To facilitate the personalized smart manufacturing paradigm with cognitive automation
capabilities, Deep Reinforcement Learning (DRL) has attracted ever-increasing attention by …

The textile industry is water intensive and discharges numerous coloring compounds into
the water body that depend on the industry's geographical location, the wet processes used …

The transition from manual to autonomous manufacturing processes, which has been
propelled by consecutive industrial revolutions, is concurrently contingent upon …

Home automation is seen as a potential pillar of the smart city revolution that combines
smart mobility, lifestyle and ecosystem governed by intelligent sensors connected to the …

The evolution of manufacturing systems toward Industry 4.0 and 5.0 paradigms has pushed
the diffusion of Machine Learning (ML) in this field. As the number of articles using ML to …

Manufacturing systems consist of a set of interdependent components. However, addressing
the dependence between these components remains a challenge in both maintenance …

In the zinc oxide rotary volatile kiln (ZORVK), an optimal temperature field is essential to
balance the strong conflict between zinc recovery rate and carbon emissions. However, the …

As the need for quickly exploring a textile manufacturing process is increasingly costly along
with the complexity in the process. The development of manufacturing process modeling has …