| 1. |
- Weber, Werner, et al.
(author)
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The EMC2 Project on Embedded Microcontrollers: Technical Progress after two years
- 2016
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Conference paper (other academic/artistic)abstract
- Since April 2014 the Artemis/ECSEL project EMC2 is running and provides significant results. EMC2 stands for “Embedded Multi-Core Systems for Mixed Criticality Applications in Dynamic and Changeable Real-Time Environments”. In this paper we report recent progress on technical work in the different workpackages and use cases. We highlight progress in the research on system architecture, design methodology, platform and operating systems, and in qualification and certification. Application cases in the fields of automotive, avionics, health care, and industry are presented exploiting the technical results achieved.
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| 2. |
- Javed, Salman, 1982-, et al.
(author)
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A Smart Manufacturing Ecosystem for Industry 5.0 using Cloud-based Collaborative Learning at the Edge
- 2023
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In: NOMS 2023-2023 IEEE/IFIP Network Operations and Management Symposium. - : IEEE. - 9781665477178 - 9781665477161
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Conference paper (peer-reviewed)abstract
- In the modern manufacturing industry, collaborative architectures are growing in popularity. We propose an Industry 5.0 value-driven manufacturing process automation ecosystem in which each edge automation system is based on a local cloud and has a service-oriented architecture. Additionally, we integrate cloud-based collaborative learning (CCL) across building energy management, logistic robot management, production line management, and human worker Aide local clouds to facilitate shared learning and collaborate in generating manufacturing workflows. Consequently, the workflow management system generates the most effective and Industry 5.0-driven workflow recipes. In addition to managing energy for a sustainable climate and executing a cost-effective, optimized, and resilient manufacturing process, this work ensures the well-being of human workers. This work has significant implications for future work, as the ecosystem can be deployed and tested for any industrial use case.
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| 3. |
- Javed, Salman, 1982-, et al.
(author)
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An approach towards demand response optimization at the edge in smart energy systems using local clouds
- 2023
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In: Smart Energy. - : Elsevier. - 2666-9552. ; 12
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Journal article (peer-reviewed)abstract
- The fourth and fifth industrial revolutions (Industry 4.0 and Industry 5.0) have driven significant advances in digitalization and integration of advanced technologies, emphasizing the need for sustainable solutions. Smart Energy Systems (SESs) have emerged as crucial tools for addressing climate change, integrating smart grids and smart homes/buildings to improve energy infrastructure. To achieve a robust and sustainable SES, stakeholders must collaborate efficiently through an energy management framework based on the Internet of Things (IoT). Demand Response (DR) is key to balancing energy demands and costs. This research proposes an edge-based automation cloud solution, utilizing Eclipse Arrowhead local clouds, which are based on Service-Oriented Architecture that promotes the integration of stakeholders. This novel solution guarantees secure, low-latency communication among various smart home and industrial IoT technologies. The study also introduces a theoretical framework that employs AI at the edge to create environment profiles for smart buildings, optimizing DR and ensuring human comfort. By focusing on room-level optimization, the research aims to improve the overall efficiency of SESs and foster sustainable energy practices.
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| 4. |
- Javed, Salman, 1982-
(author)
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Approach Towards Engineering Microservice-Oriented Composable Ecosystems for Smart Industries
- 2023
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Licentiate thesis (other academic/artistic)abstract
- The emergence of smart and integrated industrial ecosystems is replacing traditional manufacturing, where operations are more digitalized and automated. For communication and cooperation, these operations require seamless integration of the devices to ensure interoperability in a secure, reliable, and adaptable environment. Designing a solution with these capabilities raises concerns about automation and engineering optimization. More recently, the rapid progression toward Industry 5.0 (I5.0) is further reshaping the landscape of smart industry ecosystems, necessitating innovative engineering and management solutions based on its core values of resilience, sustainability, and human-centricity.This thesis investigates these challenges and requirements by emphasizing adaptable, secure, reliable, composable, and scalable communication in complex industrial ecosystems. Central to this work is a local cloud-based collaboration approach to the design and development of composable ecosystems using microservices, which facilitate the integration of various information technology and operational technology (IT/OT) systems prevalent in smart industries. These encompass industrial and smart home Internet of Things (IoT)-based smart industry ecosystems and smart energy systems. Using the microservice-oriented Eclipse Arrowhead framework, this research provides scalable and adaptable solutions that adhere to the core values of I5.0. This research also bridges the integration gap between smart manufacturing ecosystems and smart home IoT technologies, laying the foundation for interconnected smart factories and improved energy management systems.Collaboration between IT/OT components and stakeholders in smart industry and smart energy ecosystems improves competitiveness, productivity, and informed decision making, thereby filling a critical research gap. The thesis presents a cloud-based collaborative learning (CCL) approach for automated condition monitoring in smart industry ecosystems. The thesis exemplifies the use cases of wind farms and smart manufacturing ecosystems that use CCL to address the issues of dynamic learning and real-time data sharing between various IoT-based IT/OT systems. Unlike traditional smart manufacturing models that focus primarily on automation and cost efficiency, CCL-based and I5.0 core value-driven ecosystems support human-centricity, sustainability, and resilience. Lastly, the thesis investigates the optimization of demand response based on collaboration among stakeholders in smart energy systems using edge-based automation clouds. The proposed approach promotes resilient and sustainable smart city demand response strategies by ensuring human comfort, security, data privacy, and all stakeholder integration in smart energy systems.
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| 5. |
- Javed, Saleha, 1990-, et al.
(author)
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Cloud-based Collaborative Learning (CCL) for the Automated Condition Monitoring of Wind Farms
- 2022
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In: Proceedings 2022 IEEE 5th International Conference on Industrial Cyber-Physical Systems (ICPS). - : Institute of Electrical and Electronics Engineers (IEEE).
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Conference paper (peer-reviewed)abstract
- Modeling Industrial Internet of Things (IIoT) architectures for the automation of wind turbines and farms(WT/F), as well as their condition monitoring (CM) is a growing concept among researchers. Several end-to-end automated cloud-based solutions that digitize CM operations intelligently to reduce manual efforts and costs are being developed. However, establishing robust and secure communication across WT/F is still difficult for the wind energy industry. We propose a fully automated cloud-based collaborative learning (CCL) architecture using the Eclipse Arrowhead Framework and an unsupervised dictionary learning (USDL) CM approach. The scalability of the framework enabled digitization and collaboration across the WT/Fs. Collaborative learning is a novel approach that allows all WT/Fs to learn from each other in real-time. Each turbine has CCL based CM using USDL as micro-services that autonomously perform feature selection and failure prediction to optimize cost, computation, and resources. The fundamental essence of the USDA approach is to enhance the WT/F’s learning and accuracy. We use dictionary distances as a metric for analyzing the CM of WT in our proposed USDL approach. A dictionary indicates an anomaly if its distances increased from the dictionary computed at a healthy state of that WT. Using CCL, a WT/F learns all types of failures that could occur in a similar WT/F, predicts any machinery failure, and sends alerts to the technicians to ensure guaranteed proactive maintenance. The results of our research support the notion that when testing a turbine with dictionaries of all the other turbines, every dictionary converges to similar behavior and captures the fault that occurs in that turbine.
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| 9. |
- Kolluru, Katyayani Kiranmayee, et al.
(author)
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An AAA Solution for Securing Industrial IoT Devices using Next Generation Access Control
- 2018
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Conference paper (peer-reviewed)abstract
- Industry 4.0 is advancing the use of Internet of Things (IoT) devices in industrial applications, which enablesefficient device-to-device (D2D) communication. However, these devices are often heterogeneous in nature, i.e. from different manufacturers, use different protocols, etc. and adds requirements such as security, interoperability, etc.To address these requirements, the Service-Oriented Architecture-Based (SOA) Arrowhead Framework was previously proposed using the concept of local clouds. These local clouds provide a set of mandatory and support core systems to enable industrial automation applications. One of these mandatory core systems is an Authentication, Authorisationand Accounting (AAA) system, which is used to authenticate and provide access control to the devices in a local cloud. In an industrial context, with multiple stakeholders, the AAA mustsupport fine-grain access control. For example, in a distributed control loop, a controller should only have read access to its sensor such as a flow meter and write access to its actuator, such as a valve. The controller should not have access to anyother information besides what is needed to implement the desired functionality. In this work, an NGAC-based AAA solution to achieve fine-grain service level access control between IoT devices has been proposed and implemented. The solution is presented using a district heating use case.
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| 10. |
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| 11. |
- Tripathy, Aparajita, 1993-, et al.
(author)
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Interoperability Between ROS and OPC UA: A Local Cloud-Based Approach
- 2022
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In: Proceedings 2022 IEEE 5th International Conference on Industrial Cyber-Physical Systems (ICPS). - : IEEE.
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Conference paper (other academic/artistic)abstract
- Today’s manufacturing industries use a large suite of protocols and technologies to operate heterogeneous devices and software modules. Some of the most widely used technologies in industrial production are OPC UA (Open Platform CommunicationsUnified Architecture) and ROS (Robot Operating System). Hence, enabling interoperability across these technologies is critical to ensure a smooth production flow. We propose a local cloud-based approach to achieve interoperability between ROSand OPC UA by integrating them with the Eclipse ArrowheadFramework. This integration allows these technologies to operate as independent systems while communicating securely at runtime. In addition to achieving interoperability, this integration supports important industrial aspects such as loose coupling, late binding, and cyber-security, making it a flexible solution.
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| 12. |
- Tripathy, Aparajita, 1993-, et al.
(author)
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OPC UA Service Discovery and Binding in a Service-Oriented Architecture
- 2022
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In: Proceedings 2022 IEEE 5th International Conference on Industrial Cyber-Physical Systems (ICPS). - : IEEE.
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Conference paper (peer-reviewed)abstract
- The OPC UA (Open Platform CommunicationsUnified Architecture) technology is found in many industrial applications as it addresses many of Industry 4.0’s requirements. One of its appeals is its service-oriented architecture. Nonetheless, it requires engineering efforts during deployment and maintenance o bind or associates the correct services to a client or consumer system. We propose the integration of OPC UA with the Eclipse Arrowhead Framework (EAF) to enable automatic service discovery and binding at runtime, reducing delays, costs, and errors. The integration also enables the client system to get the service endpoints by querying the service attributes or metadata. Moreover, this forms a bridge to other industrial communication technologies such as Modbus TCP (TransmissionControl Protocol) as the framework is not limited to a specific protocol. To demonstrate the idea, an indexed line with an industrial PLC (programmable logic controller) with an OPCUA server is used to show that the desired services endpoints are revealed at runtime when querying their descriptive attributes or metadata through the EAF’s Orchestrator system.
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| 13. |
- Tripathy, Aparajita, 1993-
(author)
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Optimizing Smart Industries: Strategies for Efficient System of Systems Development
- 2023
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Licentiate thesis (other academic/artistic)abstract
- The era of extensive digitalization marked by the fourth industrial revolution has ushered in significant advancements in technologies like automation, artificial intelligence, and the Internet of Things (IoT). These innovations are revolutionizing manufacturing processes. Industry 4.0 (I4.0) and the subsequent Industry 5.0 (I5.0) emerged as comprehensive representations of the physical world in the information world, with goals to establish smart factories and promote human-machine coexistence. However, the implementation of I4.0 and I5.0 applications faces challenges related to engineering effort, interoperability, and efficient service discovery and binding.This thesis seeks to address these challenges by exploring potential strategies to develop an efficient System of Systems (SoS) that comprises individual, autonomous systems collaborating to achieve a shared goal. This research examines methods to enhance the efficacy of SoS by refining its engineering procedures, promoting interoperability between standardized protocols, and employing dynamic adaption mechanisms. It aims to achieve automatic service discovery and interoperability between diverse industrial standards by integrating the Eclipse Arrowhead Framework. This IoT framework facilitates secure and seamless communication and collaboration among devices, machines, and systems.Moreover, this work delves into saving energy consumption in distributed SoS environments. The thesis aims to optimize energy usage patterns, diminish peak loads, and bolster energy distribution and stability. This is achieved through the Demand Response (DR) mechanism combined with the Eclipse Arrowhead framework. The overarching objective is to pave the way for flexible production processes characterized by minimal resource waste, optimized energy consumption, and sustainable solutions. Through this endeavor, the thesis contributes to shaping a more efficient, interoperable, and sustainable manufacturing landscape in the context of Industry 4.0 and beyond.
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| 14. |
- Urgese, Gianvito, et al.
(author)
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A SOA-Based Engineering Process Model for the Life Cycle Management of System-of-Systems in Industry 4.0
- 2022
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In: Applied Sciences. - : MDPI. - 2076-3417. ; 12:15
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Journal article (peer-reviewed)abstract
- The evolution of industrial digitalisation has accelerated in recent years with the availability of hyperconnectivity, low-cost miniaturised electronic components, edge computing, and Internet of Things (IoT) technologies. More generally, with these key enablers, the concept of a system of systems (SoS) is becoming a reality in the industry domain. However, due to its complexity, the engineering process model adopted to design, develop, and manage IoT and SoS-based solutions for industry digitalisation is inadequate, inefficient, and frequently unable to manage the digitalisation solution’s entire life cycle. To address these limitations, we propose the Arrowhead Engineering Process (Arrowhead-EP) model and the Value Chain Engineering Process Map (VCEP-map), which explicitly reveal the interactions and dynamics of the engineering processes adopted by multistakeholder use cases in the industry domain. We decomposed and remodeled the engineering process to cover the complete life cycle of an industrial SoS, and we introduced a service-oriented solution intended to efficiently, flexibly, and effectively manage the three assets addressed by RAMI 4.0. The Arrowhead-EP model complemented by the VCEP-map fills the gaps identified in our literature-based analysis and satisfies the requirements of the life cycle management of a typical use case in the Industry 4.0 domain. In this regard, a specific example is used to illustrate the advantages of adopting the proposed engineering solution in a real multistakeholder use case.
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| 15. |
- Urgese, Gianvito, et al.
(author)
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An Engineering Process model for managing a digitalised life-cycle of products in the Industry 4.0
- 2020
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In: Proceedings of IEEE/IFIP Network Operations and Management Symposium 2020. - : IEEE.
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Conference paper (other academic/artistic)abstract
- The Internet of Things (IoT), and more specifically the industrial IoT, is revolutionising industry. This technology has catalyzed the fourth industrial revolution and inspired movements such as Industry 4.0, the Industrial Internet Consortium and Society 5.0. Morphing an industrial process or assembly line to aggregate Internet-connected devices and systems does not complete the picture. The concept penetrates all aspects of the engineering process (EP) which encompasses the full life-cycle of the product/solution. Phases of the EP traditionally tended to be sequential but, with the IoT, can now evolve and influence other phases throughout the product/solution life-cycle. The EU-funded Arrowhead Tools project aims to promote a service-oriented architecture (SOA) to allow tools within each phase of the engineering process to interact with each other. This paper, applies the proposed EP model to a real value chain composed of multiple stakeholders adopting different EPs for the life-cycle management of a Smart Boiler System.
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