A SYSTEMIC-ONTOLOGICAL APPROACH TO ANALYZING THE LIFE CYCLE OF COMPLEX TECHNICAL OBJECTS
Abstract
The increasing complexity of modern technical objects and their integration into digital and automated systems require advanced approaches to the analysis and management of their life cycle. Traditional linear representations of the life cycle are insufficient to describe the dynamic, iterative, and multi-level nature of complex technical objects, especially in the context of information-measurement technologies and automated decision-making. This paper addresses the problem of formalized knowledge representation of the life cycle of a complex technical object using an ontological approach. The study analyzes recent Scopus-indexed research related to ontology-based product lifecycle management, digital twins, and semantic modeling, revealing limitations associated with domain-specific models and the implicit treatment of life cycle stages. To overcome these limitations, a formalized ontological model of the life cycle of a complex technical object, represented as a complex technical system, is proposed. The model explicitly defines sets of stages and phases, relations between them, operations performed at different stages, and temporal parameters governing system evolution. Special attention is paid to the granularity of the life cycle, enabling representation at different levels of abstraction and allowing for overlapping and iterative stages. The proposed ontological framework provides a methodological basis for integrating measurement data, diagnostic information, and quality indicators across the entire life cycle of a complex technical object. From the standpoint of measurement science, the model supports semantic consistency, traceability of information, and interoperability within information-measurement and automated systems. The results of the study can be applied in the development of intelligent measurement systems, decision support tools, and life cycle management frameworks for complex technical objects.