The HORSE framework: A reference architecture for cyber-physical systems in hybrid smart manufacturing

In the Industry 4.0 era, manufacturers strive to remain competitive by using advanced technologies such as collaborative robots, automated guided vehicles, augmented reality support and smart devices. However, only if these technological advancements are integrated into their system context in a seamless way, they can deliver their full potential to a manufacturing organization. This integration requires a system architecture as a blueprint for positioning and interconnection of the technologies. For this purpose, the HORSE framework, resulting from the HORSE EU H2020 project, has been developed to act as a reference architecture of a cyber-physical system to integrate various Industry 4.0 technologies and support hybrid manufacturing processes, i.e., processes in which human and robotic workers collaborate. The architecture has been created using design science research, based on well-known software engineering frameworks, established manufacturing domain standards and practical industry requirements. The value of a reference architecture is mainly established by application in practice. For this purpose, this paper presents the application and evaluation of the HORSE framework in 10 manufacturing plants across Europe, each with its own characteristics. Through the physical deployment and demonstration, the framework proved its goal to be basis for the well-structured design of an operational smart manufacturing cyber-physical system that provides horizontal, cross-functional management of manufacturing processes and vertical control of heterogeneous technologies in work cells. We report on valuable insights on the difficulties to realize such systems in specific situations. The experiences form the basis for improved adoption, further improvement and extension of the framework. In sum, this paper shows how a reference architecture framework supports the structured application of Industry 4.0 technologies in manufacturing environments that so far have relied on more traditional digital technology.     

A blockchain-enabled collaborative intrusion detection framework for SDN-assisted cyber-physical systems

International Journal of Information Security - Cyber-physical systems (CPS) play an important role in our daily lives, such as automotive, medical monitoring, smart grid, industrial control...     

Human modeling and interaction in cyber-physical systems: A reference framework

This study focuses on the question of how humans can be inherently integrated into cyber-physical systems (CPS) to reinforce their involvement in the increasingly automated industrial processes. After a use-case oriented review of the related research literature, a human-integration framework and associated data models are presented as part of a multi-agent IoT middleware called CHARIOT. The framework enables human actors to be semantically represented and registered, together with other IoT entities, in a common service directory, thereby facilitating their inclusion in complex service chains. To validate and evaluate the proposed framework, a user study is conducted on a setup where a human and a robot arm collaborate on a “pick-assemble-place” job on a conveyor belt. Based on the human skill set parameters obtained from the user study, online and offline variants of task assignment on the conveyor belt setup are implemented and analyzed over the presented framework. The results illustrate possible efficiency gains through the consolidated online monitoring and control of all cyber-physical system entities, including human actors.     

An actor-based framework for asynchronous event-based cyber-physical systems

Software and Systems Modeling - In cyber-physical systems like automotive systems, there are components like sensors, actuators, and controllers that communicate asynchronously with each other. The...     

Toward a framework for self-adaptive workflows in cyber-physical systems

Software and Systems Modeling - With the establishment of Cyber-physical Systems (CPS) and the Internet of Things, the virtual world of software and services and the physical world of objects and...     

A physical hash for preventing and detecting cyber-physical attacks in additive manufacturing systems

Cyber-physical security is a major concern in the modern environment of digital manufacturing, wherein a cyber-attack has the potential to result in the production of defective parts, theft of IP, or damage to infrastructure or the operator have become a real threat that have the potential to create bad parts. Current cyber only solutions are insufficient due to the nature of manufacturing environments where it may not be feasible or even possible to upgrade physical equipment to the most current cyber security standards, necessitating an approach that addresses both the cyber and the physical components. This paper proposes a new method for detecting malicious cyber-physical attacks on additive manufacturing (AM) systems. The method makes use of a physical hash, which links digital data to the manufactured part via a disconnected side-channel measurement system. The disconnection ensures that if the network and/or AM system becomes compromised, the manufacturer can still rely on the measurement system for attack detection. The physical hash ensures protection of the intellectual property (IP) associated with both process and toolpath parameters while also enabling in situ quality assurance. In this paper, the physical hash takes the form of a QR code that contains a hash string of the nominal process parameters and toolpath. It is manufactured alongside the original geometry for the measurement system to scan and compare to the readings from its sensor suite. By taking measurements in situ, the measurement system can detect in real-time if the part being manufactured matches the designer’s specification.In this paper, the overall concept and underlying algorithm of the physical hash is presented. A proof-of-concept validation is realized on a material extrusion AM machine, to demonstrate the ability of a physical hash and in situ monitoring to detect the existence (and absence) of malicious attacks on the STL file, the printing process parameters, and the printing toolpath.     

A metamodel for cyber-physical systems

With the advent of the Internet of Things and Industry 4.0 concepts, cyber-physical systems in civil engineering experience an increasing impact on structural health monitoring (SHM) and control applications. Designing, optimizing, and documenting cyber-physical system on a formal basis require platform-independent and technology-independent metamodels. This study, with emphasis on communication in cyber-physical systems, presents a metamodel for describing cyber-physical systems. First, metamodeling concepts commonly used in computing in civil engineering are reviewed and possibilities and limitations of describing communication-related information are discussed. Next, communication-related properties and behavior of distributed cyber-physical systems applied for SHM and control are explained, and system components relevant to communication are specified. Then, the metamodel to formally describe cyber-physical systems is proposed and mapped into the Industry Foundation Classes (IFC), an open international standard for building information modeling (BIM). Finally, the IFC-based approach is verified using software of the official IFC certification program, and it is validated by BIM-based example modeling of a prototype cyber-physical system, which is physically implemented in the laboratory. As a result, cyber-physical systems applied for SHM and control are described and the information is stored, documented, and exchanged on the formal basis of IFC, facilitating design, optimization, and documentation of cyber-physical systems.     

Knowledge framework for intelligent manufacturing systems

Nowadays, competition is experienced not only among companies but among global supply chains and business networks. There is a demand for intelligent world-class solutions capable of reinforcing partnerships and collaborations with an improved cross-cultural understanding. However due to the proliferation of terminology, organizations from similar business environments have trouble cooperating, and are experiencing difficulties exchanging electronically vital information, such as product and manufacturing data, even when using international standards. To address similar interoperability problems, the Intelligent manufacturing systems program () is providing an opportunity to develop industry-led R&D initiatives, building common semantics and integrated solutions. The SMART-fm project was one of those initiatives. It led to the development of the international standard for product data representation and exchange in the furniture sector (ISO 10303-236) and identified the challenge of semantic interoperability which is today a major challenge in modern enterprise integration. This paper presents a knowledge framework to address that challenge and make interoperable intelligent manufacturing systems a reality. It proposes to use semantically enriched international product data standards, and knowledge representation elements as a basis for achieving seamless enterprise interoperability.     

A framework and a simulation generator for kanban-controlled manufacturing systems

A generalized framework for the definition of kanban-controlled manufacturing systems and a simulation generator based on this framework are introduced in this paper. Kanbans are used between and within workstations to trigger product flow or production. The simulation generator is capable of modeling complex manufacturing systems with multiple parts, multiple work centers and multiple processes at each work center. Multiple process definition capability enables users to define convergent and divergent points in a manufacturing system. Several decision rules are defined and incorporated into the generator. The simulation generator can be used as a completely interactive tool that is data-driven and requires no programming skills.     

Big Data and virtualization for manufacturing cyber-physical systems: A survey of the current status and future outlook

The recent advances in sensor and communication technologies can provide the foundations for linking the physical manufacturing facility and machine world to the cyber world of Internet applications. The coupled manufacturing cyber-physical system is envisioned to handle the actual operations in the physical world while simultaneously monitor them in the cyber world with the help of advanced data processing and simulation models at both the manufacturing process and system operational levels. Moreover, a sensor-packed manufacturing system in which each process or piece of equipment makes available event and status information, coupled with market research for true advanced Big Data analytics, seem to be the right ingredients for event response selection and operation virtualization. As a drawback, the resulting manufacturing cyber-physical system will be vulnerable to the inevitable cyber-attacks, unfortunately, so common for the software and Internet-based systems. This reality makes cybersecurity penetration within the manufacturing domain a need that goes uncontested across researchers and practitioners. This work provides a review of the current status of virtualization and cloud-based services for manufacturing systems and of the use of Big Data analytics for planning and control of manufacturing operations. Building on already developed cloud business solutions, cloud manufacturing is expected to offer improved enterprise manufacturing and business decision support. Based on the current state-of-the-art cloud manufacturing solutions and Big Data applications, this work also proposes a framework for the development of predictive manufacturing cyber-physical systems that include capabilities for attaching to the Internet of Things, and capabilities for complex event processing and Big Data algorithmic analytics.     

A decision-making framework for dynamic scheduling of cyber-physical production systems based on digital twins

Nowadays, one important challenge in cyber-physical production systems is updating dynamic production schedules through an automated decision-making performed while the production is running. The condition of the manufacturing equipment may in fact lead to schedule unfeasibility or inefficiency, thus requiring responsiveness to preserve productivity and reduce the operational costs. In order to address current limitations of traditional scheduling methods, this work proposes a new framework that exploits the aggregation of several digital twins, representing different physical assets and their autonomous decision-making, together with a global digital twin, in order to perform production scheduling optimization when it is needed. The decision-making process is supported on a fuzzy inference system using the state or conditions of different assets and the production rate of the whole system. The condition of the assets is predicted by the condition-based monitoring modules in the local digital twins of the workstations, whereas the production rate is evaluated and assured by the global digital twin of the shop floor. This paper presents a framework for decentralized and integrated decision-making for re-scheduling of a cyber-physical production system, and the validation and proof-of-concept of the proposed method in an Industry 4.0 pilot line of assembly process. The experimental results demonstrate that the proposed framework is capable to detect changes in the manufacturing process and to make appropriate decisions for re-scheduling the process.     

SmartVM: a SLA-aware microservice deployment framework

World Wide Web - Software-as-a-Service is becoming the prevalent way of software delivery. The popularisation of microservices architecture and containers has facilitated the efficient development...     

Semantic communications between distributed cyber-physical systems towards collaborative automation for smart manufacturing

Machine-to-machine (M2M) communication is a crucial technology for collaborative manufacturing automation in the Industrial Internet of Things (IIoT)-empowered industrial networks. The new decentralized manufacturing automation paradigm features ubiquitous communication and interoperable interactions between machines. However, peer-to-peer (P2P) interoperable communications at the semantic level between industrial machines is a challenge. To address this challenge, we introduce a concept of Semantic-aware Cyber-Physical Systems (SCPSs) based on which manufacturing devices can establish semantic M2M communications. In this work, we propose a generic system architecture of SCPS and its enabling technologies. Our proposed system architecture adds a semantic layer and a communication layer to the conventional cyber-physical system (CPS) in order to maximize compatibility with the diverse CPS implementation architecture. With Semantic Web technologies as the backbone of the semantic layer, SCPSs can exchange semantic messages with maximum interoperability following the same understanding of the manufacturing context. A pilot implementation of the presented work is illustrated with a proof-of-concept case study between two semantic-aware cyber-physical machine tools. The semantic communication provided by the SCPS architecture makes ubiquitous M2M communication in a network of manufacturing devices environment possible, laying the foundation for collaborative manufacturing automation for achieving smart manufacturing. Another case study focusing on decentralized production control between machines in a workshop also proved the merits of semantic-aware M2M communication technologies.     

A topology and risk-aware access control framework for cyber-physical space

Cyber-physical space is a spatial environment that integrates the cyber world and the physical world, aiming to provide an intelligent environment for users to conduct their day-to-day activities. The interplay between the cyber space and physical space proposes specific security requirements that are not captured by traditional access control frameworks. On one hand, the security of the physical space and the cyber space should be both concerned in the cyber-physical space. On the other hand, the bad results caused by failure in providing secure policy enforcementmay directly affect the controlled physical world. In this paper, we propose an effective access control framework for the cyber-physical space. Firstly, a topology-aware access control (TAAC) model is proposed. It can express the cyber access control, the physical access control, and the interaction access control simultaneously. Secondly, a risk assessment approach is proposed for the policy enforcement phase. It is used to evaluate the user behavior and ensures that the suspicious behaviors executed by authorized users can be handled correctly. Thirdly, we propose a role activation algorithm to ensure that the objects are accessed only by legal and honest users. Finally, we evaluate our approach by using an illustrative example and the performance analysis. The results demonstrate the feasibility of our approach.     

A framework for variation visualization and understanding in complex manufacturing systems

This paper provides a framework that allows industrial practitioners to visualize the most significant variation patterns within their process using three-dimensional animation software. In essence, this framework complements Phase I statistical monitoring methods by enabling users to: (1) acquire detailed understanding of common-cause variability (especially in complex manufacturing systems); (2) quickly and easily visualize the effects of common-cause variability in a process with respect to the final product; and (3) utilize the new insights regarding the process variability to identify opportunities for process improvement. The framework is illustrated through a case study using actual dimensional data from a US automotive assembly plant.     

Resource-efficient cyber-physical systems design: A survey

Many Cyber-Physical Systems (CPSs) in industrial applications are embedded control systems. With the increasing scale and complexity of such system, the resource efficiency in the system design has become an important issue. The resources of CPSs mainly include: computation resource, communication resource and memory resource. The CPSs combine computation, communication and instruction/data storage closely, and realize the combination and coordination of computing resources and physical resources. This paper classifies the existing mainstream research results from three aspect: computation resource, communication resource and memory resource, reviews the research hotspots of each research field, and discusses the urgent problems related to computation resource, communication resource and memory resource in CPSs, as well as the possible research directions in the future.     

制造执行系统柔性应用框架研究

针对制造执行系统应用开发的复杂性,提出了一个制造执行系统的柔性应用框架。在多层服务体系结构的基础上,该应用框架通过运用面向过程的对象分析技术、基于规则的事件服务机制和业务工程分析技术,提供可重构的组织结构、可伸缩的业务流程和可定制的业务规则,使得系统开发和实施的柔性得以提高。同时,运用该柔性框架,对一个实例进行分析和实现。     

A comprehensive co-simulation platform for cyber-physical systems

Cyber-physical systems (CPSs) are the synergy of the physical world with the cyber world. CPSs will bring about unprecedented applications that will enable the monitoring and controlling of the physical environments. CPSs’ further progress necessitates the availability of co-simulation platforms that can capture both the physical and the communication dynamics. In this paper, we build on our previous experiences to build a comprehensive co-simulation platform for CPSs. The newly developed platform enjoys several indispensable features. In the process of discussing the steps to engineer the platform, we present several design alternatives that might prove beneficial in other future tools that combine different simulator environments. We discuss thoroughly why we rule in or rule out each of such alternatives. Then, we validate the developed platform to make sure it works correctly. Finally, we present demonstrative examples showing the capabilities of the platform.     

UML4IoT—A UML-based approach to exploit IoT in cyber-physical manufacturing systems

Internet of Things (IoT) is changing the world. The manufacturing industry has already identified that the IoT brings great opportunities to retain its leading position in economy and society. However, the adoption of the IoT changes the development process of the manufacturing system and raises many challenges. In this paper, the modern manufacturing system is considered as a composition of cyber-physical, cyber and human components, and IoT is used as a glue for their integration as far as their cyber interfaces are concerned. An approach based on a UML profile for the IoT is presented to fully automate the generation process of the IoT-compliant layer that is required for the cyber-physical component to be effectively integrated into the modern IoT manufacturing environment. The approach can also be applied at the source code level specification of the component in case that a UML design specification is not available. A prototype implementation of the myLiqueur production laboratory system is used to demonstrate the applicability and effectiveness of the UML4IoT approach.     

A support-design framework for Cooperative Robots systems in labor-intensive manufacturing processes

Manufacturing processes and industrial systems gradually change their traditional layouts and configurations, preparing to introduce novel integrated human-robot technologies as collaborative robots and exoskeletons. Whether mass customization of lot size and the production mix discourages the adoption of capital-intensive automation, collaborative robots become affordable and effective and a hotspot of the debate on manufacturing systems. This paper provides a novel support-design framework for the cooperative robot system in labor-intensive manufacturing processes to aid layout and task scheduling design. Through an iterative closed-loop methodology, this framework explores the impact of a cooperative robot in a labour-intensive manufacturing system like the production facility of a food service company. The framework leads the designer through the re-layout of the end-of-line, the economic and technical feasibility analyses, using simulation to estimate payback and ergonomics benefits for workers. Within the proposed layout, we state that adopting a cooperative cobot for the end-of-line is affordable and ergonomically convenient without representing a safety threat for workers. The testbed confirms the framework as an enabling tool for human-robot technologies integration in current manufacturing systems under budget and workers-driven constraints.