СТВОРЕННЯ ЦИФРОВОГО ДВІЙНИКА ЦИЛІНДРУ ДВОТАКТНОГО ДВИГУНА У ПАРАМЕТРИЧНОМУ ПРОСТОРІ СИСТЕМІ УПРАВЛІННЯ ЖИТТЄВИМ ЦИКЛОМ

The article explores the transformation of approaches to the use of Product Lifecycle Management (PLM) systems in the context of Industry 4.0 technologies, aimed at achieving strategic goals of sustainable development. Using the example of creating a digital environment for the two-stroke engine cylinder model, the initial stage of integration with the 3DEXPERIENCE platform is presented, demonstrating the practical implementation of the digital twin concept. The study identifies key trends in addressing global environmental challenges, particularly the reduction of carbon emissions and the minimization of natural resource consumption—both of which represent critical tasks throughout all stages of the automotive product lifecycle. The application of sustainable manufacturing technologies is considered a key prerequisite for ensuring the long-term resilience of the industry by combining economic efficiency with social responsibility and environmental safety. As part of the research, a roadmap for adapting modern design and manufacturing principles of cast internal combustion engine (ICE) components within the framework of Industry 4.0 technologies was developed. A comparative analysis of existing PLM systems was carried out, covering a wide range of functional capabilities, each with its own strengths and limitations. Based on a thorough evaluation, the 3DEXPERIENCE platform was reasonably selected due to its support for the full product lifecycle, including the integration of digital design, simulation, and production management tools. Particular attention is paid to the platform’s functionality in enabling decentralized collaboration through cloud infrastructure and centralized data management. Within the digital twin concept, a virtual environment for the cast cylinder component of a two-stroke engine was created, ensuring continuous synchronization between the digital model and real-world manufacturing processes. Further steps for the modernization of the integrated digital model within the PLM system are discussed, including process simulation, stress-strain analysis, and the implementation of innovative materials with predefined physical and mechanical properties. The conclusions highlight the prospects for the development of next-generation, high-level autonomous digital twins that combine artificial intelligence, embedded sensor systems, and big data analytics—enabling significantly greater flexibility, adaptability, and sustainable efficiency in manufacturing systems within the context of Industry 4.0 and its evolution toward Industry 5.0.