Open Platform Communication Research Articles

A federated information system framework for vertical integration

The convergence of operational and information technology in the era of Industry 4.0 has significantly increased the volume of data being generated on the manufacturing shop floors. Current research trends have focused on integrating this data with information present throughout the different systems in manufacturing facilities from Enterprise Resource Planning (ERP) to Manufacturing Execution System (MES) software, otherwise known as vertical integration. More specifically, previous works have looked at aggregating this data being read from Open Platform Communication Unified Architecture (OPC UA) servers by utilizing centralized aggregation servers to create information systems. This article, however, proposes a framework that adopts a federated information system designed to fulfill the manufacturing industry’s requirements and is capable of connecting to different OPC UA servers and storing the data within knowledge graph-based information models. GraphQL servers are also utilized in this system for easy accessibility of information by users. This system provides modularity, scalability, and interoperability to supplement the capabilities of information systems previously implemented. A prototype was also developed in this article for a federated information system for a boiler monitoring system.

A Cyber–Physical System Based on Digital Twin and 3D SCADA for Real-Time Monitoring of Olive Oil Mills

Cyber–physical systems involve the creation, continuous updating, and monitoring of virtual replicas that closely mirror their physical counterparts. These virtual representations are fed by real-time data from sensors, Internet of Things (IoT) devices, and other sources, enabling a dynamic and accurate reflection of the state of the physical system. This emphasizes the importance of data synchronization, visualization, and interaction within virtual environments as a means to improve decision-making, training, maintenance, and overall operational efficiency. This paper presents a novel approach to a cyber–physical system that integrates virtual reality (VR)-based digital twins and 3D SCADA in the context of Industry 4.0 for the monitoring and optimization of an olive mill. The methodology leverages virtual reality to create a digital twin that enables immersive data-driven simulations for olive mill monitoring. The proposed CPS takes data from the physical environment through the existing sensors and measurement elements in the olive mill, concentrates them, and exposes them to the virtual environment through the Open Platform Communication United Architecture (OPC-UA) protocol, thus establishing bidirectional and real-time communication. Furthermore, in the proposed virtual environment, the digital twin is interfaced with the 3D SCADA system, allowing it to create virtual models of the process. This innovative approach has the potential to revolutionize the olive oil industry by improving operational efficiency, product quality, and sustainability while optimizing maintenance practices.

The State of The Knowledge of Cloud Computing Technology for Manufacturing Automation Systems

The manufacturing sector is grappling with the need to adapt to rapid technological changes, and leveraging cloud computing is becoming crucial for staying competitive and resilient. The presentation of knowledge in this work focuses on highlighting the specific challenges and opportunities in integrating cloud technologies into manufacturing systems. It aims to answer critical questions such as how cloud computing can enhance manufacturing automation, solve problems, and benefit to the industry. The methodology employed in this research takes a comprehensive and top-down approach, aligning and exploring the practical aspects of implementing these X-as-a-Service (XaaS) model in manufacturing setups. The research also acknowledges the shift from legacy Distributed Numerical Control (DNC) systems to modern solutions like MTConnect and Open Platform Communication (OPC) for data exchange in automated manufacturing systems. Emphasizing the important of data collection and real-time monitoring, the study highlights the role of Industrial Internet of Things (IoT) sensors deployed at various points of manufacturing system components (machine tools, spindles, cutting tools, production units, etc.). These sensors capture real-time production and condition data, enabling informed decision-making in manufacturing systems. This research not only presents the latest knowledge but also offers insights into the challenges, strategies, and methodologies involved in the successful integration of cloud-based technology into manufacturing automation systems. It also aims to serve as a valuable resource for manufacturers, researchers, and industry professionals navigating the transformative journey toward cloud-powered manufacturing.

Industrial Internet of Things: A Review of Improvements Over Traditional SCADA Systems for Industrial Automation

This review article provides an overview of the potential of the Industrial Internet of Things (IIoT) to revolutionize industrial automation. The IIoT is the Internet of Things (IoT) but in an industrial context, i.e., IIoT is used more to connect machines and devices in industrial environments. The IIoT has the potential to benefit from advances in artificial intelligence, particularly machine learning and deep learning, to increase efficiency and productivity and reduce overhead costs. We provide an overview of the supervisory control and data acquisition system, a definition of IIoT, and how IIoT can offer industry greater potential for system integration to improve automation and optimization. In addition, five of the major IIoT protocols are discussed, namely, message queue telemetry transport, advanced messaging queuing protocol, constrained application protocol, data distribution service, and open platform communication unified architecture. We then identified key IIoT improvements for industrial automation. These are; efficient and low-cost systems, digital twin, machine failure prediction, real-time remote monitoring, and security. We then discussed the key research in the literature for each category. We presented some public IIoT datasets so that researchers can use them to develop new learning models to improve the security of IIoT systems. Finally, we discussed some of the limitations, recommendations, and future perspectives for developing IIoT-enabled systems.

Implementation of Matlab communication and Allen Bradley PLC for control of the AMATROL JUPITER XL Robot

The article introduces a method to enable a robot, the "AMATROL JUPITER XL," without relying on its conventional controllers. Instead, a Human-Machine Interface (HMI) is employed using Allen Bradley's "ControlLogix 5550" software. This setup combines the engineering program MATLAB (via the Simulink extension) to develop control block diagrams containing calculations for robot design and comprehension. A data read-write interface is implemented on an "Allen Bradley 1756-L1" PLC, along with the integration of an Open Platform Communication (OPC) platform using the "RSLinx Classic" software. This configuration empowers the user to manipulate trajectories and objectives using calculations that depict the kinematics and dynamics of the mentioned robot. Consequently, this setup offers a control option that enables direct application of theoretical mathematical principles to the design and control aspects of robotics, leading to enhanced understanding of these principles.

Hardware in the Loop Simulation for Bottle Sealing Process Virtualized on Unity 3D

This paper details the design and implementation of a virtualized bottle sealing plant using the Hardware in the Loop technique, for which it is divided into two parts: (i) Software consists of a virtualized environment in Unity 3D to visualize its behavior in real time; and (ii) Hardware was implemented through a PLC S7 1200 AC/DC/RLY (Programmable Logic Controller), which is responsible for the automation of the plant, programmed through the software TIA Portal V16 (Totally Integrated Automation Portal) and a control panel with buttons and indicator lights. The two developed parts communicate through bidirectional TCP/IP Ethernet, achieving a Server–Client architecture. For real-time monitoring and visualization, a SCADA (Supervisory Control and Data Acquisition) system implemented in InTouch is considered. In addition, the data acquisition is accomplished through the OPC (Open Platform Communication) server; the functionality of the OPC server is to transmit the information generated in an industrial plant at the enterprise level. This allows the process to execute its tasks of connectivity of automated processes and their supervision, as well as having scalability so that more tags can be included in other processes over time and ensure its operability.

Architecture for manufacturing-X: Bringing asset administration shell, eclipse dataspace connector and OPC UA together

Manufacturing-X represents the idea of a decentralized data economy. The aim is to increase sustainability, competitiveness and resilience by digitizing supply chains. Technically, this requires three technologies. First, a standardized data model to ensure interoperability across company boundaries. Second, a solution to realize sovereign inter-organizational data exchange. And thirdly, a component for the company’s internal data communication. Asset Administration Shell (AAS), Eclipse Dataspace Connector (EDSC) and Open Platform Communication Unified Architecture (OPC UA) are suitable solutions. This paper introduces an appropriate architecture to combine these technologies in an industrial production environment and discusses existing challenges, limitations and future potentials.

Detection and mitigation of field flooding attacks on oil and gas critical infrastructure communication

Industrial Cyber-Physical Systems (ICPS) are highly dependent on Supervisory Control and Data Acquisition (SCADA) for process monitoring and control. Such SCADA systems are known to communicate using various insecure protocols such as Modbus, DNP3, and Open Platform Communication (OPC) Data Access standards (providing access to real-time automation data), which are vulnerable to a range of attacks. This leads to increased cyber risks faced in critical infrastructures, especially in the Oil and Gas sector. One of the most popular and critical attacks deployed against such infrastructure is Denial of Service (DoS), as it can have severe consequences that range from financial loss to loss of life. Such attacks can disrupt the ability of an operator to control hazardous operations leading to potentially unsafe scenarios. A novel Field Flooding attack is described which takes advantage of the packet memory structure of the Modbus protocol to perform a DoS attack. This attack can cause overflowing of the memory bank allocated in the Programmable Logic Controller (PLC) for Modbus operations. The attack is deployed and evaluated on a real industrial testbed and its impact against the Mitre ATT&CK framework is assessed, in order to identify which tactics an adversary could use to compromise the system. A novel mechanism that utilises supervised machine learning to detect this attack in industrial control system networks is also described. Experimental results show that the proposed mechanism, using the XGBoost algorithm, can identify this attack with 99% accuracy.

A framework for researching energy optimization of factory operations

Energy optimization of factory operations has gained increasing importance over recent years since it is understood as one way to counteract climate change. At the same time, the number of research teams working on energy-optimized factory operations has also increased. While many tools are useful in this area, our team has recognized the importance of a comprehensive framework to combine functionality for optimization, simulation, and communication with devices in the factory. Therefore, we developed a framework that provides a standardized interface to research energy-optimized factory operations with a rolling horizon approach. The optimization part of the framework is based on the OpenAI gym environment. The framework also provides connectors for multiple communication protocols including Open Platform Communication Unified Architecture and Modbus via Transmission Control Protocol. These facilities can be utilized to implement rolling horizon optimizations for factory systems easily and directly control devices in the factory with the optimization results. In this article, we present the framework and show some examples to prove the effectiveness of our approach.

Vulnerabilities of the Open Platform Communication Unified Architecture Protocol in Industrial Internet of Things Operation

Recently, as new threats from attackers are discovered, the damage and scale of these threats are increasing. Vulnerabilities should be identified early, and countermeasures should be implemented to solve this problem. However, there are limitations to applying the vulnerability discovery framework used in practice. Existing frameworks have limitations in terms of the analysis target. If the analysis target is abstract, it cannot be easily applied to the framework. Therefore, this study proposes a framework for vulnerability discovery and countermeasures that can be applied to any analysis target. The proposed framework includes a structural analysis to discover vulnerabilities from a scenario composition, including analysis targets. In addition, a proof of concept is conducted to derive and verify threats that can actually occur through threat modeling. In this study, the open platform communication integrated architecture used in the industrial control system and industrial Internet of Things environment was selected as an analysis target. We find 30 major threats and four vulnerabilities based on the proposed framework. As a result, the validity of malicious client attacks using certificates and DoS attack scenarios using flooding were validated, and we create countermeasures for these vulnerabilities.

An Aggregated Data Integration Approach to the Web and Cloud Platforms through a Modular REST-Based OPC UA Middleware.

The Internet of Things (IoT) empowers the development of heterogeneous systems for various application domains using embedded devices and diverse data transmission protocols. Collaborative integration of these systems in the industrial domain leads to incompatibility and interoperability at different automation levels, requiring unified coordination to exchange information efficiently. The hardware specifications of these devices are resource-constrained, limiting their performance in resource allocation, data management, and remote process supervision. Hence, unlocking network capabilities with other domains such as cloud and web services is required. This study proposed a platform-independent middleware module incorporating the Open Platform Communication Unified Architecture (OPC UA) and Representational State Transfer (REST) paradigms. The object-oriented structure of this middleware allows information contextualization to address interoperability issues and offers aggregated data integration with other domains. RESTful web and cloud platforms were implemented to collect this middleware data, provide remote application support, and enable aggregated resource allocation in a database server. Several performance assessments were conducted on the developed system deployed in Raspberry Pi and Intel NUC PC, which showed acceptable platform resource utilization regarding CPU, bandwidth, and power consumption, with low service, update, and response time requirements. This integrated approach demonstrates an excellent cost-effective prospect for interoperable Machine-to-Machine (M2M) communication, enables remote process supervision, and offers aggregated bulk data management with wider domains.

Towards a Data Lake for High Pressure Die Casting

The High Pressure Die Casting (HPDC) process is characterized by a high degree of automation and therefore represents a data rich production technology. From concepts such as Industry 4.0 and the Internet of Production (IoP), it is well known that the utilization of process data can facilitate improvements in product quality and productivity. In this work, we present a concept and its first steps of implementation to enable data management via a data lake for HPDC. Our goal was to design a system capable of acquiring, transmitting and storing static as well as dynamic process variables. The measurements originate from multiple data sources based on the Open Platform Communication Unified Architecture (OPC UA) within the HPDC cell and are transmitted via a streaming pipeline implemented in Node-Red and Apache Kafka. The data are consecutively stored in a data lake for HPDC that is based on a MinIO object store. In initial tests the implemented system proved it to be reliable, flexible and scalable. On standard consumer hardware, data handling of several thousand measurements per minute is possible. The use of the visual programming language Node-Red enables swift reconfiguration and deployment of the data processing pipeline.

Evaluation of PLC4X based Middleware as Integrator of Brownfield systems into Industrial Cyber-Physical Systems

The emergence of the Internet of Things (IoT) and Cyber-Physical Systems (CPS), supported by the rapid growth in computing and communication technologies in the past decade, has started the fourth industrial revolution (Industry 4.0). Industry 4.0 reinvents the industrial communication paradigm by proposing a mesh of intertwined physical and digital entities, namely the digital twin network. Integration of brownfield legacy systems into an Industry 4.0 compliant CPS, due to their relatively high vendor dependency and technological heterogeneity, remains one of the biggest challenges. To tackle this issue, Open Platform Communication Unified Architecture (OPC UA) was developed. OPC UA acts as a vendor and protocol-agnostic communication middleware for data acquisition. Modern Programmable Logic Controllers (PLC) allow running an OPC UA server inside them and data access can be performed through any OPC UA client tool. While this does solve the brownfield integration problem to a certain extent, the majority of the tools on the shop floor still use vendor-specific technologies. PLC4X is a set of libraries for communicating with PLCs and fetching data from them. It supports a wide range of communication protocols and could be a promising candidate for addressing the integration challenges. Therefore, in this paper, we evaluate the viability of PLC4X as an enabler for a communication middleware that tackles the integration challenges concerning the brownfield systems in Industry 4.0.

Development of Innovative Operational Flexibility Measurement Model for Smart Systems in Industry 4.0 Paradigm

The exponential growth of cutting-edge technologies continuously pushing the manufacturing industry into the paradigm of smart manufacturing. Smart manufacturing provides the pace of highly competitive market demand and customized intensive production. The goal of smart manufacturing technologies embedded systems in the Industry 4.0 paradigm and lean production is to enhance the flexibility in all tears of the enterprise. It is a big challenge, to measure the flexibility of smart systems for decision-making and adaptation of the new manufacturing technologies. The conceptual architecture of smart manufacturing systems has been proposed to solve the problem. Operational flexibility has been measured using a mathematical model for smart manufacturing in the Open Platform Communication Unified Architecture enabled Cyber-Physical Production System at shop floor level and validated. The results obtained from experimentation depict the operational flexibility, maximum capacity, and breakeven point of the manufacturing system have been improved by using smart manufacturing technologies. The proposed model improves the product manufacturing using Smart Computer Numeric Control Machining, Smart Autonomous Robotic Machining, Smart Additive Manufacturing and Smart Hybrid Additive & Subtractive Manufacturing up to 30.4%, 53.6%, 55% and 65% respectively. It will also help the decision-makers to overcome the challenges of transformation from conventional to smart manufacturing industry 4.0 paradigm.

DDS and OPC UA Protocol Coexistence Solution in Real-Time and Industry 4.0 Context Using Non-Ideal Infrastructure.

Continuing the evolution towards Industry 4.0, the industrial communication protocols represent a significant topic of interest, as real-time data exchange between multiple devices constitute the pillar of Industrial Internet of Things (IIoT) scenarios. Although the legacy protocols are still persistent in the industry, the transition was initiated by the key Industry 4.0 facilitating protocol, the Open Platform Communication Unified Architecture (OPC UA). OPC UA has to reach the envisioned applicability, and it therefore has to consider coexistence with other emerging real-time oriented protocols in the production lines. The Data Distribution Service (DDS) will certainly be present in future architectures in some areas as robots, co-bots, and compact units. The current paper proposes a solution to evaluate the real-time coexistence of OPC UA and DDS protocols, functioning in parallel and in a gateway context. The purpose is to confirm the compatibility and feasibility between the two protocols alongside a general definition of criteria and expectations from an architectural point of view, pointing out advantages and disadvantages in a neutral manner, shaping a comprehensive view of the possibilities. The researched architecture is meant to comply with both performance comparison scenarios and interaction scenarios over a gateway application. Considering the industrial tendencies, the developed solution is applied using non-ideal infrastructures to provide a more feasible and faster applicability in the production lines.

A method for predicting hobbing tool wear based on CNC real-time monitoring data and deep learning

Intelligent monitoring and diagnosis of tool status are of great significance for improving the manufacturing efficiency and accuracy of the workpiece. It is difficult to quickly and accurately predict the wear state of worm gear hob under different working conditions. This paper proposes a novel approach to predict hob wear status based on CNC real-time monitoring data. Based on the open platform communication unified architecture (OPC UA) technology and orthogonal test, the machine data of motor power, current, etc. related to tool wear are collected online in the worm gear machining process. And then, an improved deep belief network (DBN) is used to generate a tool wear model by training data. A growing DBN with transfer learning is introduced to automatically decide its best model structure, which can accelerate its learning process, improve training efficiency and model performance. The experiment results show that the proposed method can effectively predict hob wear status under multi-cutting conditions. To show the advantages of the proposed approach, the performance of the DBN is compared with the traditional back propagation neural network (BP) method in terms of the mean-squared error (MSE). The compared results show that this tool wear prediction method has better prediction accuracy than the traditional BP method during worm gear hobbing.

Automated Design and Integration of Asset Administration Shells in Components of Industry 4.0.

One of the central concepts in the principles of Industry 4.0 relates to the methodology for designing and implementing the digital shell of the manufacturing process components. This concept, the Asset Administration Shell (AAS), embodies a systematically formed, standardized data envelope of a concrete component within Industry 4.0. The paper discusses the AAS in terms of its structure, its components, the sub-models that form a substantial part of the shell’s content, and its communication protocols (Open Platform Communication—Unified Architecture (OPC UA) and MQTT) or SW interfaces enabling vertical and horizontal communication to involve other components and levels of management systems. Using a case study of a virtual assembly line that integrates AASs into the technological process, the authors present a comprehensive analysis centered on forming AASs for individual components. In the given context, the manual AAS creation mode exploiting framework-based automated generation, which forms the AAS via a configuration wizard, is assessed. Another outcome consists of the activation of a virtual assembly line connected to real AASs, a step that allows us verify the properties of the distributed manufacturing management. Moreover, a discrete event system was modeled for the case study, enabling the effective application of the Industry 4.0 solution.

Approaching OPC UA Publish-Subscribe in the Context of UDP-Based Multi-Channel Communication and Image Transmission.

The Open Platform Communication Unified Architecture (OPC UA) protocol is a key enabler of Industry 4.0 and Industrial Internet of Things (IIoT). OPC UA is already accepted by the industry and its presence is expected to reach more and more fields, applications, and hierarchical levels. Advances within the latest specifications are providing the opportunity to extend the capabilities and the applicability of the protocol, targeting better performances in terms of data volumes, speed, availability, footprint, and security. Continuing previous researches focusing on the publish–subscribe (pub/sub) mechanism and real-time constraints, the current study aims to consider higher data-volumes, approach the multi-channel User Datagram Protocol (UDP)-based communication, and analyze the robustness of the developed mechanism in the context of long-term data transmission. Consequently, the research proposes to extend the applicability of the OPC UA in the context of image transmission. Although highly needed, the image transmission after processing is currently beyond the reach of OPC UA or other legacy industrial protocols, being considered as a separate fraction in the industrial environment. The concept and developments are applied considering both the end-of-line industrial manufacturing process in the automotive sector and the car-to-infrastructure communication. Without special hardware constraints, the obtained results are proven to be appreciable, opening various future perspectives for image transmission using OPC UA.

A framework for monitoring multiple databases in industries using OPC UA

Database management and monitoring is an inseparable part of any industry. A uniform scheme of monitoring relational databases without explicit user access to database servers is not much explored outside the database environment. In this paper, we present an information distribution scheme related to databases using Open Platform Communication Unified Architecture (OPC UA) servers to clients when multiple databases are involved in a factory. The aim is for external, but relevant clients, to be able to monitor this information mesh independent of explicit access to user schemas. A methodology to dispense data from, as well as check changes in databases using SQL queries and events is outlined and implemented using OPC UA servers. The structure can be used as a remote viewing application for multiple databases in one address space of an OPC UA server.

Improving OPC UA Publish-Subscribe Mechanism over UDP with Synchronization Algorithm and Multithreading Broker Application.

Communication protocols are evolving continuously as the interfacing and interoperability requirements are the foundation of Industry 4.0 and Industrial Internet of Things (IIoT), and the Open Platform Communication Unified Architecture (OPC UA) protocol is a major enabling technology. OPC UA was adopted by the industry, and research is continuously carried out to extend and to improve its capabilities, to fulfil the growing requirements of specific industries and hierarchical levels. Consistent issues that have to be approached are related to the latest specifications and the real-time context that could extend the applicability of the protocol and bring significant benefits in terms of speed, data volumes, footprint, security. The real-time context is essential in the automotive sector and it is highly developed within some specific protocols. The current work approaches first the conceptual analysis to improve the OPC UA interfacing using the Publish-Subscribe mechanism, focusing on real-time constraints and role distribution between entities, and considering some well-founded interfacing strategies from the automotive sector. The conceptual analysis is materialized into a solution that takes OPC UA Publish-Subscribe over User Datagram Protocol (UDP) mechanism to the next level by developing a synchronization algorithm and a multithreading broker application to obtain real time responsiveness and increased efficiency by lowering the publisher and the subscriber footprint and computational effort, reducing the difficulty of sending larger volumes of data for various subscribers and the charge on the network and services in terms of polling and filtering. The proof of concept is evaluated and the results prove the efficiency of the approach and the solution.