The Duo of Artificial Intelligence and Big Data for Industry 4.0: Review of Applications, Techniques, Challenges, and Future Research Directions

TL;DR

This paper reviews how AI and Big Data technologies are transforming Industry 4.0 by enabling smart manufacturing, discussing applications, techniques, challenges, and future research directions for deployment and advancement.

Contribution

It provides a comprehensive overview of AI and Big Data integration in Industry 4.0, highlighting key applications, challenges, and future research pathways for Industry 5.0.

Findings

AI and Big Data significantly enhance Industry 4.0 applications.

Major challenges include data availability, bias, security, and interpretability.

The review sets a baseline for future research in smart manufacturing technologies.

Abstract

The increasing need for economic, safe, and sustainable smart manufacturing combined with novel technological enablers, has paved the way for Artificial Intelligence (AI) and Big Data in support of smart manufacturing. This implies a substantial integration of AI, Industrial Internet of Things (IIoT), Robotics, Big data, Blockchain, 5G communications, in support of smart manufacturing and the dynamical processes in modern industries. In this paper, we provide a comprehensive overview of different aspects of AI and Big Data in Industry 4.0 with a particular focus on key applications, techniques, the concepts involved, key enabling technologies, challenges, and research perspective towards deployment of Industry 5.0. In detail, we highlight and analyze how the duo of AI and Big Data is helping in different applications of Industry 4.0. We also highlight key challenges in a successful deployment of AI and Big Data methods in smart industries with a particular emphasis on data-related issues, such as availability, bias, auditing, management, interpretability, communication, and different adversarial attacks and security issues. In a nutshell, we have explored the significance of AI and Big data towards Industry 4.0 applications through panoramic reviews and discussions. We believe, this work will provide a baseline for future research in the domain.