shitao Han ◽  
Ruting Feng ◽  
...  
Keyword(s):  
Polymer Hybrids ◽  
Metal Polymer

Inprozess-Dichtheitsprüfung in der Montage/In-process leak testing in assembly

2021 ◽  
Vol 111 (09) ◽  
pp. 650-653
Author(s):  
Rainer Müller ◽  
Anne Blum ◽  
Steffen Klein ◽  
Tizian Schneider ◽  
Andreas Schütze ◽  
...  
Keyword(s):  
Machine Learning ◽  
Added Value ◽  
Leak Test ◽  
Learning Methods ◽  
Machine Learning Methods ◽  
Complex Interactions ◽  
Leak Testing ◽  
Joining Process

In diesem Beitrag wird ein Fügeprozess mittels sensitiver Robotik vorgestellt, bei dem gleichzeitig eine Inprozess-Dichtheitsprüfung durch Methoden des maschinellen Lernens erfolgt. Dabei werden komplexe Wirkzusammenhänge in den Daten extrahiert und Informationen über die Qualität eines zu montierenden Produkts gewonnen. Durch die Kombination eines Füge- und Prüfprozesses wird die Wertschöpfung einzelner Prozesse gesteigert, wodurch eine zeitaufwendige End-of-Line-Prüfung entfallen kann.   In this paper, a joining process using sensitive robotics is introduced, in which an in-process leak test is performed at the same time using machine learning methods. Complex interactions in the data are extracted and information about the quality of a product to be assembled is obtained. By combining a joining and testing process, the added value of individual processes is increased, which eliminates the need for time-consuming end-of-line testing.

Hierarchical Metal–Polymer Hybrids for Enhanced CO 2 Electroreduction

2021 ◽  
Vol 60 (19) ◽  
pp. 10977-10982
Author(s):  
Shuaiqiang Jia ◽  
Qinggong Zhu ◽  
Mengen Chu ◽  
Shitao Han ◽  
Ruting Feng ◽  
...  
Keyword(s):  
Polymer Hybrids ◽  
Metal Polymer

D32 Relationship between Strength of Metal/Polymer Hybrids and Manufacturing Conditions

2014 ◽  
Vol 2014.10 (0) ◽  
pp. 253-254
Author(s):  
Fuminobu Kimura ◽  
Shotaro Kadoya ◽  
Yusuke Kajihara
Keyword(s):  
Polymer Hybrids ◽  
Metal Polymer

scholarly journals Laser Ablation of Titanium Alloy (Ti64): Effects of Process Parameters on Performance of Laser Welded Ti64 – Polyamide 6.6 Joints.

2021 ◽  
Author(s):  
Adham Al-Sayyad ◽  
Farah Salah ◽  
Julien Bardon ◽  
Pierre Hirchenhahn ◽  
Lamia Shihata ◽  
...  
Keyword(s):  
Titanium Alloy ◽  
Laser Ablation ◽  
Titanium Surface ◽  
Process Window ◽  
Welding Quality ◽  
Optimal Parameters ◽  
Joint Resistance ◽  
Polyamide 6.6 ◽  
Joining Process ◽  
Metal Polymer

Abstract Laser welding of metals – polymers has gained strong scientific and industrial interest because of its ability to produce miniaturized joints in lightweight products with customized properties. Surface pretreatments before joining process have shown significant impact on enhancing properties of laser welded metal – polymer joints. This work adopts a Design of Experiments (DoE) approach to investigate the influence of titanium alloy (Ti64) laser ablation parameters on the performance of laser welded Ti64 – polyamide (PA6.6) assemblies. In this first study, significant laser ablation parameters were highlighted, process window outlined, and optimal parameters identified. Laser ablation pretreatment parameters demonstrated a strong influence on joint resistance to failure. Effects of laser ablation parameters on titanium surface morphology were analyzed using Scanning Electron Microscope (SEM). In a second study, the effects of ablation parameters on Ti64 surface properties and welding quality will be investigated.

Sign in / Sign up

Export Citation Format

Share Document