Machine learning and deep learning based predictive quality in manufacturing: a systematic review (English)
Free access
- New search for: Tercan, Hasan
- Further information on Tercan, Hasan:
- https://orcid.org/0000-0003-0080-6285
- New search for: Meisen, Tobias
- New search for: Tercan, Hasan
- Further information on Tercan, Hasan:
- https://orcid.org/0000-0003-0080-6285
- New search for: Meisen, Tobias
In:
Journal of Intelligent Manufacturing
;
33
, 7
; 1879-1905
;
2022
-
ISSN:
- Article (Journal) / Electronic Resource
-
Title:Machine learning and deep learning based predictive quality in manufacturing: a systematic review
-
Contributors:Tercan, Hasan ( author ) / Meisen, Tobias ( author )
-
Published in:Journal of Intelligent Manufacturing ; 33, 7 ; 1879-1905
-
Publisher:
- New search for: Springer US
- New search for: Springer Science + Business Media B.V
-
Place of publication:Dordrecht [u.a.]
-
Publication date:2022
-
ISSN:
-
ZDBID:
-
DOI:
-
Type of media:Article (Journal)
-
Type of material:Electronic Resource
-
Language:English
- New search for: 52.72
- Further information on Basic classification
-
Keywords:
-
Classification:
BKL: 52.72 Fertigungsautomatisierung -
Source:
Table of contents – Volume 33, Issue 7
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
- 1879
-
Machine learning and deep learning based predictive quality in manufacturing: a systematic reviewTercan, Hasan / Meisen, Tobias et al. | 2022
- 1907
-
Model predictive force control in milling based on an ensemble Kalman filterSchwenzer, Max / Stemmler, Sebastian / Ay, Muzaffer / Rüppel, Adrian Karl / Bergs, Thomas / Abel, Dirk et al. | 2022
- 1921
-
A virtual sensor for backlash in robotic manipulatorsGiovannitti, Eliana / Nabavi, Sayyidshahab / Squillero, Giovanni / Tonda, Alberto et al. | 2022
- 1939
-
Switching strategy-based hybrid evolutionary algorithms for job shop scheduling problemsMahmud, Shahed / Chakrabortty, Ripon K. / Abbasi, Alireza / Ryan, Michael J. et al. | 2022
- 1967
-
Hybrid prediction-optimization approaches for maximizing parts density in SLM of Ti6Al4V titanium alloyCosta, A. / Buffa, G. / Palmeri, D. / Pollara, G. / Fratini, L. et al. | 2022
- 1991
-
The use of Fuzzy rule-based systems in the design process of the metallic products on example of microstructure evolution predictionMacioł, Andrzej / Macioł, Piotr et al. | 2022
- 2013
-
Single system for online monitoring and inspection of automated fiber placement with object segmentation by artificial neural networksBrysch, Marco / Bahar, Mohammad / Hohensee, Hans Christoph / Sinapius, Michael et al. | 2022
- 2027
-
Understanding unforeseen production downtimes in manufacturing processes using log data-driven causal reasoningHagedorn, Christopher / Huegle, Johannes / Schlosser, Rainer et al. | 2022
- 2045
-
Process optimization via confidence region: a case study from micro-injection moldingTrotta, Gianluca / Cacace, Stefania / Semeraro, Quirico et al. | 2022
- 2059
-
A hybrid genetic algorithm for parallel machine scheduling with setup timesAdan, J. et al. | 2022
- 2075
-
An unsupervised defect detection model for a dry carbon fiber textileSzarski, Martin / Chauhan, Sunita et al. | 2022
- 2093
-
In-process monitoring and prediction of droplet quality in droplet-on-demand liquid metal jetting additive manufacturing using machine learningGaikwad, Aniruddha / Chang, Tammy / Giera, Brian / Watkins, Nicholas / Mukherjee, Saptarshi / Pascall, Andrew / Stobbe, David / Rao, Prahalada et al. | 2022
- 2119
-
A novel tracking system for the iron foundry field based on deep convolutional neural networksBeck, Michael / Layh, Michael / Nebauer, Markus / Pinzer, Bernd R. et al. | 2022
- 2129
-
Capturing and incorporating expert knowledge into machine learning models for quality prediction in manufacturingLink, Patrick / Poursanidis, Miltiadis / Schmid, Jochen / Zache, Rebekka / von Kurnatowski, Martin / Teicher, Uwe / Ihlenfeldt, Steffen et al. | 2022
- 2143
-
Relating wear stages in sheet metal forming based on short- and long-term force signal variationsNiemietz, Philipp / Kornely, Mia J. K. / Trauth, Daniel / Bergs, Thomas et al. | 2022
- 2157
-
Testing the reliability of monocular obstacle detection methods in a simulated 3D factory environmentWenning, Marius / Backhaus, Anton Akira / Adlon, Tobias / Burggräf, Peter et al. | 2022
- 2167
-
A universal method to compare parts from STEP filesOjal, Nishant / Giera, Brian / Devlugt, Kyle T. / Jaycox, Adam W. / Blum, Alexander et al. | 2022
- 2179
-
Optimal droplet transfer mode maintenance for wire + arc additive manufacturing (WAAM) based on deep learningQin, Jian / Wang, Yipeng / Ding, Jialuo / Williams, Stewart et al. | 2022