Artificial Intelligence and Smart Machine Learning: Progress, Trends and Directions

Abstract

Adaptation and innovation stand as critical
pillars for the manufacturing industry's evolution,
particularly in achieving sustainable practices through the
integration of new technologies. To advance
sustainability goals, the implementation of smart
production necessitates a global perspective on the
application of smart production technologies. In this
context, the extensive research endeavors in artificial
intelligence (AI) have yielded various AI-based
techniques, notably machine learning, which have found
traction in the industry, facilitating sustainable
manufacturing practices. Consequently, the primary
objective of this research was to systematically analyze
the scientific literature concerning the utilization of
artificial intelligence and machine learning (ML) within
the industrial domain. Indeed, with the advent of Industry
4.0, artificial intelligence and machine learning emerge as
pivotal drivers of the smart factory revolution. This
review aims to categorize the literature based on
publication year, authors, scientific sector, country,
institution, and keywords. The analysis was conducted
utilizing data from the Web of Science and SCOPUS
databases.