Challenges and Opportunities for Deep Learning Applications in Industry 4.0

Challenges and Opportunities for Deep Learning Applications in Industry 4.0

Author(s): Nipun R. Navadia*, Gurleen Kaur, Harshit Bhadwaj, Taranjeet Singh, Yashpal Singh, Indu Malik, Arpit Bhardwaj and Aditi Sakalle

Pp: 1-24 (24)

DOI: 10.2174/9789815036060122010003

* (Excluding Mailing and Handling)


Manufacturing plays a prominent role in the development and economic growth of countries. A dynamic shift from a manual mass production model to an integrated automated industry towards automation includes several stages. Along with the boost in the economy, manufacturers also face several challenges, including several aspects. Machine Learning can prove to be an essential tool and optimize the production process, respond quickly to the changes and market demand respectively, predict certain aspects of the particular industry to improve performance, maintain machine health and other aspects. Machine Learning technology can prove its effectiveness when applied to a specific issue in the sector— such as filtering out the primary use cases of Machine Learning manufacturing specifically, 'Predictive quality and yield' and 'Predictive maintenance.' Supervised Machine Learning and Unsupervised Machine Learning may provide the accuracy to predict the outputs and the underlying patterns.

Keywords: Artificial Intelligence, Instance-Based Learning, Intelligent Manufacturing System, Machine Learning, Manufacturing

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