Кафедра "Інтернет речей"

Постійне посилання колекціїhttps://repository.kpi.kharkov.ua/handle/KhPI-Press/5398

Увага! Поповнення колекції кафедри "Інтернет речей" – призупинено.

Від вересня 2022 року кафедри "Інтернет речей" та "Мультимедійних інформаційних технологій і систем" об’єднані у кафедру "Мультимедійні та інтернет технології і системи".

Первісна назва кафедри – "Розподілені інформаційні системи і хмарні технології".

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Synthesis of algorithms for stabilization ofthe level of inter-operative backlogs of the production flow line
(Національний технічний університет "Харківський політехнічний інститут", 2020) Pihnastyi, O. M.; Khodusov, V. D.
The report discusses methods for constructing algorithms for optimal stabilization of the value of inter-operational backlogs of the production flow line.
On the methods of the statistical theory of control system of production lines
(Національний технічний інститут "Харківський політехнічний інститут", 2015) Azarenkov, N. A.; Pihnastyi, O. M.; Khodusov, V. D.
The analysis of modern methods of organization and management of production is given.
Entropy method in the models industrial process control
(Національний технічний інститут "Харківський політехнічний інститут", 2013) Azarenkov, N. A.; Pihnastyi, O. M.; Khodusov, V. D.
For the first time, the importance of the entropy method in control theory has Dzh. Fon Neumann. Entropy approach to modeling the processes discussed in detail B. N. Petrov, I. V. Prangishvili. The entropy of the process is associated with the distribution function of process parameters on the possible states. The distribution function of the items of work is not explicitly linked to the parameters describing the state of the items of work in the technological processing.
To a question on application of the statistical theory for the description of industrial systems
(2009) Khodusov, V. D.; Pihnastyi, O. M.
The application of the methods of Statistical Physics for its description is possible owing to the representation of the manufacturing firm with mass production output as a system with a large number of elements (the basic products) of stochastic nature, which is in the production process. The behavior of the basic products along the technological chain depends on the definite manufacturing and technological laws in accordance with the technological process of the manufacturing firm, its production plan, the availability of manpower resources and equipment. The state of the production system’s basic products at any instant of time is given as the point in two-dimensional phase space. The function of the basic product’s distribution in the rate of expense’s variation is set and the equation similar to the kinetic equation in Physics is written down. The engineer-production function, which is analogous to the force moving the basic product along the technological chain of the production process, is set and can be determined from the technical documentation of the manufactured article approved in the manufacturing firm. The producer function, which describes the interaction of the basic products (the system’s elements) during their moving along the technological chain of the production process with technical equipment, is based on the equipment disposition schemes and its technical characteristics according to the operating mode of half-finished products. Using the kinetic equation a closed system of balances equations is written down in a zero approximation on a small parameter for the moments of the distribution function. The system of balances equations describes the behavior of the basic economic macroscopic quantities of the production system, such as reserve, pace, and dispersion of the production output along the technological chain. From the balances, equations were obtained the well-known relations in business operation theory for the calculation of reserves and places of the production output.
Neural model of conveyor type transport system
(2020) Pihnastyi, O. M.; Khodusov, V. D.
In this paper, a model of a transport conveyor system using a neural network is demonstrated. The analysis of the main parameters of modern conveyor systems is presented. The main models of the conveyor section, which are used for the design of control systems for flow parameters, are considered. The necessity of using neural networks in the design of conveyor transport control systems is substantiated. A review of conveyor models using a neural network is performed. The conditions of applicability of models using neural networks to describe conveyor systems are determined. A comparative analysis of the analytical model of the conveyor section and the model using the neural network is performed. The technique of forming a set of test data for the process of training a neural network is presented. The foundation for the formation of test data for learning neural network is an analytical model of the conveyor section. Using an analytical model allowed us to form a set of test data for transient dynamic modes of functioning of the transport system. The transport system is presented in the form of a directed graph without cycles. Analysis of the model using a neural network showed a high-quality relationship between the output flow for different conveyor sections of the transport system.
The statement of the task of optimal control of the production line using the additional time of equipment operation
(Харківський національний університет ім. В. Н. Каразіна, 2019) Khodusov, V. D.; Pihnastyi, O. M.
The production line of an enterprise with a flow method of organizing production is considered as a dynamic distributed system. The technological route for manufacturing products for many modern enterprises contains several hundreds of technological operations, in the inter-operating reserve of each of which there are thousands of products awaiting processing. Technological routes of different parts of the same type of products intersect. This leads to the fact that the distribution of sybjects of labour along the technological route has a significant impact on the throughput capacity of the production line. To describe such systems, a new class of production line models (PDE-model) has been introduced. Models of this class use partial differential equations to describe the behaviour of production line flow parameters. In this article, a PDE-model of the production line is built, the flow parameters of which depend on the load factor of the process equipment for each operation. For the description of a distributed dynamic system, the PDE model of the production line was used. At the same time, the single-shift mode of operation of a production enterprise is considered as a basic mode of operation.