期刊


ISSN0956-5515
刊名Journal of Intelligent Manufacturing
参考译名智能化制造业杂志
收藏年代1999～2024



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2005 2006 2007 2008 2009 2010
2011 2012 2013 2014 2015 2016
2017 2018 2019 2020 2021 2022
2023 2024

2024, vol.35, no.1 2024, vol.35, no.2 2024, vol.35, no.3 2024, vol.35, no.4 2024, vol.35, no.5 2024, vol.35, no.6

题名作者出版年年卷期
Production quality prediction of cross-specification products using dynamic deep transfer learning networkWang, Pei; Wang, Tao; Yang, Sheng; Cheng, Han; Huang, Pengde; Zhang, Qianle20242024, vol.35, no.6
A novel interpretable predictive model based on ensemble learning and differential evolution algorithm for surface roughness prediction in abrasive water jet polishingXie, Shutong; He, Zongbao; Loh, Yee Man; Yang, Yu; Liu, Kunhong; Liu, Chao; Cheung, Chi Fai; Yu, Nan; Wang, Chunjin20242024, vol.35, no.6
Applying machine learning to wire arc additive manufacturing: a systematic data-driven literature reviewHamrani, Abderrachid; Agarwal, Arvind; Allouhi, Amine; McDaniel, Dwayne20242024, vol.35, no.6
Deviation compensation in LPBF series production via statistical predeformation and structural pattern analysisLechner, Philipp; Hartmann, Christoph; Wolf, Daniel; Habiba, Abdelrahman20242024, vol.35, no.6
Equipment electrocardiogram (EECG): making intelligent production line more robustChen, Baotong; Wang, Lei; Yu, Shujun; Wan, Jiafu; Xia, Xuhui20242024, vol.35, no.6
Swarm intelligence-based framework for accelerated and optimized assembly line design in the automotive industryEl Houd, Anass; Piranda, Benoit; De Matos, Raphael; Bourgeois, Julien20242024, vol.35, no.6
Smart scheduling of dynamic job shop based on discrete event simulation and deep reinforcement learningWang, Ziqing; Liao, Wenzhu20242024, vol.35, no.6
Image deep learning in fault diagnosis of mechanical equipmentWang, Chuanhao; Sun, Yongjian; Wang, Xiaohong20242024, vol.35, no.6
Evaluation of process planning in manufacturing by a neural network based on an energy definition of hopfield netsSpoor, Jan Michael; Weber, Jens20242024, vol.35, no.6
SSMSPC: self-supervised multivariate statistical in-process control in discrete manufacturing processesBiegel, Tobias; Helm, Patrick; Jourdan, Nicolas; Metternich, Joachim20242024, vol.35, no.6
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