Industry 4.0 and Industrial Internet of Things (IIoT) are promoting the connection of millions of devices, that once were seen as unconnectable, into a huge network, to be used in a large number of applications, from autonomous vehicles to industrial control systems, passing through building automation systems. These paradigm rely on the adoption of Cyber Physical Systems complemented with Internet of Things (IoT) technologies and artificial intelligence techniques. These type of systems are responsible for collecting, processing and exchanging a vast amount of data, and for that reason, it is imperative to assure data integrity and protection against malicious modifications and attacks to ensure a safe and reliable operation. Data thefts and cyber attacks in general represent a significant danger, however, cyber attacks on IoT systems can be specially critical due to their proximity with humans, enhancing the risk of physical damage. This paper highlights the importance of securing these systems, pursuing a safer operation, having in mind the amount of security vulnerabilities found in embedded devices. For this purpose, this article studies possible security threats and weakness in two case studies coming from different IoT domains, i.e. building automation and factory automation, while seeking for solutions to improve these systems’ security.

In the 4th Industrial Revolution era, automation processes operate in a more modular, flexible, and reconfigurable manner, leveraging decentralized decision-making and distributed control. As the backbone of this revolution lies the Cyber-physical Production System (CPPS) concept, which emphasizes the strong interlink and interdependence of the digital/cyber and physical components. It requires the use of a technology capable of incorporating intelligence through the entities in a decentralized manner. IEC-61499 Function Blocks technology stands out as a suitable approach to implementing distributed automation control systems. This work presents the development of a dynamic and on-the-fly reconfiguration conveyor transfer system based on the IEC-61499 standard, that automatically adapts its operation to face changes in the number and position of the conveyor modules. For this purpose, the developed control system considers a Python-based Function Block (FB) network using the DINASORE framework, capable of effectively communicating between system components and identifying changes in real time. The experimental tests showed promising results regarding the system’s ability to adapt to condition changes automatically and on the fly, as well as its scalability and robustness.

The adoption of industrial cyber-physical systems is facing several challenges, with artificial intelligence and self-organization techniques assuming critical aspects to be considered in the deployment of such solutions to support the dynamic evolution and adaptation to condition changes. This paper describes the implementation of a modular, flexible and self-organized cyber-physical conveyor system build up with different individual modular and intelligent transfer modules. For this purpose, multi-agent systems are used to distribute intelligence among transfer modules supporting pluggability and modularity, complemented with self-organization capabilities to achieve a truly self-reconfigurable system. Furthermore, Internet of Things and Artificial Intelligence technologies are used to enable the real-time monitoring of the system, aiming the detection and prevention of anomalies in advance, and to enable the protection from possible external threats.

One main foundation of the Industry 4.0 is the connectivity of devices and systems using Internet of Things technologies, where Cyber-physical systems (CPS) act as the backbone infrastructure based on distributed and decentralized structures. CPS requires the use of Artificial Intelligence (AI) techniques, such as Multi-Agent Systems (MAS), allowing the incorporation of intelligence into the CPS through autonomous, proactive and cooperative entities. The adoption of this new generation of systems in the industrial environment opens new doors for various attacks that can cause serious damage to industrial production systems. This work presents the development of security mechanisms for systems based on MAS, where these mechanisms are used in an experimental case study that consists of a multiagent cyber-physical conveyor system. For this purpose, simple security mechanisms were employed in the system, such as user authentication, signature and message encryption, as well as other more complex mechanisms, such as machine learning techniques that allows the agents to be more intelligent in relation to the exchange of messages protecting the system against attacks, through the classification of the messages as reliable or not, and also an intrusion detection system was carried out. Based on the obtained results, the efficient protection of the system was reached, mitigating the main attack vectors present in the system architecture.

The PERFoRM project, an innovation action promoted within the scope of the EU Horizon 2020 program, advocates the use of an Industrie 4.0 compliant system architecture for the seamless reconfiguration of robots and machinery. The system architecture re-uses the innovative results from previous successful R & D projects on distributed control systems domain, such as SOCRADES, IMC-AESOP, GRACE and IDEAS. This paper, after describing the main pillars of the PERFoRM system architecture, focuses on mapping the system architecture into four industrial use cases aiming to validate the system architecture design before its deployment in the real environments.

Cyber-Physical Systems (CPS) are devoted to be the main participants in Industry 4.0 (I4.0) solutions. In recent years, many authors have focused their efforts on making proposals for the design and implementation of CPS based on different digital technologies. However, the comparative evaluation of these I4.0 solutions is complex, since there is no uniform criterion when it comes to defining the test scenarios and the metrics to assess them. This paper presents a technology-independent CPS demonstrator for benchmarking I4.0 solutions. To that end, a set of testing scenarios, Key Performance Indicators and services were defined considering the available automation cells setup. The proposed demonstrator has been used to test an I4.0 solution based on a Multi-agent Systems (MAS) approach.

Multi-stage manufacturing, typical in important industrial sectors, is inherently a complex process. The application of the zero defect manufacturing (ZDM) philosophy, together with recent technological advances in cyber-physical systems (CPS), presents significant challenges and opportunities for the implementation of new methodologies towards the continuous system improvement. This paper introduces the main principles of a multi-agent CPS aiming the application of ZDM in multi-stage production systems, which is being developed under the EU H2020 GO0D MAN project. In particular, this paper describes the MAS architecture that allows the distributed data collection and the balancing of the data analysis for monitoring and adaptation among cloud and edge layers, to enable the earlier detection of process and product variability, and the generation of new optimized knowledge by correlating the aggregated data.

In the last years, many organizations intend to convert their existing production systems towards ones that are characterized by adaptability, openness, flexibility and modularity. This requires a redesign of existing information processing systems especially related to control, leading possibly to the implementation of Cyber-Physical Production Systems (CPPS). However, the implementation of new control technologies will have a direct impact on the normal operational status of production while engineers will also face several challenges and obstacles in adopting intelligent automation systems. New step-wise migration strategies are required to holistically support industries in their journey towards CPPS taking into account technical, economic and social aspects. This work describes the definition of a migration approach for innovative production systems, particularly those CPPS that are developed under the PERFoRM ecosystem, establishing guidelines for a smooth migration from a traditional system to agile plug-and-produce systems in a secure and efficient way. The designed migration approach comprises five phases, namely Preparation, Options Investigation, Design, Implementation and Deployment, sustained by three different migration strategies, namely One-Shot, Parallel and Phased. The modelling of the migration process uses the Petri nets formalism taking advantage of its inherent capabilities to synthesize the process specifications but also to verify, simulate and validate the correctness of the system specifications during the design phase.

Industrie 4.0 principles demand increasing flexibility and modularity for automated production systems. Current system architectures provide an isolated view of specific applications and use cases, but lack a global, more generic approach. Based on the specific architectures of two EU projects and one German Industrie 4.0 project, a generic system architecture is proposed. This system architecture features the strengths of the three isolated proposals, such as cross-enterprise data sharing, service orchestration, and real-time capabilities, and can be applied to a wide field of applications. Future research should be directed towards considering the applicability of the architecture to other equal applications.

Smart parking systems are promising solutions for a set of traffic-related problems in major cities across the world. The goal of those systems is to guide users through paths in which they spend less time, resources, and release fewer greenhouse gases to find a parking spot. To this end, deployers develop Cyber-physical Systems that generally comprise embedded electronics materials, Internet of Things technologies, and Artificial Intelligence concepts. This work combines ESP8266 microcontrollers and Raspberry Pi microprocessors through MQTT communication protocol to implement its architecture, a few possible different options for the actuator are also presented, and a project for the power supply by lowcurrent photovoltaic panels is documented. Therefore, the goal is to work over some options and ideas for the physical implementation of the low-level electronics physical stage of a smart parking Cyber-physical System. The results include validated actuator options, a small photovoltaic generation sizing, and the deployment of a microcontroller routine capable of properly operate as a physical asset controller enabling scalability.

Industry 4.0 vision and its mandated digital transformation are radically reshaping the way business is carried out and the way overall industrial processes and collaborations are operating. In this work, the objective is to analyze the current level of adoption of Industry 4.0, via the footprint available in industrial and academic research works. The analysis performed reveals insights on how Industry 4.0 has impacted and is still influencing research and innovation in industrial systems, services, and business approaches. It also reveals pertinent trends on key enabling features, technologies and challenges associated with this 4th industrial revolution, mainly focusing on the pathways for wider industrial adoption of Industry 4.0-compliant technologies and solutions.

Cyber-Physical Systems (CPSs) are increasingly important in everyday applications including the latest mobile devices, power grids and intelligent buildings. CPS functionality has intrinsic characteristics including considerable heterogeneity, variable dynamics, and complexity of operation. These systems also typically have insufficient resources to satisfy their full demand for specialized services such as data edge storage, data fusion, and reasoning. These novel CPS characteristics require new management strategies to support the resilient global operation of CPSs. To reach this goal, we propose a Software Defined Networking based solution scaled out by Network Function Virtualization modules implemented as distributed management agents. Considering the obvious need for orchestrating the distributed agents towards the satisfaction of a common set of global CPS functional goals, we analyze distinct incentive strategies to enact a cooperative behavior among the agents. The repeated operation of each agent's local algorithm allows that agent to learn how to adjust its behavior following both its own experience and observed behavior in neighboring agents. Therefore, global CPS management can evolve iteratively to ensure a state of predictable and resilient operation.

This dissertation aims to design and implement a monitoring and control system for a small-scale production system, guided by the imperatives of Cyber-Physical Systems (CPS) and Industry 4.0. One of the main objectives of Industry 4.0 is the connectivity of devices and systems using Internet of Things (IoT) technologies, and CPS that acts as the backbone of an infrastructure based on distributed and decentralized structures. CPS requires the use of Distributed Artificial Intelligence (DAI) techniques, such as agents and Multi-Agent Systems (MAS). The most fundamental concept of agents is to view them as entities that emulate human-like attributes, such as decision-making, intention, and perception. Agents have actions, behaviors, beliefs, intentions, and desires just like humans. CPS requires the use of MAS, allowing the incorporation of intelligence into the CPS through autonomous, proactive, and cooperative actions. The case study focuses on a small-scale production system, consisting of an IRB 1400 ABB robot, two punching machines, and two indexed lines supplied by FischertechnikTM which runs in a Modicon M340 PLC. The dissertation aims to develop an MAS in JADE to control the production system, with each device considered as an agent. The agents communicate with each other and report their current status, actions, and behaviors through messages formatted according to the FIPA-ACL specification. A classic approach will be adopted: requirements analysis, MAS modeling, implementation, and testing.

Cyber-physical systems are an emergent paradigm to design complex, adaptive and smart systems, combining computational applications with physical hardware devices. Multi-agent systems play an important role in such systems to provide flexibility, robustness and adaptation, but their alignment will require the integration of agents with physical devices. This process is usually complex and time consuming due to the proprietary protocols provided by the hardware automation devices. This paper describes the deployment of an agent-based system in a small-scale flexible production system composed by a set of heterogeneous automation devices, such as programmable logic controllers and robots.

Cyber-physical systems are a network of integrated computational decisional com-ponents and physical elements. The integration of computational decisional components with the heterogeneous physical automation systems and devices is not transparent and constitutes a critical challenge for the success of this approach. The objective of the paper is to describe an approach to establish standard interfaces based on the use of the ISO 9506 Manufacturing Mes-sage Specification international standard. The proposed approach is exemplified by the con-struction of a robotic cyber-physical production component that is plug-in in a cyber-physical system for a small-scale production system based on Fischertechnik systems.

Presently, many industries are facing strong challenges related to the demand of customized and high-quality products. These pressures lead to internal company's conflicts where current production systems have a rigid structure, forcing the company into a organization stall when a fast product change is required. Therefore, the need to smoothly migrate traditional systems into more feature-rich and cost-effective systems, namely Cyber-Physical Production Systems (CPPS), became a highly discussed topic. PERFoRM project focuses the conceptual transformation of existing production systems towards plug\&produce ones to achieve flexible and reconfigurable manufacturing environments. In particular, the smooth migration process is considered crucial to effectively transpose existing production systems into truly CPPS. This paper describes the use of Petri nets to design the migration process under the PERFoRM perspective, taking advantage of its inherent capabilities to design, analyze, simulate and validate such complex processes.

Cyber-Physical Systems (CPS) is an emergent approach that focuses on the integration of computational applications with physical devices, being designed as a network of interacting cyber and physical elements. CPS control and monitor real-world physical infrastructures and thus is starting having a high impact in industrial automation. As such design, implementation and operation of CPS and management of the resulting automation infrastructure is of key importance for the industry. In this work, an overview of key aspects of industrial CPS, their technologies and emerging directions, as well as challenges for their implementation is presented. Based on the hands-on experiences gathered from four European innovation projects over the last decade (i.e. SOCRADES, IMC-AESOP, GRACE and ARUM), a key challenges have been identified and a prioritization and timeline are pointed out with the aim to increase Technology Readiness Levels and lead to their usage in industrial automation environments.

This paper describes the development of a multiagent system (MAS) to support the implementation of zero-defect manufacturing strategies in multi-stage production systems. The MAS infrastructure, combined with on-line inspection tools, data analytics and knowledge generation, constitutes a suitable approach to integrate process and quality control in multi-stage environments. This will allow the early detection of product defects, the adaptation to operating condition changes and the optimisation of manufacturing processes. This type of integrated management structure is aligned with a zero-defect manufacturing production model which is of paramount importance in the actual state-of-the-art manufacturing paradigms. As a proof of concept, the devised manufacturing supervision model was deployed into an experimental multi-stage system that run a set of several tests on electrical motors. The agent-based solution was implemented using the JADE framework and the exchange of information structured by proper data models and industrial based Internet-of-Things and Machine-to-Machine technologies, such as OPC-UA, REST and JSON. The obtained results demonstrate the suitability of the devised integrated management model as a vehicle to achieve dynamic and continuous system improvement in multi-stage manufacturing environments.

The digital transformation that is taking place worldwide in the context of Industry 4.0 stimulates the emergence of new concepts and technologies and is reshaping the manufacturing world. As a result, the Digital Twin concept is gaining more and more momentum. In this sense, the creation of a virtual copy of the physical system provides a connection between the real and virtual systems to collect, analyze and simulate data in the virtual model to improve the performance of the real system. This work presents the development of virtualization of a modular and self-organized transport system, based on the use of Cyber-Physical Systems (CPS) and Multi-Agent Systems (MAS), to ensure the monitoring of its operation and allow the early detection of failures through real-time analysis of data collected from the physical system. For this purpose, Internet of Things (IoT) tools and technologies were used, such as Node-RED and the Message Queuing Telemetry Transport (MQTT) communication protocol, and the storage of collected data and cyber-security issues related to the use of IoT technologies during the data collection, suggesting the implementation of solutions to avoid possible threats, such as user authentication and data encryption. Among the results obtained, the control panel displays system data in real-time, in addition to providing statistical information, and supports dynamic monitoring of the transport system’s condition operation, generating alerts through the implementation of control rules.

Rapid technology advances and increasing digitalization bring new opportunities but also put new challenges to modern production systems. Industrial agent concepts and technologies can be used to address the needs of modern Cyber-Physical Production Systems (CPPS). To do so, their interplay, especially in industrial settings, needs to be better understood and assessed. Key directions for investigations that are relevant for industrial agent based CPPS are analyzed in this work, mainly the design patterns, interfaces between agents and CPPS, metrics to evaluate the quality of agent based CPPS, and distributed intelligence implemented in or by agents. Although efforts exist both in agent and CPPS domains, their amalgamation still has several aspects that are under-investigated, especially when considering large-scale systems of CPPS, and the proposed four directions discussed in this work, seem promising to address several of the key underlying challenges.