DIGITAL TWIN-BASED MANAGEMENT MODEL FOR HIGH-TECH PRODUCTION

Abstract

A management model for high-tech production based on digital twin technology is presented, combining the architecture of a data lake and the principles of ontological engineering and an agent-based service approach. The study examines the problems of managing complex production environments in the context of Industry 4.0, and suggests a hybrid approach combining the principles of a “smart factory” with lean manufacturing methodologies. The model includes a multi-level architecture covering strategic, tactical and operational levels, supported by an agent-service structure for system integration. The aim of the work is to develop an integrated management model for high-tech production based on the integration of digital twin technology, an ontological approach, and an agent-service architecture using a data lake. Methods. The research methodology uses a systematic approach to data management using data lake and electronic passports, and fuzzy ontologies to formalize knowledge. Results. The implementation is demonstrated on the example of multiscale modeling of chemical materials and compounds, where the effectiveness of the model is quantified. The results indicate a significant increase in productivity, especially in data retrieval operations, as structured search protocols demonstrate higher efficiency compared to traditional approaches. Conclusion. The results show that integration of digital twins with ontological structures and architectures of agency services provides enhanced operational control and decision-making capabilities in high-tech production environments. The practical application of the model demonstrates its scalability and adaptability in various industries, contributing to both theoretical understanding and practical implementation of advanced production systems. This research develops the field of high-tech production management by providing a structured framework for the digital transformation of production operations.