دانلود رایگان مقاله انگلیسی یادگیری عمیق برای تولید هوشمند: روش ها و کاربردها - الزویر 2018

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.

6. Conclusions

Deep learning provides advanced analytics and offers great potentials to smart manufacturing in the age of big data. By unlocking the unprecedented amount of data into actionable and insightful information, deep learning gives decision-makers new visibility into their operations, as well as real-time performance measures and costs. To facilitate advanced analytics, a comprehensive overview of deep learning techniques is presented with the applications to smart manufacturing. Four typical deep learning models including Convolutional Neural Network, Restricted Boltzmann Machine, Auto Encoder, and Recurrent Neural Network are discussed in detail. The emerging research effort of deep learning in applications of manufacturing is also summarized. Despite of the promising results reported so far, there are still some limitations and significant challenges for further exploration. As the evolution of computing resources (e.g., cloud computing [119–124], fog computing [125,126], etc.), computational intelligence including deep learning may be push into cloud, enabling more convenient and on-demand computing services for smart manufacturing.