Abstract
Modern production is impossible to imagine without integrated data management information systems that ensure the stability of technological, financial, logistical and other processes. The concept is based on the construction of a single information space based on advanced information technologies. One of the key aspects of building a single information space of the enterprise is the integration of automated systems of all divisions of the enterprise into a single information space. The implementation of such a concept is the key to improving the efficiency of production processes, reducing the time of development and launch of new products, increasing the total output. Moreover, it happens with the simultaneous deep integration of project teams of different departments into a single highly professional team of the company, which aims to achieve a common goal. This approach requires appropriate transformations of the information space of the enterprise. The paper considers the elements of the information space, their parameters and relationships that form a single information space of a manufacturing enterprise with critical infrastructure. The elements of the information space are presented in the form of separate nodes with established connections in a fully connected topology. The algorithm for restoring the parameters of atomic elements of the information space in a single information space and the algorithm for identifying the input atomic elements of the information space in a single information space are described. The latter is based on a step-by-step analysis of the features of the object using queries to enable it to make decisions to identify it. The method of identification of the input element of the information space in the information space has been tested with the help of machine learning methods.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
More From: Collection of scientific works of the Military Institute of Kyiv National Taras Shevchenko University
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.