scholarly journals RESEARCH OF DIKW AND 5C ARCHITECTURAL MODELS FOR CREATION OF CYBER-PHYSICAL PRODUCTION SYSTEMS WITHIN THE CONCEPT OF INDUSTRY 4.0

2021 ◽  
pp. 132-140
Author(s):  
Sergei Osadchy ◽  
Nataliia Demska ◽  
Yuriy Oleksandrov ◽  
Viktoriia Nevliudova
Keyword(s):  
Production System ◽  
Production Systems ◽  
Structural Level ◽  
Sensors And Actuators ◽  
Industrial Systems ◽  
Decomposition Structure ◽  
Architectural Model ◽  
Architectural Models ◽  
Cyber Physical Production Systems ◽  
Interpretation Model

The development of cyber-physical production systems is a complex scientific and technical task, therefore the developer needs to determine the requirements, tasks for the system being developed and choose an architectural model for its implementation. In turn, the choice of an architectural model assumes a balance for the set of requirements of persons interested in its development. In a typical case, the development of a specific cyber-physical industrial systems needs to be adapted to the means of implementation, to the realities of its future use, maintenance and evolution. Subject matter of this study are architectural models for building complex cyber-physical production systems. Goal of this article is a study of architectural models DIKW and 5C, according to the results of the decomposition of which, in the future, it will be possible to carry out a mathematical description of elementary problems of each level and their physical or simulation modeling. To achieve this goal, it is necessary to solve the following tasks: analyze the DIKW model; analyze the architectural model 5C; compare the DIKW model and the 5C architectural model, using its structural decomposition into levels, information and command channels with feedback within each structure.  The research carried out is based on the methods of decomposition and formalized representation of systems. Conclusions: Based on the results of the decomposition at each structural level of the DIKW and 5C models, a decomposition structure was developed, which shows the main differences and general similarities of the models. It was revealed that the 5C model, as a common software shell that combines integrated sensors and actuators, is more suitable for solving problems of developing a cyber-physical production system, and the DIKW interpretation model is more suitable for solving problems of modifying existing systems at enterprises, and the choice of the model itself the development of a cyber-physical production system depends on the requirements of the customer, existing equipment, the level of its automation and the level of project financing.

User-Guided Visual Analysis of Cyber-Physical Production Systems

2017 ◽  
Vol 17 (2) ◽  
Author(s):  
Tobias Post ◽  
Rebecca Ilsen ◽  
Bernd Hamann ◽  
Hans Hagen ◽  
Jan C. Aurich
Keyword(s):  
Information And Communication Technology ◽  
Communication Technology ◽  
Production System ◽  
High Performance ◽  
Visual Analysis ◽  
Production Systems ◽  
Physical Systems ◽  
Information And Communication ◽  
Cyber Physical Production Systems ◽  
Constituent Elements

Modern cyber-physical production systems (CPPS) connect different elements like machine tools and workpieces. The constituent elements are often equipped with high-performance sensors as well as information and communication technology, enabling them to interact with each other. This leads to an increasing amount and complexity of data that requires better analysis tools to support system refinement and revision performed by an expert. This paper presents a user-guided visual analysis approach that can answer relevant questions concerning the behavior of cyber-physical systems. The approach generates visualizations of aggregated views that capture an entire production system as well as specific characteristics of individual data features. To show the applicability of the presented methodologies, an exemplary production system is simulated and analyzed.

Reliable software-based control as enabler for flexible production systems

2017 ◽  
Vol 65 (12) ◽  
Author(s):  
Santiago Soler Perez Olaya ◽  
Stefan Mätzler ◽  
Martin Wollschlaeger
Keyword(s):  
Production Systems ◽  
Networked Control Systems ◽  
Information Source ◽  
System Structure ◽  
Industrial Systems ◽  
Control Approach ◽  
Control Value ◽  
Flexible Production Systems ◽  
Cyber Physical Production Systems ◽  
And Control

AbstractThe current evolution of the industrial production systems to cyber physical production systems requires an increased flexibility of the system structure that is nowadays still difficult to find in the industrial systems. The control applications are extremely strict by requiting jitter-free communication of sensor and control values in networked control systems. The software-based control approach presented here enhances the reliability of the control system using a control value matrix as information source. This approach benefits of predictive control algorithms that rely on model-based strategies.

scholarly journals Development of a Decision Support System for 3D Printing Processes based on Cyber Physical Production Systems

Procedia CIRP ◽  
2021 ◽  
Vol 98 ◽  
pp. 348-353
Author(s):  
Rishi Kumar ◽  
Christopher Rogall ◽  
Sebastian Thiede ◽  
Christoph Herrmann ◽  
Kuldip Singh Sangwan
Keyword(s):  
Decision Support ◽  
3D Printing ◽  
Decision Support System ◽  
Support System ◽  
Production Systems ◽  
Cyber Physical Production Systems ◽  
Printing Processes

scholarly journals Soil Bacterial Community Diversity and Composition as Affected by Tillage Intensity Treatments in Corn-Soybean Production Systems

2021 ◽  
Vol 12 (1) ◽  
pp. 157-172
Author(s):  
Shankar G. Shanmugam ◽  
Normie W. Buehring ◽  
Jon D. Prevost ◽  
William L. Kingery
Keyword(s):  
Microbial Community ◽  
Bacterial Community ◽  
Community Composition ◽  
Production System ◽  
Soil Microbial Community ◽  
Production Systems ◽  
Bacterial Community Composition ◽  
Soybean Production ◽  
Soil Microbial ◽  
Soil Bacterial

Our understanding on the effects of tillage intensity on the soil microbial community structure and composition in crop production systems are limited. This study evaluated the soil microbial community composition and diversity under different tillage management systems in an effort to identify management practices that effectively support sustainable agriculture. We report results from a three-year study to determine the effects on changes in soil microbial diversity and composition from four tillage intensity treatments and two residue management treatments in a corn-soybean production system using Illumina high-throughput sequencing of 16S rRNA genes. Soil samples were collected from tillage treatments at locations in the Southern Coastal Plain (Verona, Mississippi, USA) and Southern Mississippi River Alluvium (Stoneville, Mississippi, USA) for soil analysis and bacterial community characterization. Our results indicated that different tillage intensity treatments differentially changed the relative abundances of bacterial phyla. The Mantel test of correlations indicated that differences among bacterial community composition were significantly influenced by tillage regime (rM = 0.39, p ≤ 0.0001). Simpson’s reciprocal diversity index indicated greater bacterial diversity with reduction in tillage intensity for each year and study location. For both study sites, differences in tillage intensity had significant influence on the abundance of Proteobacteria. The shift in the soil bacterial community composition under different tillage systems was strongly correlated to changes in labile carbon pool in the system and how it affected the microbial metabolism. This study indicates that soil management through tillage intensity regime had a profound influence on diversity and composition of soil bacterial communities in a corn-soybean production system.

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