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- Virtualization and monitoring of a modular and self-organized multi-agent conveyor systemPublication . Melo, Victória; Leitão, Paulo; Barbosa, José; Vallim, MarcosThe 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.
- Self-organized cyber-physical conveyor system using multi-agent systemsPublication . Leitão, Paulo; Barbosa, José; Funchal, Gustavo Silva; Melo, VictóriaThe 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.
- A fuzzy logic approach for self-managing energy efficiency in IoT nodesPublication . Melo, Victória; Funchal, Gustavo Silva; Queiroz, Jonas; Leitão, PauloThe collection and analysis of data assume a crucial importance in the digital transformation era. Internet of Things (IoT) technologies allow to gather data from heterogeneous sources and make them available for data-driven systems aiming, e.g., monitoring, diagnosis, prediction and optimization. Several applications require that these IoT nodes be located remotely without connection to the electrical grid and being powered by batteries or renewable sources, thus requiring a more efficient management of the energy consumption in their operation. This paper aims to study and develop intelligent IoT nodes that embed Artificial Intelligence techniques to optimize their operation in terms of energy consumption when operating in constrained environments and powered by energy harvesting systems. For this purpose, a Fuzzy Logic system is proposed to determine the optimal operation strategy, considering the node’s current resource demands, the current battery condition and the power charge expectation. The proposed approach was implemented in IoT nodes measuring environmental parameters and placed in a university campus with Wi-Fi coverage. The achieved results show the advantage of adjusting the operation mode taking into consideration the battery level and the weather forecasts to increase the energy efficiency without compromising the IoT nodes’ functionalities and QoS.
- Monitoring electrical and operational parameters of a stamping machine for failure predictionPublication . Pecora, Pedro; Garcia, Fernando Feijoo; Melo, Victória; Leitão, Paulo; Pellegri, UmbertoGiven the industrial environment, the production efficiency is the ultimate goal to achieve a high standard. Any deviation from the standard can be costly, e.g., a malfunction of a machine in an assembly line tends to have a major setback in the overall factory efficiency. The data value brought by the advent of Industry 4.0 re-shaped the way that processes and machines are managed, being possible to analyse the collected data in real-time to identify and prevent machine malfunctions. In this work, a monitoring and prediction system was developed on a cold stamping machine focusing on its electrical and operational parameters, based on the Digital Twin approach. The proposed system ranges from data collection to visualization, condition monitoring and prediction. The collected data is visualized via dashboards created to provide insights of the machine status, alongside with visual alerts related to the early detection of trends and outliers in the machine’s operation. The analysis of the current intensity is carried out aiming to predict failures and warn the maintenance team about possible future disturbances in the machine condition.
- Digital twin experiments focusing virtualisation, connectivity and real-time monitoringPublication . Pires, Flávia; Melo, Victória; Almeida, João; Leitão, PauloIndustry 4.0 is re-shaping the manufacturing world, and amongst the several associated emerging methods and technologies, Digital Twin is becoming a popular approach both in industry and academia. However, the lack of knowledge about the characteristics, functionalities, best practices and benefits that it can provide, especially for small and medium enterprises, constraints its wider adoption. The use of real applications and demonstrators can contribute to exposing stakeholders to these new and innovative technologies and approaches, showing the applicability of Digital Twins. This paper presents several experiments in implementing Digital Twin for automation scenarios, considering different technologies and functionalities, namely in terms of virtualisation, connectivity and monitoring. Lessons learnt and challenges are also provided as a result of the experimental implementations.
- Design of an ISO 23247 Compliant Digital Twin for an Automotive Assembly LinePublication . Melo, Victoria; Barbosa, José; Mota, Gonçalo; Prieta Pintado, Fernando De la; Leitão, PauloThe integration of Industry 4.0 (I4.0) technologies is transforming various society sectors, and particularly the manufacturing sector, promoting a digital transformation that fosters smart and interconnected systems. The Digital Twin (DT) acts as a key component in the digital transformation landscape and its integration with I4.0 technologies paves the way for the implementation of Zero Defect Manufacturing strategies. A spotlight on the automotive industry underscores the power of DT applications for real-time defect detection and improvement of product quality and process efficiency. However, the proper DT implementation, contributing to their integration and interoperability, requires the compliance with standards and reference architectures. Having this in mind, this paper describes the design of a DT architecture compliant with the ISO 23247 standard and aligned with the RAMI 4.0 to cover the dimensional measurement process comprising inspection stations placed in the body shop area of an automotive assembly line. This implementation enables the real-time and early identification of defects along the assembly process, allowing to prevent their occurrence at a single stage and their propagation to downstream processes.
- Positioning Cyber-Physical Systems and Digital Twins in Industry 4.0Publication . Pires, Flávia; Melo, Victoria; Queiroz, Jonas; Moreira, António Paulo G. M.; Prieta Pintado, Fernando De la; Estevez, Elisabet; Leitão, PauloIndustry 4.0 has brought innovative concepts and technologies that have greatly improved the development of more intelligent, flexible and reconfigurable systems. Two of these concepts, Cyber-Physical Systems (CPSs) and Digital Twins (DTs), have gained significant attention from various stakeholders, e.g., researchers, industry practitioners, and governmental organizations. Both are vital to support the digitalisation of products, machines, and systems, and they focus on the integration of physical and cyber processes, where one affects the other through feedback loops. Having this in mind, this paper aims to better understand how CPS and DT are correlated, particularly exploring their similarities and differences, their positioning within the Industry 4.0 paradigm, and their convergence to develop Industry 4.0 solutions. Some research challenges to develop Industry 4.0 solutions by integrating these concepts are also discussed.
- Alignment of digital twin systems with the RAMI 4.0 model using multi-agent systemsPublication . Melo, Victoria; Prieta Pintado, Fernando De la; Leitão, PauloThe Digital Twin approach has emerged in the Industry 4.0 context to perform the design, virtual commissioning and optimization of processes and machines, considering the simulation model feed with real-time data, and articulated with AI data-driven algorithms to extract value and knowledge. The digital Twin can be seen as a way to proceed with the digitalization of production assets, covering the layers dimension defined by the RAMI 4.0 model. However, a pertinent question is related to understand the relationship between the Digital Twin concept and the other two dimensions of the RAMI 4.0 model, and particularly the way to address the distributed nature exhibited by the hierarchy levels and the life-cycle management defined by the life-cycle value stream dimension. Having this in mind, this paper aims to analyse the coverage of the Digital Twin concept according to the three dimensions of the RAMI 4.0 model, particularly considering the inherent capabilities of Multi-agent Systems to support the development of more distributed and pro-active Digital Twin ecosystems that cover the life-cycle management, facing the demands established by Industry 4.0 compliant solutions.
- Machine vision to empower an intelligent personal assistant for assembly tasksPublication . Talacio, Matheus Teixeira; Funchal, Gustavo Silva; Melo, Victória; Piardi, Luis; Vallim, Marcos; Leitão, PauloIn the context of the fourth industrial revolution, the integration of human operators in emergent cyber-physical systems assumes a crucial relevance. In this context, humans and machines can not be considered in an isolated manner but instead regarded as a collaborative and symbiotic team. Methodologies based on the use of intelligent assistants that guide human operators during the execution of their operations, taking advantage of user friendly interfaces, artificial intelligence (AI) and virtual reality (VR) technologies, become an interesting approach to industrial systems. This is particularly helpful in the execution of customised and/or complex assembly and maintenance operations. This paper presents the development of an intelligent personal assistant that empowers operators to perform faster and more cost-effectively their assembly operations. The developed approach considers ICT technologies, and particularly machine vision and image processing, to guide operators during the execution of their tasks, and particularly to verify the correctness of performed operations, contributing to increase productivity and efficiency, mainly in the assembly of complex products.
- An intrusion detection system dataset for a multi-agent cyber-physical conveyor systemPublication . Funchal, Gustavo Silva; Zahid, Farzana; Melo, Victoria; Kuo, Matthew M.Y.; Pedrosa, Tiago; Sinha, Roopak; Prieta Pintado, Fernando De la; Leitão, PauloIndustry 4.0 is built upon the foundation of connecting devices and systems via Internet of Things (IoT) technologies, with Cyber-Physical Systems (CPS) serving as the backbone infrastructure. Although this approach brings numerous benefits like improved performance, responsiveness and reconfigurability, it also introduces security concerns, making devices and systems vulnerable to cyber attacks. There is a need for effective techniques to protect these systems, and the availability of datasets becomes essential to support the development of such techniques. This paper presents a dataset based on the collection of traffic information exchanged in a self-organizing conveyor system using the multi-agent systems (MAS) architecture and containing various intelligent conveyor modules. The dataset comprises data collected at the network and agent levels under normal system operation, denial of service (DoS) attacks, and malicious agent attacks. An intrusion detection system that integrates Fast Fourier Transform (FFT) and Machine Learning (ML) analysis is developed to demonstrate the utility of this dataset.