Semantic Scholar Open Access 2018 1464 sitasi

Deep learning for smart manufacturing: Methods and applications

Jinjiang Wang Yulin Ma Laibin Zhang R. Gao Dazhong Wu

Abstrak

Abstract Smart manufacturing refers to using advanced data analytics to complement physical science for improving system performance and decision making. With the widespread deployment of sensors and Internet of Things, there is an increasing need of handling big manufacturing data characterized by high volume, high velocity, and high variety. Deep learning provides advanced analytics tools for processing and analysing big manufacturing data. This paper presents a comprehensive survey of commonly used deep learning algorithms and discusses their applications toward making manufacturing “smart”. The evolvement of deep learning technologies and their advantages over traditional machine learning are firstly discussed. Subsequently, computational methods based on deep learning are presented specially aim to improve system performance in manufacturing. Several representative deep learning models are comparably discussed. Finally, emerging topics of research on deep learning are highlighted, and future trends and challenges associated with deep learning for smart manufacturing are summarized.

Topik & Kata Kunci

Computer Science

Penulis (5)

Jinjiang Wang

Yulin Ma

Laibin Zhang

R. Gao

Dazhong Wu

Format Sitasi

APA MLA BibTeX

Wang, J., Ma, Y., Zhang, L., Gao, R., Wu, D. (2018). Deep learning for smart manufacturing: Methods and applications. https://doi.org/10.1016/J.JMSY.2018.01.003

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Informasi Jurnal

Tahun Terbit: 2018
Bahasa: en
Total Sitasi: 1464×
Sumber Database: Semantic Scholar
DOI: 10.1016/J.JMSY.2018.01.003
Akses: Open Access ✓