BACKGROUND: An essential condition of existence for enterprises of all forms in the face of rapid external and internal transformations is digital reformation of their business processes. The Saint Petersburg subway is no exception, which has an aging fleet of escalators, for which the introduction of digital technologies, accompanied by the optimization of the control system for the main technological processes, can provide a balance between ever-increasing costs and limited, not always rhythmically flowing supplies. AIMS: To establish one of the possible options for the software architecture for planning and monitoring maintenance and repair of the subway escalator fleet. At the same time, the object of research in the study is the subway escalator fleet, and the subject is automation of the maintenance and repair system. METHODS: Analysis of modern architectural solutions used in the design of software (materials), and the synthesis on their basis of a microservice architecture implemented by tools taken from the field of machine learning and artificial intelligence are the methods used in this study. RESULTS: A significant result of the work for practical application is the proposed scheme of the two-circuit IT landscape of the information system and the block diagram of the software implementing the internal processing circuit. The proposed version of the software is intended for regular use as a tool for monitoring and controlling the register of management objects (works) that create and do not create value for the company (providing/not providing transportation of passenger traffic). At the same time, the implementation of the proposed circuit design solution can be carried out using ready-to-use and free software components, significantly reducing the design time and the cost of its creation and operation. CONCLUSIONS: The results obtained may be one of the options for implementing the concept of digital transformation of the maintenance and repair system of the subway escalator fleet.
In this article, the object of researchers is escalator department, and the subject is the state of difficult technical objects fleet. The purpose of this work is to establish aspects that determine escalator fleet operation, and which can be used as elements of information space for the digital transformation concept of underground tunnel escalator fleet maintenance and repair system. At the same time, the main task is the state of equipment fleet comprehensive analysis. The solving task methods used in this work are the elements of mathematical statistics and expert assessments. As a result of a comprehensive analysis of the state of the fleet, it was found that the types of escalators with a long history of operation are characterized by stable operation. In turn, for new types of escalators with a short history of operation, there is a tendency to increase the number of violations of normal operation. A significant result of the work for practical application is a matrix method of scoring the influence of factors on subsystems. The proposed method established predominance of design and organization of operation factors, and among the subsystems, the predominance of transporting and driving. The results obtained in the article are suitable for further use in the information space that implements the concept of digital transformation of the maintenance and repair system. Keywords:еscalator, escalator fleet, transport hub, digital transformation
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.