Interoperability between OPC UA and oneM2M

Implementation of OPC UA Communication Traffic Control for Analog Values in an Automation Device with Embedded OPC UA Servers

In recent years, intelligent manufacturing has developed rapidly. Industrial IoT technologies are applied to different industrial scenarios. OPC UA is a service-oriented architecture, which has good interoperability. At the same time, it is a cross-platform communication standard that can realize the interconnection between heterogeneous network devices and solve the problem of information silos in the industrial IoT field. However, with the gradual increase of industrial equipment, the amount of data transmission in the network is increasing. The traditional OPC UA communication method based on client/server mode has defects such as tight coupling and performance bottleneck. It cannot meet the high throughput demand of the network. Therefore, these phenomena lead to longer time delays and lower transmission efficiency of network communication systems. To solve the above problems, this paper proposes a publish/subscribe communication model based on OPC UA. We design the overall architecture of the OPC UA publish/subscribe model and adopt a message agent mechanism to realize distributed communication of OPC UA. This model has functions such as message modeling, address space construction, and publish/subscribe. The architecture of this communication model is compatible with the C/S model, which can ensure compatibility and coexistence with the traditional OPC UA communication system. Meanwhile, in order to improve the distinguished service capability of the OPC UA system, a multi-priority data scheduling algorithm is proposed and integrated into the publish/subscribe communication model to improve the efficiency of real-time data transmission in industrial networks. The experimental results show that the communication model can accomplish distributed communication in industrial networks and be better applied in wireless sensor networks. The scheduling algorithm included in the model significantly improves the efficiency of real-time data transmission and reduces the time delay.

Gaining value out of data provided in industrial application in a standardized Industrie 4.0 compliant way is a challenging and time-extensive task. Not only does the data need to be integrated into a data platform, it also needs to be described and integrated in an appropriate way, that allows a standardized processing for its value-added services. One way to achieve this, lies in the use of OPC UA and the asset administration shell. Together they can implement an Industrie 4.0 Component as the standardized service for tailored data integration and usage. Data in OPC UA is available in different levels of abstraction, both in terms of the data and its description. Rarely is the asset administration shell (AAS) considered in this context. This paper will introduce a first approach to harmonize OPC UA and the AAS in an I4.0 compliant Aggregation Server. The server is able to aggregate information models based on the current meta model mapping of the AAS, regardless of whether the base servers implement this or not. Moreover the aggregated server can route OPC UA services down to the base servers and is managing itself in case of discovery and information aggregation. This approach can be used as the standalone interface for data integration in respective data platforms.

Optimization of industrial processes requires further research on the integration of machine-centric systems with human-centric cloud-based services in the context of new emerging disciplines, namely the fourth industrial revolution coined as Industry 4.0 and Industrial Internet of Things. The following research aims at working out a new generic architecture and deployment scenario applicable to that integration. A reactive interoperability relationship of the communication parties is proposed to deal with the network traffic propagation asymmetry or assets’ mobility. Described solution based on the OPC Unified Architecture international standard relaxes issues related to the real-time multi-vendor environment. The discussion concludes that the embedded gateway software component best suits all requirements and thus has been implemented as a composable part of the selected reactive OPC UA framework which promotes separation of concerns and reusability.The proposals are backed by proof-of-concept reference implementations confirming the possibility of integrating selected cloud services with the OPC UA based cyber-physical system by applying the proposed architecture and deployment scenario. It is contrary to interconnecting cloud services with the selected OPC UA Server limiting the PubSub role to data export only.KeywordsIndustry 4.0Internet of ThingsObject-Oriented InternetCloud computingIndustrial communicationReactive networkingMachine to Machine communicationOPC Unified ArchitectureAzure

OPC UA is a new specification developed on the basis of classic OPC. It overcomes the limitations of classic OPC, has the advantages of platform independence and scalability, and is widely used in industrial fields. Node-Red is a visual programming tool based on node.js that allows you to combine modules to write applications and make programming simpler. This paper designs a Node-Red to create a stream as an OPC UA client by connecting OPC UA related node modules, connect to the OPC UA server, and call services such as reading and writing, subscription, etc., to realize real-time monitoring and display of the workshop temperature, and start the fan when the temperature is too high. In addition, Node-Red has a display module that provides a more diverse selection of information.

This article proposes the development of an information model that allows starting the digital transformation of a small or medium-sized company (SME) using the OPC UA protocol. The model is made up of a hardware component made up of the process plant and the control equipment, as well as a software component where the information model is implemented.As an application case, the proposed information model is developed in a unit process plant, a filtration plant. The process carried out in this plant is through a filter to remove the solid particles present in the water used in the manufacturing process of a beverage. This plant can be integrated into a beverage and/or soft drink manufacturing system in a small company.The information model is integrated into an OPC UA server, a programmable controller, mapping the process variables such as level, temperature flow, and energy consumption. The information of the technological elements that make up the filtration plant are: serial, manufacturer, and calibration dates: OPC UA clients request information from the OPC UA server and then they are sent through procedures (methods) defined in the server and consumed by the server. client, all this integrates the information model.The foregoing shows the viability of the proposed

Global CO2 emissions reduction requires industries to manage and understand their CO2 emission levels in real-time. This paper examines the Industrial Internet of Things (IIoT) for real-time monitoring, measurement, and visualization of reducing CO2 emissions in industrial and environmental domains. Methodology: The methodology consists of a literature review based on peer-reviewed publications and use cases to explore the current state and practical implications. Furthermore, a technical analysis of IIoT systems, CO2 sensors, and data processing techniques is also identified. Results: IIoT systems can support CO2 emission monitoring and accuracy optimization in industrial domains by combining CO2 sensors, wireless communication, and data fusion techniques. In addition, machine learning and artificial intelligence can be used to reduce anomalies in CO2 sensor readings and predictive maintenance of systems. Challenges: Challenges include interoperability, data security and system scalability. To resolve these issues standardized communication protocols, data security methods and implementation barriers should be improved. Future Directions: To enhance data processing and security features, future work should focus on integrating edge computing, artificial intelligence, machine learning, and blockchain techniques. In addition, data visualizations and cost-effective solutions should also be in focus, to provide more adoptable IIoT systems in industrial domains. Conclusion: As IIoT systems and CO2 sensor technologies evolve, IIoT systems can contribute significantly to increasing global air quality and CO2 emission control in industry, agricultural, and urban areas.

The vision of Industry 4.0, otherwise known as the fourth industrial revolution, is the integration of massively deployed smart computing and network technologies in industrial production and manufacturing settings for the purposes of automation, reliability, and control, implicating the development of an Industrial Internet of Things (I-IoT). Specifically, I-IoT is devoted to adopting the Internet of Things (IoT) to enable the interconnection of anything, anywhere, and at anytime in the manufacturing system context to improve the productivity, efficiency, safety and intelligence. As an emerging technology, I-IoT has distinct properties and requirements that distinguish it from consumer IoT, including the unique types of smart devices incorporated, network technologies and quality of service requirements, and strict needs of command and control. To more clearly understand the complexities of I-IoT and its distinct needs, and to present a unified assessment of the technology from a systems perspective, in this paper we comprehensively survey the body of existing research on I-IoT. Particularly, we first present the I-IoT architecture, I-IoT applications (i.e., factory automation (FA) and process automation (PA)) and their characteristics. We then consider existing research efforts from the three key systems aspects of control, networking and computing. Regarding control, we first categorize industrial control systems and then present recent and relevant research efforts. Next, considering networking, we propose a three-dimensional framework to explore the existing research space, and investigate the adoption of some representative networking technologies, including 5G, machine-to-machine (M2M) communication, and software defined networking (SDN). Similarly, concerning computing, we again propose a second three-dimensional framework that explores the problem space of computing in I-IoT, and investigate the cloud, edge, and hybrid cloud and edge computing platforms. Finally, we outline particular challenges and future research needs in control, networking, and computing systems, as well as for the adoption of machine learning, in an I-IoT context.

Industry 4.0 is the German vision for the future of manufacturing, where smart factories use information and communication technologies to digitise their processes to achieve improved quality, lower costs, and increased efficiency. It is likely to bring a massive change to the way control systems function today. Future distributed control systems are expected to have an increased connectivity to the Internet, in order to capitalize on new offers and research findings related to digitalization, such as cloud, big data, and machine learning. A key technology in the realization of distributed control systems is middleware, which is usually described as a reusable software layer between operating system and distributed applications. Various middleware technologies have been proposed to facilitate communication in industrial control systems and hide the heterogeneity amongst the subsystems, such as OPC UA, DDS, and RT-CORBA. These technologies can significantly simplify the system design and integration of devices despite their heterogeneity. However, each of these technologies has its own characteristics that may work better for particular applications. Selection of the best middleware for a specific application is a critical issue for system designers. In this paper, we conduct a survey on available standard middleware technologies, including OPC UA, DDS, and RT-CORBA, and show new trends for different industrial domains.

With the boom of Industry 4.0 for industrial automation, the data exchange between the different industrial devices has tremendously increased through local (edge) and cloud computing. Nowadays, several communication protocols are available to realize data acquisition in the industry. As a result, understanding the practical capabilities of each communication protocol arises as an essential issue in optimizing the data acquisition and storage in industrial plants. This study aims to develop a software-based test environment to evaluate the performance of two widely used communication protocols within the scope of the Industrial Internet of Things (IIoT). These contemplated protocols are Open Platform Communications Unified Architecture (OPC UA) and Message Queuing Telemetry Transport (MQTT). With the help of the developed test environment, several performance metrics, like packet overhead, latency, packet loss ratio, and CPU utilization, are evaluated for different application scenarios where the varying number of clients and subscribers are considered. Derived results indicate the stronger parts of each protocol under varying communication configurations.

Using a physical laboratory for Industrial Internet of Things (IIoT) demands significant allocation of financial resources fo r supervision and maintenance post-installation. Consequently, its utilization is often confined to highly guided laboratory practices to safeguard the integrity of industrial controllers, limited to a few workstations within the facilities. These re strictive constraints create a bottleneck for undergraduate students to engage in practical exercises related to automation processes. Our main goal is to provide an open-source, low-cost educational platform for resource-constrained universities which can be easily implemented, configured and connected to mobile networks. The proposed coursework chooses text-based programming to familiarise first-semester technical/college students with programming for industrial automation, and the physical testbed integrates a legacy programmable logic controller (PLC) with an Open Platform Communications Unified Architecture (OPC UA) server, alongside text-based programming to configure mobile communication modems supporting multiple Radio Access Technologies (RATs). The combined approaches serve as a safe option for simple industrial automation trainin g, including access to mobile services.

An aggregating server providing data access to multiple data sources is a software architecture that is often applied in industrial applications. This paper presents a design of an aggregating server based on OPC UA technology and tests it with two different experimental applications, one about production control of a flexible manufacturing system and another about remote monitoring of mobile work machines. The presented design enables transparent access to the data in the address space of the aggregating server through utilization of address space transformations. The transformations can be either configured with rules or be programmed. Feasibility of the design of the aggregating server and the applications was evaluated with experimental implementations containing both simulated devices and real work machines.

Internet of Things (IoT), together with fifth-generation (5G) mobile systems and related enabling communication technologies, constantly contributing for the enhancement in various industrial applications and driving towards the vision of complete industrial automation. In this context, both Blockchain and Edge computing are considered as promising technologies to fulfill the vision and requirements for the future Industry 4.0. The integration of these technologies together with massive scale Industrial IoT (IIoT) applications would be vital in addressing several key challenges related to e.g. latency, scalability and security of data processing and sharing, among others. However, such complex IIoT systems are constantly exposed to security threats from various sources. This paper focuses on identifying the major security challenges in the IIoT blockchain-edge related networks. In addition, some potential security solutions are presented in order to overcome these challenges.

Blockchain technologies have recently come to the forefront of the research and industrial communities as they bring potential benefits for many industries. This is due to their practical capabilities in solving many issues currently inhibiting further advances in various industrial domains. Securely recording and sharing transactional data, establishing automated and efficient supply chain processes, and enhancing transparency across the whole value chain are some examples of these issues. Blockchain offers an effective way to tackle these issues using distributed, shared, secure, and permissioned transactional ledgers. The employment of blockchain technologies and the possibility of applying them in different situations enables many industrial applications through increased efficiency and security; enhanced traceability and transparency; and reduced costs. In this paper, different industrial application domains where the use of blockchain technologies has been proposed are reviewed. This paper explores the opportunities, benefits, and challenges of incorporating blockchain in different industrial applications. Furthermore, the paper attempts to identify the requirements that support the implementation of blockchain for different industrial applications. The review reveals that several opportunities are available for utilizing blockchain in various industrial sectors; however, there are still some challenges to be addressed to achieve better utilization of this technology.

Open Platform Communications Unified Architecture (OPC UA) is an increasingly important standard for industrial communication, which brings up the need for testing. Still, functional or formal verification of the implementation relies on conformance testing or custom solutions. Model-based testing has been studied and applied for decades, targeting many different technologies. OPC UA already provides a defined serialization format for its interfaces, representing a simple model of the application that could be utilized for testing.In this paper, we present our work on applying model-based testing to OPC UA server applications using the serialized interface description as the model. We introduce a possible toolchain for that approach and, based on that, discuss the possibilities and shortcomings of the interface description as a model for testing.