An improved cyber-physical systems architecture for Industry 4.0 smart factories

Jiang, Jehn-Ruey

doi:10.1177/1687814018784192

Cited by 81 publications

(49 citation statements)

References 25 publications

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“…However, the cited paper does not address modern cyber threats to IT-and OT infrastructures taking into consideration their synergy and hybridity. Study [11] offers the architecture of CPPS 8C by adding 3C faces to the 5C architecture. The author emphasizes the horizontal integration of CPPS as the integration of different parties and the associated information component (content).…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

Development of an architectural-logical model to automate the management of the process of creating complex cyber-physical industrial systems

Nevliudov

Yevsieiev

Maksymova

et al. 2020

EEJET

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Modern highly technological production puts forward new requirements and approaches to the implementation of the Industry 4.0 concept. To achieve this, it is necessary to develop a cyber-physical production system that would make it possible to fully take into consideration all the factors of the actual production system. All solutions must pursue the global goal of making the best use of production time and resources, as well as meet the "Lean Production" concept. Existing ISO-95, 5C, and 8C cyber-physical production systems (CPPS) reference architectures cannot provide clearly expressed systematization and detailing. Such systems are a set of general recommendations that show the interaction processes among the physical and cyber-components of CPPS. This paper reports a new approach to the systemic representation of the processes for managing the development of complex cyber-physical production systems in the face of today's threats. We have suggested a systemic representation of automating the process of managing the development of complex CPPS. Modern threats to the cyber-physical and information and communication systems (ICS) have been considered, which underlie CPPS. An architectural-logical model, as well as methods for automating the CPPS development process management, have been developed. This could help build a logical relationship from the initial "target" stage to the process of obtaining "management algorithms" at each level and stage of CPPS development as a symbiosis of physical and cyber-components. The devised CPPS development process management model provides an opportunity to propose a group of mathematical models and methods that logically link all development stages into a single "rigid" hierarchical sequence. This makes it possible to build a single information space with a set of complex CPPS development methodology. The proposed solutions could enable the development of an automated system to manage the process of the development of complex CPPS

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Section: Literature Review and Problem Statementmentioning

confidence: 99%

Development of an architectural-logical model to automate the management of the process of creating complex cyber-physical industrial systems

Nevliudov

Yevsieiev

Maksymova

et al. 2020

EEJET

View full text Add to dashboard Cite

show abstract

“…In EDM and other works about lasers, welding, etc., CPS are spreading. For instance, EDM edge computing is becoming a leading research line [24]. 5G and IoT will be key to enhancing and enabling the advances in manufacturing.…”

Section: Content Analysismentioning

confidence: 99%

Smart Cyber-Physical Manufacturing: Extended and Real-Time Optimization of Logistics Resources in Matrix Production

et al. 2019

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In the context of Industry 4.0, the matrix production concept represents revolutionary solutions from a technological and logistics point of view. In a matrix production system, flexible, configurable production and assembly cells are arranged in a grid layout, and the in-plant supply is based on autonomous vehicles. Adaptable and flexible material handling solutions are required to perform the dynamically changing supply-demands of standardized and categorized manufacturing and assembly cells. Within the frame of this paper, the authors describe the in-plant supply process of matrix production and the optimization potential in these processes. After a systematic literature review, this paper introduces the structure of matrix production as a cyber-physical system focusing on logistics aspects. A mathematical model of this in-plant supply process is described including extended and real-time optimization from routing, assignment, and scheduling points of view. The optimization problem described in the model is an NP-hard problem. There are no known efficient analytical methods to find the best solution for this kind of problem; therefore, we use heuristics to find a suitable solution for the above-described problem. Next, a sequential black hole–floral pollination heuristic algorithm is described. The scenario analysis, which focuses on the clustering and routing aspects of supply demands in a matrix production system, validates the model and evaluates its performance to increase cost-efficiency and warrants environmental awareness of the in-plant supply in matrix production.

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“…They argued that such an automation system could operate repeatedly in the internal devices of smart factories or in virtual applications in the form of either an interaction pattern or an unstructured mesh. Jiang [21] treated process data originating from continuous production equipment as previously unqualified data, because there was no clear indication of its use. However, it has become available as meaningful information to the manager by recording and sharing the temperature, pressure, and precise position information of the facilities acquired through the smart device, and the recent smart factory-based sensor, communication, and various processing technologies.…”

Section: Sensor-based Smart Factorymentioning

confidence: 99%

Real-Time Early Warning System for Sustainable and Intelligent Plastic Film Manufacturing

Kim

Hwangbo

2019

Sustainability

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In this study, real-time preventive measures were formulated for a crusher process that is impossible to automate, due to the impossibility of installing sensors during the production of plastic films, and a real-time early warning system for semi-automated processes subsequently developed. First, the flow of a typical film process was ascertained. Second, a sustainable plan for real-time forecasting in a process that cannot be automated was developed using the semi-automation method flexible structure production control (FSPC). Third, statistical early selection of the process variables that are most probably responsible for failure was performed during data preprocessing. Then, a new, unified dataset was created using the link reordering method to transform the time sequence of the continuous process into one time zone. Fourth, a sustainable prediction algorithm was developed using the association rule method along with traditional statistical techniques, and verified using actual data. Finally, the overall developed logic was applied to new production process data to verify its prediction accuracy. The developed real-time early warning system for semi-automated processes contributes significantly to the smart manufacturing process both theoretically and practically.

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An improved cyber-physical systems architecture for Industry 4.0 smart factories

Cited by 81 publications

References 25 publications

Development of an architectural-logical model to automate the management of the process of creating complex cyber-physical industrial systems

Development of an architectural-logical model to automate the management of the process of creating complex cyber-physical industrial systems

Smart Cyber-Physical Manufacturing: Extended and Real-Time Optimization of Logistics Resources in Matrix Production

Real-Time Early Warning System for Sustainable and Intelligent Plastic Film Manufacturing

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