scholarly journals V-nets, new formalism to manage diagnosis problems in Cyber-Physical Systems (CPS) and industrial applications

2020 ◽  
Vol 53 (5) ◽  
pp. 197-202
Author(s):  
J.W. Vásquez-Capacho
Keyword(s):  
Cyber Physical Systems ◽  
Industrial Applications ◽  
New Formalism ◽  
Physical Systems

ROBIN: An open-source middleware for plug‘n’produce of Cyber-Physical Systems

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142091031
Author(s):  
Rafael Arrais ◽  
Paulo Ribeiro ◽  
Henrique Domingos ◽  
Germano Veiga
Keyword(s):  
Open Source ◽  
Industrial Revolution ◽  
Cyber Physical Systems ◽  
Industrial Applications ◽  
Mobile Manipulator ◽  
Battery Management ◽  
Efficient Manner ◽  
Physical Systems ◽  
Data Interchange ◽  
Automation Equipment

Motivated by the Fourth Industrial Revolution, there is an ever-increasing need to integrated Cyber-Physical Systems in industrial production environments. To address the demand for flexible robotics in contemporary industrial environments and the necessity to integrate robots and automation equipment in an efficient manner, an effective, bidirectional, reliable and structured data interchange mechanism is required. As an answer to these requirements, this article presents ROBIN, an open-source middleware for achieving interoperability between the Robot Operating System and CODESYS, a softPLC that can run on embedded devices and that supports a variety of fieldbuses and industrial network protocols. The referred middleware was successfully applied and tested in various industrial applications such as battery management systems, motion, robotic manipulator and safety hardware control, and horizontal integration between a mobile manipulator and a conveyor system.

Cloud-Integrated Cyber-Physical Systems for Complex Industrial Applications

2015 ◽  
Vol 21 (5) ◽  
pp. 865-878 ◽  
Author(s):  
Zhaogang Shu ◽  
Jiafu Wan ◽  
Daqiang Zhang ◽  
Di Li
Keyword(s):  
Cyber Physical Systems ◽  
Industrial Applications ◽  
Physical Systems

A Survey on Network Intrusion Detection Using Deep Generative Networks for Cyber-Physical Systems

2021 ◽  
pp. 137-159
Author(s):  
Srikanth Yadav M. ◽  
Kalpana R.
Keyword(s):  
Deep Learning ◽  
Intrusion Detection ◽  
Critical Infrastructure ◽  
Cyber Physical Systems ◽  
Industrial Applications ◽  
Network Intrusion Detection ◽  
Primary Concern ◽  
Physical Systems ◽  
Detection Systems ◽  
Network Intrusion

In the present computing world, network intrusion detection systems are playing a vital part in detecting malicious activities, and enormous attention has been given to deep learning from several years. During the past few years, cyber-physical systems (CPSs) have become ubiquitous in modern critical infrastructure and industrial applications. Safety is therefore a primary concern. Because of the success of deep learning (DL) in several domains, DL-based CPS security applications have been developed in the last few years. However, despite the wide range of efforts to use DL to ensure safety for CPSs. The major challenges in front of the research community are developing an efficient and reliable ID that is capable of handling a large amount of data, in analyzing the changing behavioral patterns of attacks in real-time. The work presented in this manuscript reviews the various deep learning generative methodologies and their performance in detecting anomalies in CPSs. The metrics accuracy, precision, recall, and F1-score are used to measure the performance.

scholarly journals Digital twins as run-time predictive models for the resilience of cyber-physical systems: a conceptual framework

2021 ◽  
Vol 379 (2207) ◽  
pp. 20200369
Author(s):  
Francesco Flammini
Keyword(s):  
Conceptual Framework ◽  
Autonomous Systems ◽  
Three Dimensional ◽  
Cyber Physical Systems ◽  
Industrial Applications ◽  
Physical Systems ◽  
Digital Twins ◽  
Self Adaptation ◽  
Run Time ◽  
Three Dimensional Models

Digital twins (DT) are emerging as an extremely promising paradigm for run-time modelling and performability prediction of cyber-physical systems (CPS) in various domains. Although several different definitions and industrial applications of DT exist, ranging from purely visual three-dimensional models to predictive maintenance tools, in this paper, we focus on data-driven evaluation and prediction of critical dependability attributes such as safety. To that end, we introduce a conceptual framework based on autonomic systems to host DT run-time models based on a structured and systematic approach. We argue that the convergence between DT and self-adaptation is the key to building smarter, resilient and trustworthy CPS that can self-monitor, self-diagnose and—ultimately—self-heal. The conceptual framework eases dependability assessment, which is essential for the certification of autonomous CPS operating with artificial intelligence and machine learning in critical applications. This article is part of the theme issue ‘Towards symbiotic autonomous systems’.

scholarly journals ANALYSIS OF PROSPECTS AND OPPORTUNITIES OF CYBER-PHYSICAL SYSTEMS EDUCATION

2020 ◽  
Vol 1 ◽  
pp. 60-65
Author(s):  
Galina Nikolcheva
Keyword(s):  
Industry 4.0 ◽  
Cyber Physical Systems ◽  
Industrial Applications ◽  
Digital Transformation ◽  
Cyber Physical System ◽  
Pilot Projects ◽  
Laboratory Practice ◽  
Good Practices ◽  
Physical Systems ◽  
Industry Standards

The readiness for digital transformation of industry is highly dependent from the existence of enough ICT experts with profiles to industrial applications and cyber-physical systems as well as the widespread promotion and application of existing industry standards and practices in the domain of Industry 4.0. The raising of the digital readiness index for the industry requires the development of educational and scientific initiatives in order to create capacity for institutional and organizational acceptance of the requirements and prerequisites of Industry 4.0 as well the creation of pilot projects and demonstration installations for the purpose of visualizing and presenting good practices. This paper analyses prospects and opportunities of Cyber-physical system education in order to prepare well-trained and capable specialists for Industry 4.0. Some good practices in this area are outlined. Ideas for building the foundation of the training as well as the organization of the laboratory practice are presented.

Application Scenarios of Smart Glasses in the Industrial Sector

i-com ◽  
2016 ◽  
Vol 15 (2) ◽  
Author(s):  
Sebastian Hobert ◽  
Matthias Schumann
Keyword(s):  
Human Computer Interaction ◽  
Structural Changes ◽  
Business Models ◽  
Industrial Sector ◽  
Cyber Physical Systems ◽  
Industrial Applications ◽  
Factory Workers ◽  
Physical Systems ◽  
Smart Glasses ◽  
Computer Interaction

AbstractMany companies in the industrial sector are currently facing massive changes in order to optimize processes and enable new customer demands (e. g. mass customization of products). Often, these changes are related to a modernization of existing infrastructure to enable cyber-physical systems and smart factories (so called Industry 4.0). These structural changes have effects on business processes and business models. Consequently, the factory workers need to adapt to the changing infrastructure and therefore, it is necessary to analyze how factory workers can be supported during their day-to-day work in the changed environment. Thus, an important aspect is the analysis of human computer interaction interfaces which aim at assisting factory workers. One promising human computer interface solution between cyber-physical systems and factory workers are smart glasses, as this technology is suited for assisting humans hands-free. Since prior research on application scenarios of smart glasses in the industrial sector is limited, the aim of our research is to identify relevant application scenarios. Therefore, we conducted a qualitative, explorative study by interviewing 21 domain experts. Based on this, we derived 15 application scenarios which can be used by both, research and practice, to develop and evaluate new human computer interaction interfaces for industrial applications.

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