Proceedings of the International scientific and practical conference ―Science and Global Development‖ (February 20-22, 2026) / Publisher website: www.naukainfo.com. – Barcelona, Spain, 2026. - 229 p.

86 Their practical significance lies in their key role in evaluating the service life and durability of mechanical systems. The matrix demonstrates that no single methodology is universal; rather, effective confirmation of the reliability of mechanical systems is achieved through a combination of several standardized tests. For basic certification, static and hardness tests are generally sufficient. For complex and critical structures, it is advisable to complement them with biaxial and tribological testing. Thus, the effectiveness matrix can serve as a tool for selecting an optimal set of tests depending on technical requirements, the level of structural responsibility, and the resource capabilities of an enterprise. National standards such as DSTU, EN, ISO 6892-1:2022 (Metallic materials – Tensile testing) and DSTU, EN, ISO 527-1:2017 (Plastics – Determination of tensile properties) are examples of regulatory documents that establish strict procedures for conducting such tests [6]. Importantly, testing standards not only describe the procedures themselves but also provide a structured framework for interpreting results, which is critical for confirming the durability and reliability of the final product. It is essential to consider the role of standardized testing in reliability verification. The reliability of a mechanical system is defined as the ability of a product to perform its functions over a specified period without failure under real operating conditions. Standardized testing methodologies constitute one of the primary instruments for ensuring such reliability, as they: - provide reproducible testing parameters and eliminate subjective operator influence; - enable comparison of results across different batches of materials and products; - facilitate the correlation of experimental data with mechanical models and predictive calculations under service conditions.