Technical solutions for the implementation of a software and hardware complex for food quality management-Reference-Cited by-同舟云学术

Technical solutions for the implementation of a software and hardware complex for food quality management

Published:2021-12-22 Issue:4 Volume:83 Page:49-56
ISSN:2310-1202
Container-title:Proceedings of the Voronezh State University of Engineering Technologies
language:
Short-container-title:Vestn. Voronež. gos. univ. inž. tehnol.

Author:

Muzyka M. Y.¹^ORCID,Blagoveshchensk I. G.¹^ORCID,Blagoveshchensk V. G.¹^ORCID,Golovin V. V.¹^ORCID,Blagoveshchensk M. M.¹^ORCID,Kachura I. A.²^ORCID

Affiliation:

1. Moscow State University of Food Production

2. Department of Education and Science of the city of Moscow

Abstract

The problem of technical solutions for the implementation of a software and hardware complex for food quality management is considered. The review and analysis of existing modern control systems is presented, which made it possible to conclude that today food enterprises need new effective solutions using highly efficient intelligent technologies. The analysis of the possibility of intellectualization of the food production quality management system is carried out. The main tasks of this system are presented. It is shown that a practical basis for the implementation of this problem can be the creation of a software and hardware complex for an automated food quality control system using artificial intelligence technologies, which includes neural network technologies, computer vision systems, simulation modeling and an effective combination of hybrid methods and technologies in its arsenal. Methods, algorithms and technologies for the development of the investigated software and hardware complex of an intelligent automated food quality control system are analyzed. The developed generalized functional structure of such an intelligent system and the main stages of its implementation are presented. The main types of support for this system have been developed: information, mathematical and software. The main stages of decision-making on the quality of finished food products have been developed. The necessary technical means are recommended for the implementation of the system. For the practical implementation of the developed intelligent system, the CP1EE14DRA controller from Omron was chosen - a modular programmable controller. As an operator's workstation, a choice should be made in favor of Siemens products - SIMATIC Panel PC. For the tasks of data storage and implementation of calculations, a conventional personal server equipped with a powerful processor, for example, IntelCorei7, has been proposed. It is shown that the implementation of the developed intelligent automated food quality management system makes food industry enterprises more efficient and safe.

Publisher

FSBEI HE Voronezh State University of Engineering Technologies

Subject

General Agricultural and Biological Sciences

Reference20 articles.

1. Balykhin M.G., Borzov A.B., Blagoveshchensky I.G. Methodological foundations for the creation of expert systems for monitoring and predicting the quality of food products using intelligent technologies. Moscow, Frantera, 2017. 338 p. (in Russian).

2. Blagoveshchensky V.G. and others. Development of an expert quality control system in the process of making halva. Living systems and biological safety of the population: collection of materials of the XV international scientific conference of students and young scientists. 2017. pp. 132-137. (in Russian).

3. Blagoveshchensky V.G. et al. Development of a hardware and software complex for monitoring halva production. Development of the food and processing industry in Russia: personnel and science. 2017. pp. 196-199. (in Russian).

4. Balykhin M.G., Borzov A.B., Blagoveshchensky I.G. Architecture and the basic concept of creating an intelligent expert system for quality control of food products. Food Industry. 2017. no. 11. pp. 60 - 63. (in Russian).

5. Kharitonova P.N., Karelina E.B., Blagoveshchensky V.G., Kleho D.Yu. et al. Implementation of the digital twin of management in technological production. In the collection: Intelligent systems and technologies in the food industry: collection of conference materials. 2019. pp. 171–180. (in Russian).