Industry 4.0 is strongly intertwined with big data streaming flows from intelligent sensors and
machinery installed in industrial facilities. Failures can disrupt production and lead the …

Time series prediction stands at the forefront of the fourth industrial revolution (Industry 4.0),
offering a crucial analytical tool for the vast data streams generated by modern industrial …

This study examined the efficacy of artificial intelligence (AI) technologies in predictive risk
assessment and their contribution to ensuring business continuity. This research aimed to …

Although the applications of artificial intelligence especially deep learning have greatly
improved various aspects of intelligent manufacturing, they still face challenges for broader …

As the global demand for sustainable energy solutions grows, photovoltaic (PV) power
plants are increasingly vital, especially with the integration of innovative technologies like …

In the span of three years, the application of large language models (LLMs) has accelerated
across a multitude of professional sectors. Amid this development, a new collection of …

Timely fault diagnosis is essential to ensure the reliable performance of manufacturing
systems. Aiming at the problems of insufficient prior information and incomplete reliability of …

The accelerated development of smart manufacturing is taking place all over the world, but
the definition of the theoretical foundations of its stimulation, as well as the unequivocal …

Прискорений розвиток смарт-промисловості відбувається в усьому світі, але
визначення теоретичних засад її стимулювання, як і однозначне розуміння самого …

The industrial fault prediction based on time series data inference is a very meaningful work.
Generally, this task has two key difficulties including the limited amount of fault data and …