Operational Management of Production for Car Maintenance and Repair Using Digital Twin Technology

Evgeniy Kozin
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Evgeniy Kozin: Industrial University of Tyumen

A chapter in The Future of Industry, 2024, pp 205-218 from Springer

Abstract: Abstract The article discusses approaches to creating a digital twin of a car service station. Given the six levels of evolution of digital twins identified by experts, the work proposes ways for implementing the first three levels. The first level of the digital twin is directed to reflect a piece of information about the actual state of the production area by analyzing the flow of frames from a video camera installed in the area and a neural network that makes it possible to detect cars and mechanics in these frames. The second level is a virtual model of the production zone. The model allows one to visually evaluate the current state of the technological operations performed by mechanics and the quality of the work performed. The third level of the digital twin allows predicting the technological route of mechanics, taking into account the established list of influencing factors, among which are the need for work indicated by the client, the probability of related work occurring, etc. The research applied computer vision methods using convolutional neural networks, simulation modeling and technology for creating digital twins of production facilities. The developed neural network model allows determining key points of the technological route and binding them to time markers. As an efficiency criterion, it is proposed to use the current production losses of the enterprise associated with the ineffective organization of the production process and the incorrect choice of technological routes for mechanics. The developed methodology is presented in the form of an algorithm for using a neural network to determine a technological route, which can be applied to develop a software product for the operational management of production for vehicle maintenance and repair. The practical significance of the findings lies in the development of a methodology for using neural networks to assess the efficiency of the car maintenance and repair process, which can be used by automobile manufacturers.

Keywords: Service station; Digital twin; Production management; Automobiles; Maintenance and repair; Optimization (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-031-66801-2_14

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DOI: 10.1007/978-3-031-66801-2_14

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