Deep Learning For Smart Manufacturing: Methods And Applications

Keywords

Computational intelligence; Data analytics; Deep learning; Smart manufacturing

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.

Publication Date

7-1-2018

Publication Title

Journal of Manufacturing Systems

Volume

48

Number of Pages

144-156

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.jmsy.2018.01.003

Socpus ID

85044519534 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85044519534

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