With the increasing demand of customisation and high-quality products, it is necessary for

the industries to digitize the processes. Introduction of computers and Internet of things

(IoT) devices, the processes are getting evolved and real time monitoring is got easier.

With better monitoring of the processes, accurate results are being produced and accurate

losses are being identified which in turn helps increasing the productivity. This introduction

of computers and interaction as machines and computers is the latest industrial revolution

known as Industry 4.0, where the organisation has the total control over the entire value chain

of the life cycle of products. But it still remains a mere idea but an achievable one where IoT,

big data, smart manufacturing and cloud-based manufacturing plays an important role. The

difference between 3rd industrial revolution and 4th industrial revolution is that, Industry

4.0 also integrates human in the manufacturing process. The paper discusses about the

different ways to implement the concept and the tools to be used to do the same.

One of the most critical problems in all practical systems is the presence of uncertainties, internal and external disturbances, as well as disturbing noise, which makes the control of the system a challenging task. Another challenge with the physical systems is the possibility of cyber-attacks that the system’s cyber security against them is a critical issue. The systems related to oil and gas industries may also be subjected to cyber-attacks. The subsets of these industries can be mentioned to the oil and gas transmission industry, where ships have a critical role. This paper uses the Quantitative Feedback Theory (QFT) method to design a robust controller for the ship course system, aiming towards desired trajectory tracking. The proposed controller is robust against all uncertainties, internal and external disturbances, noise, and various possible Deception, Stealth, and Denial-of-Service (DOS) attacks. The robust controller for the ship system is designed using the QFT method and the QFTCT toolbox in MATLAB software. Numerical simulations are performed in MATLAB/Simulink for two case studies with disturbances and attacks involving intermittent sinusoidal and random behavior to demonstrate the proposed controller.

The new industrial era, industry 4.0, leans on Cyber Physical Systems CPS. It is an emergent approach of Production System design that consists of the intimate integration between physical processes and information computation and communication systems. The CPSs redefine the decision-making process in shop floor level to reach an intelligent shop floor control. The scheduling is one of the most important shop floor control functions. In this paper, we propose a cooperative scheduling based on multi-agents modelling for Cyber Physical Production Systems. To validate this approach, we describe a use case in which we implement a scheduling module within a flexible machining cell control tool.

The dynamically changing environment forces companies to introduce changes in production processes and the need for employees to adapt quickly to new tasks. Therefore, it is expected to implement solutions to support employees. The system that will manage the work on a manufacturing line should work in real time to support the ongoing activities and, to be implemented in SMEs, must not be expensive. The authors identified important system components and expected functionalities. The methodology of the work is based on humancentered design. A concept of a cyber-physical system is proposed. The aim of the proposed edge computing-based system is to manage the work on the manufacturing line in which certain elements communicate with each other to achieve common goals. The paper presents what the system can consist of, how information and knowledge are managed in the system, and what can be the benefits for enterprises from its implementation.

The integration of the internet of things (IoT) and cyber physical network into the battery charging station system is critical to the success and long-term viability of the vehicle to grid (V2G) trend for future automobiles in terms of environmental and energy sustainability. The goal of this article is to create a V2G battery charging station concept using the internet of things (IoT) and a cyber physical network system. The V2G charging station concept was developed with the idea that every charging electric vehicle (EV) can communicate and coordinate with the charging station's control center, which includes a cyber physical system that addresses privacy and security concerns. The communication protocol must also be considered by the charging station. The preliminary test has been taken into consideration. Normal hours (for case one), peak hours (for case two), and valley hours (for case three), respectively, were created as charging circumstances for EVs at charging stations. Simulations were run for each of the three case scenarios. Each EV's battery state of charge (SoC) is provided a 50 percent initial charge and user-defined SoC restrictions. The MATLAB/SIMULINK platform was used to run the case simulations. The grid frequency, charging station output power, and the EV's battery SoC were all observed during the 24- hour simulation. As a result, the developed V2G charging station concept can regulate its input and output power depending on the battery status of the EVs inside the charging station, as well as provide frequency regulation service to the grid while meeting the energy demand of EV customers.

By reviewing the current state of the art, this paper opens a Special Section titled “The Internet of Things and AI-driven optimization in the Industry 4.0 paradigm”. The topics of this section are part of the broader issues of integration of IoT devices, cloud computing, big data analytics, and artificial intelligence to optimize industrial processes and increase efficiency. It also focuses on how to use modern methods (i.e. computerization, robotization, automation, machine learning, new business models, etc.) to integrate the entire manufacturing industry around current and future economic and social goals. The article presents the state of knowledge on the use of the Internet of Things and optimization based on artificial intelligence within the Industry 4.0 paradigm. The authors review the previous and current state of knowledge in this field and describe known opportunities, limitations, directions for further research, and industrial applications of the most promising ideas and technologies, considering technological, economic, and social opportunities.

The authors update the issue disassembly-free control and correction of all components of the error of measuring channels with multi-bit analog-to-digital converters (ADCs). The main disadvantages of existing methods for automatic control of the parameters of multi-bit ADCs, in particular their nonlinearity, are identified. Methods for minimizing instrumental errors and errors caused by limited internal resistances of closed switches, input and output resistances of active elements are investigated. The structures of devices for determining the multiplicative and nonlinear components of the error of multi-bit ADCs based on resistive dividers built on single-nominal resistors are proposed and analyzed. The authors propose a method for the correction of additive, multiplicative and nonlinear components of the error at each of the specified points of the conversion range during non-disassembly control of the ADC with both types of inputs. The possibility of non-disassembly control, as well as correction of multiplicative and nonlinear components of the error of multi-bit ADCs in the entire range of conversion during their on-site control is proven. ADC error correction procedures are proposed. These procedures are practically invariant to the non-informative parameters of active structures with resistive dividers composed of single-nominal resistors. In the article the prospects of practical implementation of the method of error correction during non-dismantling control of ADC parameters using the possibilities provided by modern microelectronic components are shown. The ways to minimize errors are proposed and the requirements to the choice of element parameters for the implementation of the proposed technical solutions are given. It is proved that the proposed structure can be used for non-disassembly control of multiplicative and nonlinear components of the error of precision instrumentation amplifiers.