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The purpose of this paper is to describe how emerging open standards are replacing traditional industrial networks. Current industrial Ethernet networks are not interoperable; thus, limiting the potential capabilities for the Industrial Internet of Things (IIoT). There is no forthcoming new generation fieldbus standard to integrate into the IIoT and Industry 4.0 revolution. The open platform communications unified architecture (OPC UA) time-sensitive networking (TSN) is a potential vendor-independent successor technology for the factory network. The OPC UA is a data exchange standard for industrial communication, and TSN is an Institute of Electrical and Electronics Engineers standard for Ethernet that supports real-time behaviour. The merging of these open standard solutions can facilitate cross-vendor interoperability for Industry 4.0 and IIoT products.

A brief review of the history of the fieldbus standards is presented, which highlights the shortcomings for current industrial systems in meeting converged traffic solutions. An experimental system for the OPC UA TSN is described to demonstrate an approach to developing a three-layer factory network system with an emphasis on the field layer.

From the multitude of existing industrial network schemes, there is a convergence pathway in solutions based on TSN Ethernet and OPC UA. At the field level, basic timing measurements in this paper show that the OPC UA TSN can meet the basic critical timing requirements for a fieldbus network.

This paper uniquely focuses on the specific fieldbus standards elements of industrial networks evolution and traces the developments from the early history to the current developing integration in IIoT context.

A cross-domain intelligent software-defined network (SDN) routing method based on a proposed multiagent deep reinforcement learning (MDRL) method is developed.

First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between the root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to acquire global network state information in real time. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a network traffic state prediction mechanism is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time.

Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and open shortest path first (OSPF) routing methods.

Message transmission and message synchronization for multicontroller interdomain routing in SDN have long adaptation times and slow convergence speeds, coupled with the shortcomings of traditional interdomain routing methods, such as cumbersome configuration and inflexible acquisition of network state information. These drawbacks make it difficult to obtain global state information about the network, and the optimal routing decision cannot be made in real time, affecting network performance. This paper proposes a cross-domain intelligent SDN routing method based on a proposed MDRL method. First, the network is divided into multiple subdomains managed by multiple local controllers, and the state information of each subdomain is flexibly obtained by the designed SDN multithreaded network measurement mechanism. Then, a cooperative communication module is designed to realize message transmission and message synchronization between root and local controllers, and socket technology is used to ensure the reliability and stability of message transmission between multiple controllers to realize the real-time acquisition of global network state information. Finally, after the optimal intradomain and interdomain routing paths are adaptively generated by the agents in the root and local controllers, a prediction mechanism for the network traffic state is designed to improve awareness of the cross-domain intelligent routing method and enable the generation of the optimal routing paths in the global network in real time. Experimental results show that the proposed cross-domain intelligent routing method can significantly improve the network throughput and reduce the network delay and packet loss rate compared to those of the Dijkstra and OSPF routing methods.

One of the most hyped concepts in the manufacturing industry is ‘Industry 4.0’. The ‘Industry 4.0’ concept is grabbing the attention of every manufacturing industry across the globe because of its immense applications. This phenomenon is an advanced version of Industry 3.0, combining manufacturing processes and the latest Internet of Things (IoT) technologies. The main advantage of this paradigm shift is efficiency and efficacy in the manufacturing process with the help of advanced automated technologies. The concept of ‘Industry 4.0’ is contemporary, so it falls under exploratory study. Therefore, the research methodology is thematic narration grounded on secondary data (online) analysis. In this light, this chapter aims to explain ‘Industry 4.0’ in terms of concepts, theories and models based on the Web of Science (WoS) database. The data include research manuscripts, book chapters, blogs, white papers, news items and proceedings. The study details the latest technologies behind the ‘Industry 4.0’ phenomenon, different business intelligence technologies and their practical implications in some manufacturing industries. This chapter mainly elaborates on Industry 4.0 frameworks designed by (1) PwC (2) IBM (3) Frost & Sullivan.

This paper aims to improve the kinematic modeling accuracy of a spatial three-degrees-of-freedom compliant micro-motion parallel mechanism by proposing a modified modeling method based on the structural matrix method (SMM).

This paper analyzes the problem that the torsional compliance equation of the circular notched hinge is no longer applicable because it is subject to bilateral restrained torsion. The torsional compliance equation is modified by introducing the relative length coefficient. The input coupling effect, which is often neglected, is considered in kinematic modeling. The symbolic expression of the input coupling matrix is obtained. Theory, simulation and experimentation are presented to show the validity of the proposed kinematic model.

The results show that the proposed kinematics model can improve the modeling accuracy by comparing the theoretical, finite element method (FEM) and experimental method.

This work provides a feasible scheme for CMPM kinematics modeling. It can be better applied to the optimization design based on the kinematic model in the future.