A Real-Time Service-Oriented Architecture for Industrial Automation

Industrial automation platforms are experiencing a paradigm shift. New technologies are making their way in the area, including embedded real-time systems, standard local area networks like Ethernet, Wi-Fi and ZigBee, IP-based communication protocols, standard service oriented architectures (SOAs) and Web services. An automation system will be composed of flexible autonomous components with plug & play functionality, self configuration and diagnostics, and autonomic local control that communicate through standard networking technologies. However, the introduction of these new technologies raises important problems that need to be properly solved, one of these being the need to support real-time and quality-of-service (QoS) for real-time applications. This paper describes a SOA enhanced with real-time capabilities for industrial automation. The proposed architecture allows for negotiation of the QoS requested by clients from Web services, and provides temporal encapsulation of individual activities. This way, it is possible to perform an a priori analysis of the temporal behavior of each service, and to avoid unwanted interference among them. After describing the architecture, experimental results gathered on a real implementation of the framework (which leverages a soft real-time scheduler for the Linux kernel) are presented, showing the effectiveness of the proposed solution. The experiments were performed on simple case studies designed in the context of industrial automation applications

A Sequential Control Language for Industrial Automation

Current market trends for industrial automation are the need for customizable production, shorter time to market, and powerful global competitive pressure. Based on these trends two challenges have been identified: 1) flexible production systems and 2) integration and utilization of devices and software. Applications from both process automation, manufacturing, and robotics have been considered. More flexible languages and tools are needed to get a flexible production system. The graphical programming language Grafchart, based on the IEC 61131-3 standard language Sequential Function Charts (SFC), is considered with the aim to make both the language and its implementation more flexible. In particular, new constructs have been added to the Grafchart language and modern compiler techniques are evaluated for JGrafchart, a Grafchart implementation, with focus on an extensible language implementation. A first step toward real-time execution of Grafchart applications is also taken to make it possible to use Grafchart for hard real-time control. High execution rates often reveal concurrency issues and thus execution concurrency has also been investigated. Access to more data from industrial devices and software can be used to optimize production. Architectures for factory integration have been considered as this is the foundation to connect all devices and thus address the challenge of integrating and utilizing devices and software. Service Oriented Architecture (SOA) is a flexible software design methodology widely used in IT systems and for business processes. SOA service orchestration is brought to industrial automation by integrating support for both Devices Profile for Web Services (DPWS) and OPC Unified Architecture (OPC UA) in JGrafchart. Looking further, SOA 2.0 is event driven and features extremely loose coupling between components. An architecture based on SOA 2.0 where it is easy to integrate any device or software, in particular legacy devices with limited knowledge and capabilities, has been developed with focus on service choreography in industrial manufacturing. Another step toward real-time execution of Grafchart applications is integrated support for the high performance communication protocol LabComm. Additionally, it is investigated how Grafchart can be connected to Functional Mock-up Interface (FMI) for co-simulation to further address the shorter time to market trend by introducing simulation support. The PID controller is the most common controller for industrial automation. A PID implementation has been added to a Grafchart library and a flaw with the PID algorithm has been discovered. The problem occurs for PID controllers with a derivative part when the process value saturates. The derivative part then backs off which leads to undesired changes in the control signal. This issue has been analyzed and a solution to the problem is proposed

Industrial Robot Programming and UPnP Services Orchestration for the Automation of Factories

The integration of equipment and other devices built into industrial robot cells with modern Ethernet interface technologies and low‐cost mass produced devices (such as vision systems, laser scanners, force torque‐sensors, PLCs and PDAs etc.) enables integrators to offer more powerful and smarter solutions. Nevertheless, the programming of all these devices efficiently requires very specific knowledge about them, such as their hardware architectures and specific programming languages as well as details about the system¿s low level communication protocols. To address these issues, this paper describes and analyses the Plug‐and‐Play architecture. This is one of the most interesting service‐oriented architectures (SOAs) available, which exhibits characteristics that are well adapted to industrial robotics cells. To validate their programming features and applicability, a test bed was specially designed. This provides a new graphical service orchestration which was implemented using Workflow Foundation 4 of .NET. The obtained results allowed us to verify that the use of integration schemes based on SOAs reduces the system integration time and is better adapted to industrial robotic cell system integrators.The authors wish to express their gratitude to the Plan Nacional de I+D (FEDER-CICYT, Spanish Government) and to the Universitat Politecnica de Valencia (Spain) for the financing of this work, which was made under the research projects DPI2010-20814-C02-02, DPI2011-28507-C02-01 and PAID/2011/039. In addition, they also want to acknowledge the assistance of Elena Ruiz Gomez for her help in the translation of the article.Valera Fernández, Á.; Gómez Moreno, J.; Sánchez Salmerón, AJ.; Ricolfe Viala, C.; Zotovic Stanisic, R.; Vallés Miquel, M. (2012). Industrial Robot Programming and UPnP Services Orchestration for the Automation of Factories. 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IEEE Software, 28(3), 22-26. doi:10.1109/ms.2011.62Cucinotta, T., Mancina, A., Anastasi, G. F., Lipari, G., Mangeruca, L., Checcozzo, R., & Rusina, F. (2009). A Real-Time Service-Oriented Architecture for Industrial Automation. IEEE Transactions on Industrial Informatics, 5(3), 267-277. doi:10.1109/tii.2009.2027013Delamer, I. M., & Lastra, J. L. M. (2006). Service-Oriented Architecture for Distributed Publish/Subscribe Middleware in Electronics Production. IEEE Transactions on Industrial Informatics, 2(4), 281-294. doi:10.1109/tii.2006.885188Estevez-Ayres, I., Basanta-Val, P., Garcia-Valls, M., Fisteus, J. A., & Almeida, L. (2009). QoS-Aware Real-Time Composition Algorithms for Service-Based Applications. IEEE Transactions on Industrial Informatics, 5(3), 278-288. doi:10.1109/tii.2009.2026422Foster, H., Uchitel, S., Magee, J., & Kramer, J. (2010). An Integrated Workbench for Model-Based Engineering of Service Compositions. 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IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), 41(6), 909-922. doi:10.1109/tsmcc.2011.2107552Veiga, G., Pires, J. N., & Nilsson, K. (2009). Experiments with service-oriented architectures for industrial robotic cells programming. Robotics and Computer-Integrated Manufacturing, 25(4-5), 746-755. doi:10.1016/j.rcim.2008.09.001Veiga, G., Pires, J. N., & Nilsson, K. (2007). ON THE USE OF SERVICE ORIENTED SOFTWARE PLATFORMS FOR INDUSTRIAL ROBOTIC CELLS. IFAC Proceedings Volumes, 40(3), 109-115. doi:10.3182/20070523-3-es-4908.00019WHITLEY, K. N. (1997). Visual Programming Languages and the Empirical Evidence For and Against. Journal of Visual Languages & Computing, 8(1), 109-142. doi:10.1006/jvlc.1996.0030Xu, L. D. (2011). Enterprise Systems: State-of-the-Art and Future Trends. IEEE Transactions on Industrial Informatics, 7(4), 630-640. doi:10.1109/tii.2011.216715

Multi-Agent Modelling of Industrial Cyber-Physical Systems for IEC 61499 Based Distributed Intelligent Automation

Traditional industrial automation systems developed under IEC 61131-3 in centralized architectures are statically programmed with determined procedures to perform predefined tasks in structured environments. Major challenges are that these systems designed under traditional engineering techniques and running on legacy automation platforms are unable to automatically discover alternative solutions, flexibly coordinate reconfigurable modules, and actively deploy corresponding functions, to quickly respond to frequent changes and intelligently adapt to evolving requirements in dynamic environments. The core objective of this research is to explore the design of multi-layer automation architectures to enable real-time adaptation at the device level and run-time intelligence throughout the whole system under a well-integrated modelling framework. Central to this goal is the research on the integration of multi-agent modelling and IEC 61499 function block modelling to form a new automation infrastructure for industrial cyber-physical systems. Multi-agent modelling uses autonomous and cooperative agents to achieve run-time intelligence in system design and module reconfiguration. IEC 61499 function block modelling applies object-oriented and event-driven function blocks to realize real-time adaption of automation logic and control algorithms. In this thesis, the design focuses on a two-layer self-manageable architecture modelling: a) the high-level cyber module designed as multi-agent computing model consisting of Monitoring Agent, Analysis Agent, Self-Learning Agent, Planning Agent, Execution Agent, and Knowledge Agent; and b) the low-level physical module designed as agent-embedded IEC 61499 function block model with Self-Manageable Service Execution Agent, Self-Configuration Agent, Self-Healing Agent, Self-Optimization Agent, and Self-Protection Agent. The design results in a new computing module for high-level multi-agent based automation architectures and a new design pattern for low-level function block modelled control solutions. The architecture modelling framework is demonstrated through various tests on the multi-agent simulation model developed in the agent modelling environment NetLogo and the experimental testbed designed on the Jetson Nano and Raspberry Pi platforms. The performance evaluation of regular execution time and adaptation time in two typical conditions for systems designed under three different architectures are also analyzed. The results demonstrate the ability of the proposed architecture to respond to major challenges in Industry 4.0

A ROS2 based communication architecture for control in collaborative and intelligent automation systems

Collaborative robots are becoming part of intelligent automation systems in modern industry. Development and control of such systems differs from traditional automation methods and consequently leads to new challenges. Thankfully, Robot Operating System (ROS) provides a communication platform and a vast variety of tools and utilities that can aid that development. However, it is hard to use ROS in large-scale automation systems due to communication issues in a distributed setup, hence the development of ROS2. In this paper, a ROS2 based communication architecture is presented together with an industrial use-case of a collaborative and intelligent automation system.Comment: 9 pages, 4 figures, 3 tables, to be published in the proceedings of 29th International Conference on Flexible Automation and Intelligent Manufacturing (FAIM2019), June 201