<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The possibilities of using cognitive technologies in the organization of systematic industrial enterprise management are described in the article. Strategic links are defined in the development of a system of stochastic models of enterprise management based on artificial intelligence. The possibility of introduction of the Perceptron model in the industrial enterprise management with the purpose of identification of “bottlenecks” in the functionality of business activity and improvement of procedures of decision-making in the framework of creation of the program of development and technical re-equipment of the enterprise is proven. The authors offered an organizational and economic mechanism of operation of an industrial enterprise, which includes new means of implementation of managerial actions through the use of a matrix of assessment of the level of implementation of cognitive technologies. The method of determining priority directions for the implementation of cognitive technologies at an enterprise was developed based on the results of the assessment of the depth of penetration of cognitive technologies and the result obtained from their implementation, which additionally takes into account the resource ratio of the implemented technologies defined as the ratio of estimates of the actual level of competencies to what is needed to work with new cognitive technologies, which allows to obtain the planned economic and organizational effect.</p></abstract>

The possibilities of using cognitive technologies in the organization of systematic industrial enterprise management are described in the article. Strategic links are defined in the development of a system of stochastic models of enterprise management based on artificial intelligence. The possibility of introduction of the Perceptron model in the industrial enterprise management with the purpose of identification of “bottlenecks” in the functionality of business activity and improvement of procedures of decision-making in the framework of creation of the program of development and technical re-equipment of the enterprise is proven. The authors offered an organizational and economic mechanism of operation of an industrial enterprise, which includes new means of implementation of managerial actions through the use of a matrix of assessment of the level of implementation of cognitive technologies. The method of determining priority directions for the implementation of cognitive technologies at an enterprise was developed based on the results of the assessment of the depth of penetration of cognitive technologies and the result obtained from their implementation, which additionally takes into account the resource ratio of the implemented technologies defined as the ratio of estimates of the actual level of competencies to what is needed to work with new cognitive technologies, which allows to obtain the planned economic and organizational effect.

Cognitive Technologies in the Management and Formation of Directions of the Priority Development of Industrial Enterprises

Management Systems in Production Engineering

This work is licensed under the Creative Commons Attribution 4.0 Public License.

The possibilities of using cognitive technologies in the organization of systematic industrial enterprise management are described in the article. Strategic...

Cognitive Technologies in the Management and Formation of Directions of the Priority Development of Industrial Enterprises

Published Online: May 26, 2020

Page range: 133 - 138

Received: Jan 01, 2020

Accepted: Mar 01, 2020

DOI: https://doi.org/10.2478/mspe-2020-0020

Keywords
enterprise management, stochastic model, artificial intelligence, cognitive model, perceptron, neural network, digital innovation, economic effect

© 2020 Aleksy Kwilinski et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 Public License.

Cognitive Technologies in the Management and Formation of Directions of the Priority Development of Industrial Enterprises

Published Online: May 26, 2020

Page range: 133 - 138

Received: Jan 01, 2020

Accepted: Mar 01, 2020

DOI: https://doi.org/10.2478/mspe-2020-0020

Keywordsenterprise management, stochastic model, artificial intelligence, cognitive model, perceptron, neural network, digital innovation, economic effect

© 2020 Aleksy Kwilinski et al., published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 Public License.

Keywords
enterprise management, stochastic model, artificial intelligence, cognitive model, perceptron, neural network, digital innovation, economic effect