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One of the characteristic features of the next-generation of Industry 4.0 is human-centricity, which in turn includes two technological advancements: Artificial Intelligence and the Industrial Metaverse. In this work, we assess the impact that AI played on the advancement of three technologies that emerged to be cornerstones in the fourth generation of industry: intelligent industrial robotics, unmanned aerial vehicles, and additive manufacturing. Despite the significant improvement that AI and the industrial metaverse can offer, the incorporation of many AI-enabled and Metaverse-based technologies remains under the expectations. Safety continues to be a strong factor that limits the expansion of intelligent industrial robotics and drones, whilst Cybersecurity is effectively a major limiting factor for the advance of the industrial metaverse and the integration of blockchains. However, most research works agree that the lack of the skilled workforce will no-arguably be the decisive factor that limits the incorporation of these technologies in industry. Therefore, long-term planning and training programs are needed to counter the upcoming shortage in the skilled workforce.

 

In this work we investigate the electrical properties of phospholipid bilayer membranes (LBMs) formed from phosphatidylserine by analyzing two experimental setups. The Electrochemical Impedance Spectra (EIS) of phosphatidylserine show that a lipid bilayer membrane formed from this phospholipid has an average specific electrical resistance of 3.466 k Ω.cm 2 and an average capacitance of 0.385 µF/cm 2 . Some of the major factors that affect the LBM resistance include electroporation, the method of deposition, and the surface tension in microchannels for supported LBMs. Therefore, wide apertures remain the most accurate method for supporting LBMs. 

A low-cost remote supervisory control capability is added to a packaging process, in which a low-voltage signal is used to communicate between a distant HMI control panel and a PLC network using the AC power line as a communication medium. The network is a star-topology and uses a Mater-slave protocol. Remote Supervisory control is achieved using a user-defined toolbox of control functions. In this system, a Programmable Logic Controller (PLC) is used to control a process and interface with the operator through a Human Machine Interface (HMI) Panel. A star topology ethernet network is used to connect the PLCs and the HMI panel. 

In this paper we demonstrate two applications of a low-cost remote supervisory control and data acquisition system in two models. The first model is demonstrated with a Profibus-DP protocol based system in which a master Programmable Logic Controller (PLC) unit with control inputs and display outputs controls the speed and monitors the overload condition of a DC motor that is connected to a slave PLC in real time. In the upgraded model, a Profinet protocol is used to connect PLCs, and a power-line communication link is used to remotely connect the control HMI to the network. In both models, remote Supervisory control is achieved using user-defined control functions that act altogether as a block-oriented function library or toolbox. High levels of performance are achieved in real time control and data acquisition in both models.