Abstract Decision Trees (DTs) are predictive models in supervised learning, known not only
for their unquestionable utility in a wide range of applications but also for their interpretability …

The birth of mass production started in the early 1900s. The manufacturing industries were
transformed from mechanization to digitalization with the help of Information and …

In recent years, swarm intelligence algorithms have received extensive attention and
research. Swarm intelligence algorithms are a biological heuristic method, which is widely …

The distribution of the power transformers at a far distance from the electrical plants
represents the main challenge against the diagnosis of the transformer status. This paper …

The increase in cyber-attacks impacts the performance of organizations in the industrial
sector, exploiting the vulnerabilities of networked machines. The increasing digitization and …

This paper introduces a new intelligent integration between an IoT platform and deep
learning neural network (DNN) algorithm for the online monitoring of computer numerical …

This review is dedicated to the advanced applications of robotic technologies in the
industrial field. Robotic solutions in areas with non-intensive applications are presented, and …

Despite interest in opportunities that Industry 4.0 offers for Supply Chain Resilience (SCR),
little is known about the underlying mechanisms for such contributions. The study develops …

Abstract In the “Industry 4.0” era, autonomous and self-adaptive industrial machining attracts
significant attention in professional manufacturing. This trend originates from the rising …

This paper introduces an integrated IoT architecture to handle the problem of cyber attacks
based on a developed deep neural network (DNN) with a rectified linear unit in order to …