Cyber-physical system

About: Cyber-physical system is a research topic. Over the lifetime, 11096 publications have been published within this topic receiving 162489 citations. The topic is also known as: CPS.

A problem-solving ontology for human-centered cyber physical production systems

Abstract: Cyber physical social systems (CPSS) tend to integrate computation with physical processes as well as human and social characteristics. The fusion of cyber, physical, and socio spaces through Industry 4.0 emerges a new type of production systems known as cyber physical production systems (CPPS). CPPS enriches communications among cyber-physical-socio space in the production environment. Utilizing human-centered CPPS in smart factories (ideally) results in a mutual transition from human-machine cooperation to active collaboration, which is characterized by cyber-physical-socio interactions, knowledge exchange and reciprocal learning. The shift from data workers or producers to problem-solver is, therefore, triggered to both humans and CPPS, respectively. Hence, their job roles and responsibilities cannot be independently defined. This paper approaches the collaboration of human and CPPS in problem-solving from the angle of complementarity whereby “human competences” and “CPPS autonomy” together derive supplementary capability and reciprocal learning. In this research, “Problem” is an umbrella term that refers to both categories of “human-CPPS task” (i.e. a specific piece of work required to be done) and “failure event” (i.e. a state of difficulty that needs to be resolved). A holistic ontological framework is proposed, entitled PSP Ontology (Problem, Solution, Problem-Solver Ontology), which represents the logical relations between the three super-concepts of “Problem Profile”, “Problem-Solver Profile”, and “Solution Profile”. Related entities are formalized by introducing (i) contingency vector, (ii) vector of competence and autonomy, and (iii) solution maturity index, respectively. PSP Ontology is utilized for semantic representation of the super-concepts and reasoning out the competence questions, i.e. in which situation and under which conditions human and/or CPPS is dominant or eligible to solve a problem (to accomplish a given task and/or to detect or eliminate a failure), which is qualitatively exemplified in the use-case of maintenance 4.0.

Smart Collaborative Balancing for Dependable Network Components in Cyber-Physical Systems

Abstract: The evolution of cyber–physical system (CPS) benefits from substantial supports of many cutting-edge technologies. However, as a significant medium to bridge virtual and reality parts, the dependability of various network components is facing unprecedented challenges and threats. In this article, we propose a smart collaborative balancing (SCB) scheme to dynamically adjust the orchestration of network functions and efficiently optimize the workflow patterns. First, mathematical models of bandwidth allocation for multiuser with appropriate probability distribution are established. Matrix operations are utilized to solve the relevant issues based on individual congestion windows. Invasion defense mechanisms are also provided and discussed. Second, specific procedures of collaboration among different network components are presented. The capabilities of CPS, in terms of bandwidth allocation and invasion defense, are guaranteed via novel queueing policies and access control mechanisms. Third, we build a comprehensive prototype including multiple domains and users for validations. Experimental results in two scenarios illustrate that SCB not only supports service reliability of end hosts with different priorities, but also resists malicious attacks which are targeting the corresponding terminals inside domains. Compared to the benchmarks in software defined networks and traditional Internet, our scheme performs better in both available resource management and abnormal flow recognition aspects.

A Survey of Blockchain Enabled Cyber-Physical Systems

Abstract: Cyber-physical systems (CPS) is a setup that controls and monitors the physical world around us. The advancement of these systems needs to incorporate an unequivocal spotlight on making these systems efficient. Blockchains and their inherent combination of consensus algorithms, distributed data storage, and secure protocols can be utilized to build robustness and reliability in these systems. Blockchain is the underlying technology behind bitcoins and it provides a decentralized framework to validate transactions and ensure that they cannot be modified. By distributing the role of information validation across the network peers, blockchain eliminates the risks associated with a centralized architecture. It is the most secure validation mechanism that is efficient and enables the provision of financial services, thereby giving users more freedom and power. This upcoming technology provides internet users with the capability to create value and authenticate digital information. It has the capability to revolutionize a diverse set of business applications, ranging from sharing economy to data management and prediction markets. In this paper, we present a holistic survey of various applications of CPS where blockchain has been utilized. Smart grids, health-care systems, and industrial production processes are some of the many applications that can benefit from the blockchain technology and will be discussed in the paper.

Cloud-Based Industrial Cyber–Physical System for Data-Driven Reasoning: A Review and Use Case on an Industry 4.0 Pilot Line

Abstract: Nowadays, reconfiguration and adaptation by means of optimal re-parameterization in Industrial Cyber–Physical Systems (ICPSs) is one of the bottlenecks for the digital transformation of the manufacturing industry. This article proposes a cloud-to-edge-based ICPS equipped with machine learning techniques. The proposed reasoning module includes a learning procedure based on two reinforcement learning techniques, running in parallel, for updating both the data-conditioning and processing strategy and the prediction model. The presented solution distributes computational resources and analytic engines in multiple layers and independent modules, increasing the smartness and the autonomy for monitoring and control the behavior at the shop floor level. The suitability of the proposed solution, evaluated in a pilot line, is endorsed by fast time response (i.e., 0.01 s at the edge level) and the appropriate setting of optimal operational parameters for guaranteeing the desired quality surface roughness during macro- and micro-milling operations.

Sustainable and flexible industrial human machine interfaces to support adaptable applications in the Industry 4.0 paradigm

Abstract: The Industry 4.0 paradigm introduced several technologies in the industrial manufacturing landscape, highlighting the Cyber Physical Systems, Internet of Things and Visual Computing as some of the ...