128 research outputs found

    Charlie and the CryptoFactory: Towards Secure and Trusted Manufacturing Environments

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    The modernisation that stems from Industry 4.0 started populating the manufacturing sector with networked devices, complex sensors, and a significant proportion of physical actuation components. However, new capabilities in networked cyber-physical systems demand more complex infrastructure and algorithms and often lead to new security flaws and operational risks that increase the attack surface area exponentially. The interconnected nature of Industry 4.0-driven operations and the pace of digital transformation mean that cyber-attacks can have far more extensive effects than ever before. Based on that, the core ideas of this paper are driven by the observation that cyber security is one of the key enablers of Industry 4.0. Having this in mind, we propose CryptoFactory – a forward looking design of a layered-based architecture that can be used as a starting point for building secure and privacy-preserving smart factories. CryptoFactory aims to change the security outlook in smart manufacturing by discussing a set of fundamental requirements and functionality that modern factories should support in order to be resistant to both internal and external attacks. To this end, CryptoFactory first focuses on how to build trust relationships between the hardware devices in the factory. Then, we look on how to use several cryptographic approaches to allow IoT devices to securely collect, store and share their data while we also touch upon the emerging topic of secure and privacy-preserving communication and collaboration between manufacturing environments and value chains. Finally, we look into the problem of how to perform privacy-preserving analytics by leveraging Trusted Execution Environments and the promising concept of Functional Encryption

    A layered middleware for ot/it convergence to empower industry 5.0 applications

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    We are still in the midst of Industry 4.0 (I4.0), with more manufacturing lines being labeled as smart thanks to the integration of advanced ICT in Cyber–Physical Systems (CPS). While I4.0 aims to provision cognitive CPS systems, the nascent Industry 5.0 (I5.0) era goes a step beyond, aiming to build cross-border, sustainable, and circular value chains benefiting society as a whole. An enabler of this vision is the integration of data and AI in the industrial decision-making process, which does not exhibit yet a coordination between the Operation and Information Technology domains (OT/IT). This work proposes an architectural approach and an accompanying software prototype addressing the OT/IT convergence problem. The approach is based on a two-layered middleware solution, where each layer aims to better serve the specific differentiated requirements of the OT and IT layers. The proposal is validated in a real testbed, employing actual machine data, showing the capacity of the components to gracefully scale and serve increasing data volumes

    Goal-driven context-sensitive production processes : a case study using BPMN

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    The Fourth Industrial Revolution, also known as Industry 4.0 or Industrial Internet, predicts that Smart Factories driven by Internet of Things (IoT) and Cyber-Physical Systems, will reinvent the traditional manufacturing industry into a digitalized, a context-aware, and an automated manufacturing that will flourish with contemporary Information and Communication Technology (ICT). As the IoT are being deployed across production cites of the manufacturing companies, the need of decision making inside a business process based upon the received contextual data such as employee availability, machine status, etc. from the execution environment has transpired. Production processes need to be updated and optimized frequently to stay competitive in the market. Context-sensitive Adaptive Production Processes is an adept concept that illustrates how a business process can be context-sensitive keeping itself aligned with the abstract organizational goals. The notion of Context-sensitive Adaptive Production Processes leads us to Context-sensitive Execution Step (CES), a logical construct, that encompasses multiple alternative processes, albeit the best-fitting alternative can only be selected, optimized, and executed in runtime. Realization of the context-sensitive business processes requires a model-driven approach. Being Business Process Model and Notation (BPMN) the de-facto standard for business processes modeling, business experts of manufacturing companies can use custom CES construct of BPMN to model and execute context-sensitive business processes in a model-driven approach. This case study is based upon a scenario where there exists multiple alternatives to achieve the same goal in production, nevertheless all the alternatives are not suitable at a certain point of time as changes in business objectives and execution environment makes adaption tougher. Properties of intelligent production processes are different from traditional processes. Such properties along with the scrutinized properties of standard BPMN facilitates modeling CES integrated processes in BPMN. From the requirements inferred from these properties, standard BPMN is extended with extensions such that context-sensitive business processes can be modeled and executed seamlessly. Developed extensions include a new type of process construct and a new type of process definition that are technology agnostic. Thus, CES approach provides a comprehensive solution that makes production processes contextsensitive as well as goal-driven in unison

    Machine Tool Communication (MTComm) Method and Its Applications in a Cyber-Physical Manufacturing Cloud

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    The integration of cyber-physical systems and cloud manufacturing has the potential to revolutionize existing manufacturing systems by enabling better accessibility, agility, and efficiency. To achieve this, it is necessary to establish a communication method of manufacturing services over the Internet to access and manage physical machines from cloud applications. Most of the existing industrial automation protocols utilize Ethernet based Local Area Network (LAN) and are not designed specifically for Internet enabled data transmission. Recently MTConnect has been gaining popularity as a standard for monitoring status of machine tools through RESTful web services and an XML based messaging structure, but it is only designed for data collection and interpretation and lacks remote operation capability. This dissertation presents the design, development, optimization, and applications of a service-oriented Internet-scale communication method named Machine Tool Communication (MTComm) for exchanging manufacturing services in a Cyber-Physical Manufacturing Cloud (CPMC) to enable manufacturing with heterogeneous physically connected machine tools from geographically distributed locations over the Internet. MTComm uses an agent-adapter based architecture and a semantic ontology to provide both remote monitoring and operation capabilities through RESTful services and XML messages. MTComm was successfully used to develop and implement multi-purpose applications in in a CPMC including remote and collaborative manufacturing, active testing-based and edge-based fault diagnosis and maintenance of machine tools, cross-domain interoperability between Internet-of-things (IoT) devices and supply chain robots etc. To improve MTComm’s overall performance, efficiency, and acceptability in cyber manufacturing, the concept of MTComm’s edge-based middleware was introduced and three optimization strategies for data catching, transmission, and operation execution were developed and adopted at the edge. Finally, a hardware prototype of the middleware was implemented on a System-On-Chip based FPGA device to reduce computational and transmission latency. At every stage of its development, MTComm’s performance and feasibility were evaluated with experiments in a CPMC testbed with three different types of manufacturing machine tools. Experimental results demonstrated MTComm’s excellent feasibility for scalable cyber-physical manufacturing and superior performance over other existing approaches

    Increase the adoption of Agent-based Cyber-Physical Production Systems through the Design of Minimally Invasive Solutions

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    During the last few years, many approaches were proposed to offer companies the ability to have dynamic and flexible production systems. One of the conventional ap-proaches to solving this problem is the implementation of cyber-physical production sys-tems using multi-agent distributed systems. Although these systems can deal with several challenges faced by companies in this area, they have not been accepted and used in real cases. In this way, the primary objective of the proposed work is to understand the chal-lenges usually found in the adoption of these solutions and to develop a strategy to in-crease their acceptance and implementation. Thus, the document focuses on the design and development of cyber-physical produc-tion systems based on agent approaches, requiring minimal changes in the existing pro-duction systems. This approach aims of reducing the impact and the alterations needed to adopt those new cyber-physical production systems. Clarifying the subject, the author presents a definition of a minimal invasive agent-based cyber-physical production system and, the functional requirements that the designers and developers must respect to imple-ment the new software. From these functional requirements derived a list of design princi-ples that must be fulfilled to design and develop a system with these characteristics. Subsequently, to evaluate solutions that aim to be minimally invasive, an evaluation model based on a fuzzy inference system is proposed, which rank the approaches accord-ing to each of the design principles and globally. In this way, the proposed work presents the functional requirements, design principles and evaluation model of minimally invasive cyber-physical production systems, to increase the adoption of such systems

    Machine Tool Communication (MTComm) Method and Its Applications in a Cyber-Physical Manufacturing Cloud

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    The integration of cyber-physical systems and cloud manufacturing has the potential to revolutionize existing manufacturing systems by enabling better accessibility, agility, and efficiency. To achieve this, it is necessary to establish a communication method of manufacturing services over the Internet to access and manage physical machines from cloud applications. Most of the existing industrial automation protocols utilize Ethernet based Local Area Network (LAN) and are not designed specifically for Internet enabled data transmission. Recently MTConnect has been gaining popularity as a standard for monitoring status of machine tools through RESTful web services and an XML based messaging structure, but it is only designed for data collection and interpretation and lacks remote operation capability. This dissertation presents the design, development, optimization, and applications of a service-oriented Internet-scale communication method named Machine Tool Communication (MTComm) for exchanging manufacturing services in a Cyber-Physical Manufacturing Cloud (CPMC) to enable manufacturing with heterogeneous physically connected machine tools from geographically distributed locations over the Internet. MTComm uses an agent-adapter based architecture and a semantic ontology to provide both remote monitoring and operation capabilities through RESTful services and XML messages. MTComm was successfully used to develop and implement multi-purpose applications in in a CPMC including remote and collaborative manufacturing, active testing-based and edge-based fault diagnosis and maintenance of machine tools, cross-domain interoperability between Internet-of-things (IoT) devices and supply chain robots etc. To improve MTComm’s overall performance, efficiency, and acceptability in cyber manufacturing, the concept of MTComm’s edge-based middleware was introduced and three optimization strategies for data catching, transmission, and operation execution were developed and adopted at the edge. Finally, a hardware prototype of the middleware was implemented on a System-On-Chip based FPGA device to reduce computational and transmission latency. At every stage of its development, MTComm’s performance and feasibility were evaluated with experiments in a CPMC testbed with three different types of manufacturing machine tools. Experimental results demonstrated MTComm’s excellent feasibility for scalable cyber-physical manufacturing and superior performance over other existing approaches

    A distributed middleware for IT/OT convergence in modern industrial environments

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    The modern industrial environment is populated by a myriad of intelligent devices that collaborate for the accomplishment of the numerous business processes in place at the production sites. The close collaboration between humans and work machines poses new interesting challenges that industry must overcome in order to implement the new digital policies demanded by the industrial transition. The Industry 5.0 movement is a companion revolution of the previous Industry 4.0, and it relies on three characteristics that any industrial sector should have and pursue: human centrality, resilience, and sustainability. The application of the fifth industrial revolution cannot be completed without moving from the implementation of Industry 4.0-enabled platforms. The common feature found in the development of this kind of platform is the need to integrate the Information and Operational layers. Our thesis work focuses on the implementation of a platform addressing all the digitization features foreseen by the fourth industrial revolution, making the IT/OT convergence inside production plants an improvement and not a risk. Furthermore, we added modular features to our platform enabling the Industry 5.0 vision. We favored the human centrality using the mobile crowdsensing techniques and the reliability and sustainability using pluggable cloud computing services, combined with data coming from the crowd support. We achieved important and encouraging results in all the domains in which we conducted our experiments. Our IT/OT convergence-enabled platform exhibits the right performance needed to satisfy the strict requirements of production sites. The multi-layer capability of the framework enables the exploitation of data not strictly coming from work machines, allowing a more strict interaction between the company, its employees, and customers
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