Forecasting the Efficiency of the Control System of the Technological Object on the Basis of Neural Networks

Lutska, Nataliia; Zaiets, Nataliia; Vlasenko, Lidiia; Shtepa, V.; Савчук, Ольга Вікторівна

doi:10.1109/mees52427.2021.9598540

Cited by 8 publications

(1 citation statement)

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“…Methods of synthesis of control systems, including robust ones, are thoroughly considered in [22; 23], and the results of successful implementation of the latest control systems for technological objects of the food industry are investigated in [24][25][26].…”

Section: N Lutska Et Almentioning

confidence: 99%

Ontological support system of managerial decision-making of production tasks for a food enterprise

Lutska¹,

Vlasenko²,

Ladanyuk³

et al. 2022

Tehnìka ta energetika

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Resource and energy efficiency of industrial production, in particular, food production, is a defining requirement that will ensure its functioning without loss of quality and quantity of final products. This is achieved by observing the requirements for the operational parameters of the company’s technological processes and their operational changes. Given the complexity of the functioning of the energy component of the world and Ukraine due to military operations and their consequences, the issue of quality/cost ratio has become more acute. Therefore, for large manufacturing enterprises, the development of systems for supporting management decision-making in accordance with the Industry 4.0 concept becomes relevant. This will contribute to improving the production and economic indicators of the enterprise through coordinated actions of all links of production activities by structuring and processing large amounts of heterogeneous information. The purpose of the study is to develop a decision support system for the task of choosing the structure of an automated control system based on an ontological knowledge base. The developed application ontology uses descriptive logic and is interpreted as part of a digital production double implemented by a single ontological knowledge base and ontological repository. Considering existing international standards, the OWL2 language was chosen for the implementation of the ontological knowledge base. The ontology system architecture contains an ontology server, a Node-Red application, and a user form. A project decision support system that issues recommendations based on requests for the structure of the control system for a technological facility with uncertainties, considering the requirements and restrictions set for each technological process of a food enterprise, reduces the time to choose the appropriate structures, schemes, and methods. Thus, the designer receives the necessary information, supported by knowledge from the subject area, for the synthesis of an effective automated control system. It is also assumed that the ontological system will be expanded by connecting new created applied ontologies that implement related tasks of an industrial enterprise

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Section: N Lutska Et Almentioning

confidence: 99%